{"meta":{"query_hash":"95578f84ce5a","filters":{"topic":"Optimization and Search Problems"},"cohort_total":892,"direct_labels_cover":0,"predictions_cover":892,"exported":892,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/95578f84ce5a","api":"https://metacan.xera.ac/api/v1/cohort?topic=Optimization+and+Search+Problems"},"results":[{"id":"W109938289","doi":"10.1007/978-3-642-22300-6_4","title":"Multi-target Ray Searching Problems","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Heuristics; Multiplicative function; Mathematical optimization; Metric (unit); Disjoint sets; Heuristic; Computer science; Context (archaeology); Measure (data warehouse); Asymptotically optimal algorithm; Mathematics; Algorithm; Search problem; Discrete mathematics; Data mining","score_opus":0.04204162678421279,"score_gpt":0.26768997297691954,"score_spread":0.22564834619270674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W109938289","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00809536,0.0025843868,0.9192465,0.0005277396,0.00017835406,0.000073352334,0.00024708488,0.0003716362,0.06867545],"genre_scores_gemma":[0.32338881,0.0061678994,0.5356307,0.00052339863,0.00050021795,0.00058563054,0.0014500053,0.001010827,0.13074258],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931777,0.00019410039,0.000026822394,0.00014645053,0.0002550477,0.000059823604],"domain_scores_gemma":[0.99890983,0.0007737881,0.000073398194,0.00007963607,0.000097349264,0.00006600419],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009583602,0.0016869917,0.0018015355,0.0011902392,0.0007522251,0.0025759877,0.0018481498,0.003265082,0.013419855],"category_scores_gemma":[0.003486604,0.0008600837,0.0012523505,0.001998635,0.0010358006,0.0022785845,0.002663294,0.0023228552,0.0027241001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026998087,0.0001293828,0.0005186231,0.0007223299,0.0001494713,0.0002812345,0.00018578496,0.58398104,0.0037808705,0.2389748,0.02079002,0.15021645],"study_design_scores_gemma":[0.00005105531,0.000089057576,0.0003465294,0.00010946092,0.000043644854,0.00037028035,0.00008723799,0.8151384,0.0024247835,0.16195372,0.019349813,0.000036010046],"about_ca_topic_score_codex":0.0007147793,"about_ca_topic_score_gemma":0.00056146615,"teacher_disagreement_score":0.013419855,"about_ca_system_score_codex":0.000942805,"about_ca_system_score_gemma":0.000550899,"threshold_uncertainty_score":0.04489392},"labels":[],"label_agreement":null},{"id":"W110884402","doi":"10.1007/978-3-642-34645-3_2","title":"Modeling a Teacher in a Tutorial-like System Using Learning Automata","year":2012,"lang":"en","type":"book-chapter","venue":"Transactions on computational science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Novelty; Process (computing); Benchmark (surveying); Adaptation (eye); Automaton; Domain (mathematical analysis); Artificial intelligence; Field (mathematics); Learning automata; Salient; Convergence (economics); Human–computer interaction; Programming language","score_opus":0.049692438302045436,"score_gpt":0.2845329200457956,"score_spread":0.23484048174375016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W110884402","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054519188,0.000172477,0.9091432,0.0013886594,0.00014596197,0.00013276395,0.00027078242,0.0024509027,0.031776085],"genre_scores_gemma":[0.71742773,0.00026679295,0.23511703,0.0003035586,0.00005951383,0.00033079434,0.00028265076,0.00031269348,0.04589916],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965525,0.00013173644,0.00002126682,0.00009905447,0.000047085454,0.000045666216],"domain_scores_gemma":[0.9988386,0.00061099854,0.000060616127,0.00016743755,0.00018739424,0.00013496264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005446484,0.00038220154,0.0005188027,0.00034005713,0.0008760539,0.0019190996,0.0017757313,0.0019870594,0.016671613],"category_scores_gemma":[0.0031314832,0.00043900957,0.0005537682,0.00030513416,0.00095893384,0.0035432728,0.0016499622,0.0013757331,0.0029904707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039734849,0.00029311073,0.005483581,0.00035730936,0.000094575444,0.00087821094,0.0022828053,0.33210525,0.019586917,0.53773713,0.012044371,0.08873945],"study_design_scores_gemma":[0.000041547068,0.00006943785,0.0002681282,0.00003421296,0.00003263556,0.00014706906,0.00019005433,0.9034356,0.004975427,0.07953514,0.011243532,0.000027316806],"about_ca_topic_score_codex":0.0039524212,"about_ca_topic_score_gemma":0.0050861645,"teacher_disagreement_score":0.016671613,"about_ca_system_score_codex":0.0009503446,"about_ca_system_score_gemma":0.0010763074,"threshold_uncertainty_score":0.055772126},"labels":[],"label_agreement":null},{"id":"W112014004","doi":"","title":"Optimal scheduling of contract algorithms for anytime problems","year":2006,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of Waterloo","funders":"","keywords":"Computer science; Acceleration; Computation; Algorithm; Scheduling (production processes); Mathematical optimization; Schedule; Matching (statistics); Approximation algorithm; Mathematics","score_opus":0.14399056113021236,"score_gpt":0.3591819608483168,"score_spread":0.21519139971810441,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W112014004","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08937823,0.0004065641,0.8996734,0.00043016774,0.00006329563,0.00019676473,0.00011312403,0.00042187047,0.009316531],"genre_scores_gemma":[0.61790997,0.00051050156,0.37659207,0.00014364751,0.000086628344,0.00029820314,0.00033513622,0.00027078085,0.003853069],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972064,0.0009854897,0.0001796982,0.0003737783,0.000734374,0.00052011333],"domain_scores_gemma":[0.9936626,0.0035376255,0.00063416787,0.0010662857,0.0005532888,0.00054595846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003843816,0.0008630357,0.0012452346,0.00062594685,0.0008652807,0.0017365218,0.0020635652,0.000957913,0.0030313232],"category_scores_gemma":[0.01605367,0.0006630218,0.000782123,0.0009909954,0.0020149874,0.0033480471,0.0016293654,0.0018573172,0.00047255954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060351245,0.0001999424,0.00084198324,0.00019092998,0.00004660255,0.000071016766,0.00031308824,0.62766117,0.0025725868,0.30764088,0.002504275,0.05735398],"study_design_scores_gemma":[0.000080537386,0.00007888789,0.000114157316,0.000010931653,0.000011161633,0.000021008631,0.00003354923,0.84268963,0.0011899533,0.15428518,0.0014744743,0.0000105964955],"about_ca_topic_score_codex":0.0024296492,"about_ca_topic_score_gemma":0.0028142598,"teacher_disagreement_score":0.003843816,"about_ca_system_score_codex":0.0023719976,"about_ca_system_score_gemma":0.0030457766,"threshold_uncertainty_score":0.020328283},"labels":[],"label_agreement":null},{"id":"W114064698","doi":"10.1007/978-3-642-25591-5_57","title":"Input-Thrifty Extrema Testing","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Maxima and minima; Mathematics; Mathematical analysis","score_opus":0.05714484744274282,"score_gpt":0.26104418046016725,"score_spread":0.20389933301742444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W114064698","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08841576,0.000913986,0.80653614,0.0027784007,0.0007661685,0.00023237285,0.0007296288,0.008494247,0.091133274],"genre_scores_gemma":[0.7937496,0.00034679304,0.17912981,0.0009372498,0.00025697474,0.00021653381,0.0011263409,0.0019021648,0.022334596],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99590874,0.0008749677,0.00020582048,0.00064952107,0.0016817149,0.00067916326],"domain_scores_gemma":[0.98827016,0.0063235043,0.00042107134,0.0033948352,0.0012693298,0.00032117323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023928382,0.0014508304,0.0017863605,0.0013431073,0.0010353151,0.0023913088,0.004100946,0.002821361,0.01706699],"category_scores_gemma":[0.018514758,0.0007397626,0.0015038314,0.0014155599,0.0031077021,0.0052699386,0.004814055,0.0038212202,0.0028477693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011890033,0.0003439831,0.0027797248,0.0006332126,0.00013011947,0.0008576481,0.00031850755,0.06505477,0.0143821305,0.42446375,0.031115947,0.45873123],"study_design_scores_gemma":[0.0000771498,0.00019066119,0.00049492245,0.00015582965,0.000060910388,0.00060727424,0.00008694874,0.22331065,0.020073889,0.7465333,0.008361644,0.000046769448],"about_ca_topic_score_codex":0.0005681826,"about_ca_topic_score_gemma":0.0008291565,"teacher_disagreement_score":0.01706699,"about_ca_system_score_codex":0.0011587064,"about_ca_system_score_gemma":0.0013580143,"threshold_uncertainty_score":0.057094753},"labels":[],"label_agreement":null},{"id":"W116052530","doi":"10.1007/978-3-642-31585-5_45","title":"Deterministic Network Exploration by Anonymous Silent Agents with Local Traffic Reports","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Normalization property; Node (physics); Theoretical computer science; Computer network","score_opus":0.02377643852343522,"score_gpt":0.24624049077504437,"score_spread":0.22246405225160915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W116052530","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28670844,0.0005523754,0.698307,0.001035492,0.00012954962,0.00011833779,0.00019848737,0.00069175713,0.012258631],"genre_scores_gemma":[0.96360487,0.00017011173,0.02949543,0.00007504053,0.000066943416,0.00012329065,0.000072109004,0.0000810428,0.0063110846],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99883264,0.0004989416,0.0000494689,0.00022170297,0.00018480411,0.00021248824],"domain_scores_gemma":[0.9875387,0.00964258,0.0009229127,0.000855857,0.0004221906,0.00061778456],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002073938,0.00089770276,0.0016185712,0.0009037783,0.0009298929,0.0016877032,0.0025917976,0.0018970257,0.0025886416],"category_scores_gemma":[0.012324951,0.0010252661,0.0010598662,0.0010105766,0.001998948,0.0027434481,0.0030725643,0.001478385,0.00033017885],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005441085,0.00007276898,0.00074196473,0.00010535096,0.00007856476,0.00018648358,0.000145437,0.9231397,0.001623351,0.06167901,0.0011942048,0.010489071],"study_design_scores_gemma":[0.000026783258,0.000029901632,0.00006248353,0.0000066133894,0.000013890043,0.000027098711,0.000017973045,0.9795837,0.0002900747,0.019748526,0.00018350872,0.000009526932],"about_ca_topic_score_codex":0.001559138,"about_ca_topic_score_gemma":0.0016363941,"teacher_disagreement_score":0.0025917976,"about_ca_system_score_codex":0.0009345965,"about_ca_system_score_gemma":0.0008939059,"threshold_uncertainty_score":0.010968208},"labels":[],"label_agreement":null},{"id":"W1165108992","doi":"10.53846/goediss-5126","title":"Randomized Approximation and Online Algorithms for Assignment Problems","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Deutsche Forschungsgemeinschaft","keywords":"Randomized rounding; Generalized assignment problem; Competitive analysis; Online algorithm; Randomized algorithm; Mathematics; Approximation algorithm; Assignment problem; Disjoint sets; Rounding; Mathematical optimization; Integer programming; Scheduling (production processes); Separable space; Generalization; Linear bottleneck assignment problem; Weapon target assignment problem; Algorithm; Computer science; Upper and lower bounds; Combinatorics","score_opus":0.0565866783259216,"score_gpt":0.3363461507125681,"score_spread":0.27975947238664656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1165108992","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01649101,0.0019253348,0.9612314,0.0026005954,0.00035167084,0.0002884553,0.0004177001,0.0015462735,0.015147556],"genre_scores_gemma":[0.31772798,0.001603881,0.66455513,0.001217066,0.00075070374,0.0011127987,0.0017055412,0.00063854345,0.010688376],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99351764,0.0029848716,0.00027062732,0.0012293971,0.0011116425,0.0008858849],"domain_scores_gemma":[0.98314923,0.013037732,0.0008374103,0.0019880584,0.00059868704,0.00038883483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048345714,0.0026859448,0.0030290745,0.001334263,0.0019139368,0.0038284077,0.004386566,0.0032151362,0.009766447],"category_scores_gemma":[0.022470666,0.0011198998,0.0018324527,0.003472312,0.00219883,0.0065631364,0.0027443003,0.0061275274,0.001769166],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007607982,0.0009153859,0.0010047345,0.000550734,0.00018131272,0.00013901741,0.00019525764,0.60129577,0.0012926928,0.25584355,0.020352596,0.11746813],"study_design_scores_gemma":[0.00019385583,0.000062763276,0.000108788176,0.00003661836,0.000033781867,0.00004665843,0.00004150619,0.85092366,0.0004482442,0.1445928,0.0034971472,0.000014237903],"about_ca_topic_score_codex":0.0055018645,"about_ca_topic_score_gemma":0.007284049,"teacher_disagreement_score":0.009766447,"about_ca_system_score_codex":0.004041934,"about_ca_system_score_gemma":0.0043214387,"threshold_uncertainty_score":0.032672048},"labels":[],"label_agreement":null},{"id":"W117901136","doi":"10.1007/978-3-642-39212-2_49","title":"Learning a Ring Cheaply and Fast","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Ring (chemistry); Node (physics); Task (project management); Upper and lower bounds; Matching (statistics); Constant (computer programming); Computation; Class (philosophy); Time complexity; Construct (python library); Theoretical computer science; Algorithm; Discrete mathematics; Combinatorics; Mathematics; Computer network; Artificial intelligence","score_opus":0.01626947040187827,"score_gpt":0.2388798637032399,"score_spread":0.22261039330136165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W117901136","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041699436,0.0012835317,0.902879,0.0028330607,0.00059375004,0.0001804994,0.0005565346,0.005001699,0.04497245],"genre_scores_gemma":[0.35981378,0.0017936154,0.542238,0.000917677,0.00073979935,0.00038587552,0.0012320409,0.0015141477,0.09136511],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898297,0.00021317301,0.000057923364,0.00029523636,0.00030388252,0.00014684403],"domain_scores_gemma":[0.9958234,0.0022808113,0.00021659533,0.0011985357,0.00027649885,0.00020414131],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013266766,0.0011171934,0.001391631,0.0006451197,0.0009249908,0.0021266583,0.0017826918,0.0014690169,0.023145577],"category_scores_gemma":[0.008807762,0.00070831977,0.0009748297,0.0007215999,0.0013728988,0.0076724063,0.0031887796,0.0032821952,0.0069855503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005940907,0.00022040849,0.00096511364,0.00060464453,0.00010477628,0.00010807461,0.00017283915,0.0733639,0.00782263,0.32181814,0.059819993,0.53440547],"study_design_scores_gemma":[0.00014060155,0.00022827499,0.0003470658,0.00010323502,0.000082493636,0.00029105114,0.00013341372,0.2575371,0.0068061436,0.70200527,0.032279618,0.00004576284],"about_ca_topic_score_codex":0.0005065777,"about_ca_topic_score_gemma":0.0010622143,"teacher_disagreement_score":0.023145577,"about_ca_system_score_codex":0.00071678514,"about_ca_system_score_gemma":0.0012088277,"threshold_uncertainty_score":0.07742971},"labels":[],"label_agreement":null},{"id":"W11899514","doi":"10.1007/978-1-4614-7079-3_2","title":"Decentralized Optimal Resource Allocation","year":2013,"lang":"en","type":"book-chapter","venue":"SpringerBriefs in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Quality of service; Resource allocation; Computer science; Computer network; Resource management (computing); Exploit; Wireless network; Radio resource management; Resource (disambiguation); Distributed computing; Wireless; Telecommunications; Computer security","score_opus":0.02138936483571038,"score_gpt":0.24800857359841974,"score_spread":0.22661920876270936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W11899514","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006953915,0.0023732805,0.800028,0.0012769123,0.0005451787,0.000077623044,0.00016993184,0.00055387727,0.18802132],"genre_scores_gemma":[0.5929411,0.006936537,0.20361815,0.0006798987,0.0011206887,0.00048246764,0.0006120054,0.0003540982,0.19325507],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99966085,0.00009645141,0.000011238731,0.00006562973,0.00012605358,0.000039842784],"domain_scores_gemma":[0.9998109,0.00007748576,0.000015234863,0.000054406995,0.000027294855,0.000014660715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043017635,0.0005883418,0.000664195,0.00034112963,0.0003570038,0.0010239191,0.00079596,0.00055767247,0.012097147],"category_scores_gemma":[0.0010632222,0.00030446317,0.0002702237,0.0007151221,0.0006803378,0.0010003166,0.0011077857,0.00091919233,0.0019320117],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000096314296,0.00007689728,0.000107676446,0.00017656536,0.000040771658,0.000058611382,0.00004713138,0.1513844,0.003762669,0.59949505,0.034359943,0.21039397],"study_design_scores_gemma":[0.000035517507,0.000035400906,0.0001918111,0.000047882357,0.000017580984,0.00009883972,0.000024551959,0.3820445,0.0015721618,0.56420076,0.05171454,0.000016403836],"about_ca_topic_score_codex":0.0005176809,"about_ca_topic_score_gemma":0.00081009127,"teacher_disagreement_score":0.012097147,"about_ca_system_score_codex":0.00073406834,"about_ca_system_score_gemma":0.0007411802,"threshold_uncertainty_score":0.04046899},"labels":[],"label_agreement":null},{"id":"W119445844","doi":"10.1007/978-3-642-40273-9_17","title":"A Survey of Algorithms and Models for List Update","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Locality; Locality of reference; Context (archaeology); Algorithm; Theoretical computer science; Linked list; Cache; Parallel computing","score_opus":0.04485214655756037,"score_gpt":0.27540241918750563,"score_spread":0.23055027262994526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W119445844","genre_codex":"methods","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0037867944,0.03578379,0.9380894,0.0023713182,0.0006841883,0.00021579374,0.0015808794,0.0029757675,0.014512044],"genre_scores_gemma":[0.10553217,0.055287536,0.8020252,0.0020286029,0.0033125367,0.0010580412,0.004112882,0.0017544304,0.024888562],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99620616,0.0009733187,0.0003858936,0.0008196642,0.0012923339,0.0003226338],"domain_scores_gemma":[0.99135625,0.005241713,0.00045729938,0.001896445,0.00087810226,0.00017009806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030736672,0.0018848779,0.0033823121,0.0027964104,0.0018330895,0.007003033,0.007249344,0.0028051229,0.015603784],"category_scores_gemma":[0.018493403,0.001433156,0.0024016064,0.009690911,0.0019693747,0.01219759,0.0029876886,0.004117112,0.008010315],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029803382,0.00029215394,0.0011538268,0.0016000236,0.00012561707,0.00007391009,0.00023106254,0.08702898,0.0006741843,0.35893092,0.058910765,0.49068055],"study_design_scores_gemma":[0.00008459132,0.000086847285,0.00030444702,0.0003466452,0.00011954081,0.00025994558,0.00007488968,0.38590938,0.0009733449,0.55655414,0.05522116,0.00006508687],"about_ca_topic_score_codex":0.0076427455,"about_ca_topic_score_gemma":0.008140591,"teacher_disagreement_score":0.015603784,"about_ca_system_score_codex":0.0032330516,"about_ca_system_score_gemma":0.0043511284,"threshold_uncertainty_score":0.05219984},"labels":[],"label_agreement":null},{"id":"W12290988","doi":"","title":"The Mutual Visibility Problem for Oblivious Robots","year":2014,"lang":"en","type":"article","venue":"CINECA IRIS Institutial research information system (University of Pisa)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Correctness; Robot; Visibility; Computability; Computer science; Set (abstract data type); Euclidean geometry; Plane (geometry); Algorithm; Theoretical computer science; Artificial intelligence; Mathematics; Geometry","score_opus":0.04677671382139172,"score_gpt":0.2907456539820823,"score_spread":0.24396894016069057,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W12290988","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12090634,0.0002976271,0.8739681,0.00076815754,0.000026077074,0.000060154933,0.000090029804,0.00021638219,0.0036671904],"genre_scores_gemma":[0.8732168,0.0003256694,0.122163795,0.00011171039,0.000051907864,0.00017054542,0.00022318514,0.00011315727,0.0036231105],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983096,0.0005984552,0.00008953722,0.0003986731,0.00029567452,0.00030812094],"domain_scores_gemma":[0.99400216,0.0043119784,0.0006208156,0.0006680306,0.00017889868,0.00021811153],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016026313,0.00061697245,0.0009710305,0.000439155,0.0010637494,0.0012436671,0.0016173227,0.0013982868,0.0016037303],"category_scores_gemma":[0.010084368,0.0005378795,0.0010392977,0.00062380615,0.0023282452,0.0049454533,0.0037143715,0.0016662619,0.00018908948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003373827,0.00008496481,0.0014144809,0.00023760226,0.00010756734,0.00037458376,0.0010514362,0.57820207,0.0037113586,0.3824168,0.0019196145,0.030141998],"study_design_scores_gemma":[0.000075935095,0.000070478345,0.00035042953,0.000019481076,0.000027344378,0.00014185326,0.00017339631,0.60887814,0.002781994,0.3847692,0.0026914617,0.00002021938],"about_ca_topic_score_codex":0.0020293815,"about_ca_topic_score_gemma":0.0011654694,"teacher_disagreement_score":0.0020293815,"about_ca_system_score_codex":0.0011763524,"about_ca_system_score_gemma":0.0013065465,"threshold_uncertainty_score":0.008535087},"labels":[],"label_agreement":null},{"id":"W126257098","doi":"10.1109/simsym.2000.844919","title":"Flow control and dynamic load balancing in Time Warp","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Load balancing (electrical power); Flow (mathematics); Scheme (mathematics); Algorithm; Parallel computing; Distributed computing; Control flow; Reduction (mathematics); Flow control (data); Real-time computing; Computer network","score_opus":0.006499084321241622,"score_gpt":0.2067399449095578,"score_spread":0.20024086058831617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W126257098","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029393435,0.00008527708,0.9679542,0.00008846095,0.000028180837,0.000056304805,0.000025631061,0.0008231608,0.0015453589],"genre_scores_gemma":[0.6294517,0.00012815266,0.3672156,0.0000786446,0.00004620413,0.00020438273,0.00011282448,0.00017841834,0.0025840527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994186,0.00015500035,0.000030587842,0.00013211813,0.00014996652,0.00011370552],"domain_scores_gemma":[0.9990196,0.0005222575,0.000105823834,0.00015783939,0.00012338713,0.000071011535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097368425,0.0007222273,0.00073762785,0.0006040239,0.00070304854,0.0010111193,0.0011093963,0.00072913605,0.0031033666],"category_scores_gemma":[0.0028360174,0.00040326198,0.0003748231,0.0007268989,0.001164372,0.0017534188,0.0012066264,0.0009060666,0.0004341551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026056194,0.0000981333,0.0007121333,0.000040084844,0.000029184126,0.00007467033,0.000101840466,0.84199727,0.0060822917,0.022033622,0.000843593,0.12772663],"study_design_scores_gemma":[0.00002835953,0.000030154812,0.000058092613,0.0000031726913,0.000005381311,0.00001564244,0.000006980916,0.98821145,0.0024699487,0.008358956,0.0008063934,0.0000054818197],"about_ca_topic_score_codex":0.0040545,"about_ca_topic_score_gemma":0.0019849648,"teacher_disagreement_score":0.0040545,"about_ca_system_score_codex":0.00072488276,"about_ca_system_score_gemma":0.0008966928,"threshold_uncertainty_score":0.010381818},"labels":[],"label_agreement":null},{"id":"W129093026","doi":"10.1007/978-3-319-07890-8_10","title":"Synchronized Dancing of Oblivious Chameleons","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Dance; Choreography; Computer science; Asynchronous communication; Sequence (biology); Visual arts; Art; Biology","score_opus":0.014815554599129825,"score_gpt":0.24394471304628135,"score_spread":0.2291291584471515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W129093026","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2366334,0.0013570639,0.54821694,0.0010449161,0.00076326367,0.0002919735,0.00062255375,0.003961733,0.20710813],"genre_scores_gemma":[0.85630536,0.00048613932,0.05373803,0.00023064457,0.00011259494,0.00027701008,0.00045952466,0.0009494869,0.087441176],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909925,0.00019160696,0.000042212712,0.0001795395,0.000245755,0.00024170878],"domain_scores_gemma":[0.99777585,0.00080767204,0.00009821623,0.0010048838,0.00016678903,0.00014656299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060283364,0.00073807605,0.001404764,0.0011002341,0.0024757148,0.002071709,0.0020669047,0.0014155464,0.041993245],"category_scores_gemma":[0.004507475,0.0005946205,0.00064954866,0.0015334323,0.001848104,0.004410622,0.00446704,0.0018425321,0.004646384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00076890475,0.000089264075,0.0003488523,0.00018284087,0.000053917414,0.0001740311,0.00056555186,0.04804663,0.0071650296,0.84590065,0.010621339,0.086082995],"study_design_scores_gemma":[0.00010066933,0.00013238224,0.00021279305,0.000080382306,0.00002972016,0.00012941135,0.0002470795,0.19502693,0.0062571215,0.7783495,0.019389242,0.000044724045],"about_ca_topic_score_codex":0.0010860624,"about_ca_topic_score_gemma":0.0019823867,"teacher_disagreement_score":0.041993245,"about_ca_system_score_codex":0.00093491276,"about_ca_system_score_gemma":0.0008794625,"threshold_uncertainty_score":0.14048135},"labels":[],"label_agreement":null},{"id":"W129976106","doi":"","title":"Assigning Closely Spaced Targets to Multiple Autonomous Underwater Vehicles","year":2009,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Turning radius; Kinematics; Underwater; Constant (computer programming); Task (project management); Computer science; Mathematical optimization; Algorithm; Path (computing); Constant curvature; Curvature; Control theory (sociology); Mathematics; Engineering; Artificial intelligence; Aerospace engineering; Geometry","score_opus":0.014439750945576429,"score_gpt":0.21753179389921512,"score_spread":0.2030920429536387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W129976106","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29684305,0.00021632767,0.698486,0.000129547,0.000053622327,0.00015272899,0.000045896762,0.00028227878,0.0037906382],"genre_scores_gemma":[0.9031402,0.00008838171,0.093031995,0.00004133102,0.000018533094,0.00010694687,0.00005316866,0.00004129261,0.0034781564],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993754,0.000165623,0.000028118702,0.00017912796,0.000113191134,0.00013863455],"domain_scores_gemma":[0.9992797,0.00025802557,0.00012752695,0.000107027045,0.00010688139,0.000120877085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006709795,0.0007006864,0.0012264175,0.0005101957,0.0007819616,0.0007654494,0.0016916816,0.00083926274,0.0033624761],"category_scores_gemma":[0.0019855176,0.00040540737,0.00051732647,0.0006260509,0.0005151746,0.0014738496,0.0017194197,0.0006219151,0.00040611174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016603882,0.000083853905,0.0013223668,0.000048565365,0.000029752176,0.00013319727,0.00010956435,0.92273104,0.0043653673,0.004117841,0.0004424051,0.06644995],"study_design_scores_gemma":[0.000013817575,0.00013288503,0.0003058999,0.000004750326,0.000009193663,0.00004482341,0.0001190623,0.99282587,0.0017571574,0.0038783236,0.0008987984,0.0000095046435],"about_ca_topic_score_codex":0.004325444,"about_ca_topic_score_gemma":0.0038162014,"teacher_disagreement_score":0.004325444,"about_ca_system_score_codex":0.00084301014,"about_ca_system_score_gemma":0.00086318544,"threshold_uncertainty_score":0.011248589},"labels":[],"label_agreement":null},{"id":"W1472690358","doi":"10.1016/j.jnca.2016.07.010","title":"Large profits or fast gains: A dilemma in maximizing throughput with applications to network processors","year":2016,"lang":"en","type":"article","venue":"Journal of Network and Computer Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Israel Science Foundation","keywords":"Computer science; Network packet; Throughput; Queue; Network processor; Bounded function; Distributed computing; Computer network; Telecommunications; Wireless","score_opus":0.0280685812183043,"score_gpt":0.2860164329686443,"score_spread":0.25794785175034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1472690358","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24303895,0.011146403,0.5288437,0.099616125,0.0009938275,0.00019828825,0.00027107744,0.00030050625,0.115591034],"genre_scores_gemma":[0.9536329,0.0028529656,0.034350216,0.0014749144,0.0011701464,0.00011914284,0.000019179906,0.00014197329,0.006238484],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99616253,0.0023539942,0.0001216938,0.00041593544,0.000563289,0.0003825205],"domain_scores_gemma":[0.96726424,0.028849047,0.0011040663,0.0008643143,0.00089565926,0.0010226585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008823473,0.000777572,0.0014883336,0.001004917,0.0018509941,0.0075476733,0.0021716808,0.005357375,0.00477117],"category_scores_gemma":[0.04143935,0.00078538555,0.0004994698,0.0016329398,0.006439039,0.0129986135,0.00278532,0.0045059365,0.00054498075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029933348,0.000087200286,0.0007597461,0.00015064543,0.000047709324,0.00023939625,0.0004111675,0.06715956,0.000823279,0.8698435,0.008269195,0.051909186],"study_design_scores_gemma":[0.000041787014,0.000040511364,0.00026350556,0.00003064863,0.000016369178,0.0001183766,0.00027272472,0.06983553,0.00034118156,0.9264245,0.002589525,0.00002531416],"about_ca_topic_score_codex":0.0011784581,"about_ca_topic_score_gemma":0.0015418475,"teacher_disagreement_score":0.008823473,"about_ca_system_score_codex":0.0020839246,"about_ca_system_score_gemma":0.0020560974,"threshold_uncertainty_score":0.046663523},"labels":[],"label_agreement":null},{"id":"W1480384904","doi":"10.1007/978-3-642-02568-6_53","title":"A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Hierarchy; Automaton; Resource allocation; Theoretical computer science; Sampling (signal processing); Resource (disambiguation); Operations research; Mathematics; Telecommunications","score_opus":0.02930678080531624,"score_gpt":0.2897804976196341,"score_spread":0.26047371681431786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1480384904","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056498803,0.0005220259,0.9222434,0.00047217414,0.00015517363,0.00016029923,0.00047002366,0.003486777,0.015991384],"genre_scores_gemma":[0.44431144,0.00030445616,0.54553515,0.00034416243,0.000102165184,0.0005052551,0.0007047149,0.0004403372,0.0077523007],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99781525,0.00057289563,0.00030132008,0.00048177384,0.0004862663,0.0003425542],"domain_scores_gemma":[0.9915245,0.0039338632,0.0003439321,0.0025962905,0.0009943296,0.00060709444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016129299,0.0007604514,0.0019094605,0.0011630434,0.001758591,0.0041559557,0.003027534,0.0020016027,0.012626399],"category_scores_gemma":[0.009875965,0.0011101041,0.0012354396,0.0015214665,0.0017609409,0.0038536498,0.0036869997,0.0031024034,0.0020431012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053686294,0.0002450682,0.0011987095,0.00031497897,0.00006464736,0.000235969,0.000443864,0.07053644,0.016082352,0.78421944,0.0059337397,0.12018803],"study_design_scores_gemma":[0.00007089253,0.00007367264,0.00018658253,0.000043654676,0.00004746359,0.00013631949,0.00006859034,0.5697501,0.0047290092,0.421023,0.0038226114,0.000048079804],"about_ca_topic_score_codex":0.0019275685,"about_ca_topic_score_gemma":0.0035897715,"teacher_disagreement_score":0.012626399,"about_ca_system_score_codex":0.001761941,"about_ca_system_score_gemma":0.0020299377,"threshold_uncertainty_score":0.042239547},"labels":[],"label_agreement":null},{"id":"W1481888229","doi":"10.1007/978-3-540-74466-5_64","title":"Locating a Black Hole in an Un-oriented Ring Using Tokens: The Case of Scattered Agents","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Ring (chemistry); Black hole (networking); Computer science; Security token; Ring network; Constant (computer programming); Token ring; Physics; Computer network; Network topology","score_opus":0.06385829267549921,"score_gpt":0.3188294906459288,"score_spread":0.2549711979704296,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1481888229","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50565934,0.0006534681,0.47160453,0.0012138074,0.00018011619,0.00015076283,0.00007487084,0.00039754974,0.020065539],"genre_scores_gemma":[0.8640104,0.00030919505,0.12528099,0.000058552025,0.000033222903,0.00006517625,0.000032364314,0.0001074001,0.010102676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988954,0.00033640518,0.00006353919,0.00023197915,0.00016669041,0.00030587625],"domain_scores_gemma":[0.9936719,0.0037010456,0.0006878308,0.00066526857,0.00029963677,0.00097418146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027498729,0.00069747586,0.0017179684,0.00088355294,0.003017159,0.0034610494,0.0032780154,0.0047132554,0.004768022],"category_scores_gemma":[0.009456305,0.0012439585,0.0010147227,0.0011714173,0.004492923,0.008014856,0.005780918,0.0015569986,0.0008702795],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019620187,0.00033608847,0.002429541,0.0003762785,0.00010794448,0.00907815,0.0022903327,0.38181108,0.013091487,0.5601059,0.002485931,0.025925256],"study_design_scores_gemma":[0.00025847967,0.00031758114,0.00032710432,0.000060596107,0.00008239475,0.0011871455,0.0015489579,0.7752136,0.005792036,0.21182525,0.0033074687,0.00007939438],"about_ca_topic_score_codex":0.0014413189,"about_ca_topic_score_gemma":0.0012439301,"teacher_disagreement_score":0.004768022,"about_ca_system_score_codex":0.00076070323,"about_ca_system_score_gemma":0.0009445804,"threshold_uncertainty_score":0.01595062},"labels":[],"label_agreement":null},{"id":"W1484932675","doi":"10.1007/978-3-642-02777-2_26","title":"A Theoretical Analysis of Search in GSAT","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Heuristic; Algorithm; Distribution (mathematics); Mathematical optimization; Theoretical computer science; Mathematics; Artificial intelligence","score_opus":0.018391801256455245,"score_gpt":0.27934312240710363,"score_spread":0.2609513211506484,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1484932675","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03218964,0.005789133,0.7551519,0.007711632,0.00049844483,0.00012304452,0.0005707926,0.0007040947,0.1972612],"genre_scores_gemma":[0.7560895,0.00674323,0.15681046,0.0026371921,0.0013996467,0.00046021375,0.00079650816,0.0009218343,0.07414138],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99852824,0.0005360778,0.00005310258,0.00019403915,0.00041828008,0.0002702121],"domain_scores_gemma":[0.9942913,0.004351137,0.0002699574,0.0005059902,0.00035939354,0.00022218082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018458333,0.0010960877,0.0017255577,0.0023917968,0.0022744169,0.0040506427,0.0036331306,0.0031043638,0.022855183],"category_scores_gemma":[0.01178997,0.0008989427,0.0025455954,0.004826196,0.006733209,0.008615719,0.0032108189,0.0057360907,0.002271545],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001023333,0.000007973603,0.00006616041,0.00004089832,0.000005921693,0.000012259086,0.00004716166,0.009685264,0.00006477528,0.98458856,0.0019424728,0.0035282995],"study_design_scores_gemma":[0.0000073940287,0.000008131438,0.00005469547,0.000022025262,0.000008345485,0.000024674582,0.000025172429,0.050601736,0.00006983205,0.9466353,0.0025363185,0.000006258991],"about_ca_topic_score_codex":0.0052320445,"about_ca_topic_score_gemma":0.0038237388,"teacher_disagreement_score":0.022855183,"about_ca_system_score_codex":0.004307397,"about_ca_system_score_gemma":0.0021368251,"threshold_uncertainty_score":0.076458216},"labels":[],"label_agreement":null},{"id":"W1485084509","doi":"10.1109/ictel.2003.1191680","title":"Minimum cost design of a parallel computing cluster","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Research Manitoba","funders":"","keywords":"Maxima and minima; Computer science; Mathematical optimization; Approximation algorithm; Function (biology); Linear approximation; Network planning and design; Representation (politics); Approximation error; Function approximation; Linear programming; Process (computing); Algorithm; Artificial neural network; Mathematics; Artificial intelligence; Nonlinear system","score_opus":0.05122015434431328,"score_gpt":0.28319298227882944,"score_spread":0.23197282793451615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1485084509","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08266487,0.00029013192,0.9016578,0.00056564994,0.00007293501,0.00030854752,0.0001350535,0.00063844817,0.013666581],"genre_scores_gemma":[0.7458968,0.00024891598,0.2490188,0.000070151415,0.00003113615,0.000427857,0.00013619829,0.00012878158,0.0040413495],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992053,0.00024192402,0.00002804734,0.00015669383,0.00024651634,0.000121535835],"domain_scores_gemma":[0.9990977,0.00024441397,0.00013314231,0.00008611075,0.0002983978,0.00014030321],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008433569,0.00062237727,0.0008949012,0.0006951165,0.0009818143,0.0010578684,0.0019221122,0.00062931486,0.0035427627],"category_scores_gemma":[0.0027952322,0.0006384897,0.00034942428,0.0005972323,0.0007990854,0.0013684416,0.001257368,0.0006866801,0.000566557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001459117,0.000037468115,0.00037613453,0.00009181584,0.000015035311,0.00006274136,0.000036639594,0.96046907,0.004535595,0.015728595,0.0011507756,0.017350214],"study_design_scores_gemma":[0.000024177489,0.00006555147,0.00013548994,0.000008290131,0.00000904251,0.000025626345,0.000028856362,0.98937035,0.0018160852,0.006986781,0.0015216388,0.000008133026],"about_ca_topic_score_codex":0.0036325369,"about_ca_topic_score_gemma":0.0034385617,"teacher_disagreement_score":0.0036325369,"about_ca_system_score_codex":0.0018901764,"about_ca_system_score_gemma":0.0020765194,"threshold_uncertainty_score":0.0137143135},"labels":[],"label_agreement":null},{"id":"W1489544554","doi":"10.1007/11527954_19","title":"Algorithmic Foundations of the Internet: Roundup","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; The Internet; Field (mathematics); World Wide Web; Mathematics","score_opus":0.02369745416734363,"score_gpt":0.266378627808066,"score_spread":0.24268117364072236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1489544554","genre_codex":"other","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007967847,0.121959485,0.2945273,0.0878652,0.021976855,0.00012696104,0.0011055289,0.0009774012,0.46349347],"genre_scores_gemma":[0.28068408,0.17005229,0.1556963,0.017207764,0.042024355,0.000646214,0.0017095482,0.0011325878,0.33084694],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993474,0.00019487254,0.000031567542,0.00013859273,0.0002065851,0.00008101948],"domain_scores_gemma":[0.99804425,0.0010458515,0.00006499848,0.00037938857,0.00030476894,0.00016069984],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011433074,0.00097420625,0.0006236985,0.0016533888,0.0015701969,0.0063454006,0.0019401754,0.0031344395,0.032043554],"category_scores_gemma":[0.0046129427,0.00094398926,0.0009975372,0.002353991,0.0034624413,0.016420752,0.0030997852,0.0060853674,0.009222873],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021178452,0.000027785294,0.00011759587,0.00012900447,0.0000127724425,0.0000522061,0.00006915452,0.0013740322,0.00012542824,0.8616744,0.08831437,0.048082188],"study_design_scores_gemma":[0.000005719927,0.000006554934,0.000093541115,0.0001222621,0.0000065702548,0.00009242691,0.00005053234,0.001535636,0.00014104608,0.85986716,0.13806497,0.000013532089],"about_ca_topic_score_codex":0.0015787693,"about_ca_topic_score_gemma":0.0021423143,"teacher_disagreement_score":0.032043554,"about_ca_system_score_codex":0.0024993678,"about_ca_system_score_gemma":0.0011609348,"threshold_uncertainty_score":0.10719633},"labels":[],"label_agreement":null},{"id":"W1490637409","doi":"10.1007/978-3-540-24581-0_3","title":"On How to Learn from a Stochastic Teacher or a Stochastic Compulsive Liar of Unknown Identity","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Learning automata; Interval (graph theory); Point (geometry); Identity (music); Automaton; Artificial intelligence; Mechanism (biology); Space (punctuation); Stochastic process; Algorithm; Mathematics; Statistics","score_opus":0.024634053035175987,"score_gpt":0.2719790049346291,"score_spread":0.24734495189945313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1490637409","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06397267,0.0008859746,0.8638733,0.010929491,0.00025096437,0.00008623881,0.00022612863,0.0003869503,0.05938824],"genre_scores_gemma":[0.7587314,0.0014696576,0.14747128,0.0010679722,0.00021372475,0.00024286604,0.0003676945,0.0001243397,0.09031108],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998147,0.00008759787,0.0000121242565,0.0000383436,0.000028340964,0.000018921817],"domain_scores_gemma":[0.9973152,0.0022813978,0.0000764619,0.00012622545,0.0001227486,0.00007797586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082082296,0.00029672473,0.00038931204,0.00015482624,0.00037574992,0.00083560095,0.00061917916,0.0010353175,0.007869973],"category_scores_gemma":[0.0070795817,0.00015273863,0.00033274668,0.00022695721,0.0015067899,0.002795966,0.0012240851,0.0013877493,0.0007090444],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012233865,0.000060357397,0.0012535091,0.00016085009,0.000031467745,0.000063448126,0.00041097292,0.079107374,0.00050009345,0.7709405,0.0147002805,0.1326488],"study_design_scores_gemma":[0.000027798324,0.000038859063,0.00022152622,0.000033464603,0.000010904267,0.000032102715,0.00015122286,0.17889702,0.00050029473,0.81454873,0.0055280016,0.000010009897],"about_ca_topic_score_codex":0.0026470756,"about_ca_topic_score_gemma":0.0024382307,"teacher_disagreement_score":0.007869973,"about_ca_system_score_codex":0.0006031213,"about_ca_system_score_gemma":0.0007389111,"threshold_uncertainty_score":0.02632761},"labels":[],"label_agreement":null},{"id":"W1492783741","doi":"10.1023/a:1011688823715","title":"Robot Map Verification of a Graph World","year":2001,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Vertex (graph theory); Robot; Traverse; Robotics; Artificial intelligence; Theory of computation; Combinatorics; Computer science; Orientation (vector space); Graph; Automation; Topology (electrical circuits); Mathematics; Algorithm; Geometry; Geography; Engineering; Cartography","score_opus":0.01678363309690364,"score_gpt":0.2575980775032374,"score_spread":0.24081444440633373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1492783741","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36744234,0.00017061004,0.61410904,0.0016640363,0.00015272209,0.00034554087,0.0011749892,0.002800641,0.012140095],"genre_scores_gemma":[0.92682797,0.00007520261,0.068875834,0.00010953044,0.000025966308,0.000050345647,0.0006825799,0.0002425892,0.0031099517],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983718,0.00043451425,0.0000800374,0.00035959567,0.00044319755,0.00031096349],"domain_scores_gemma":[0.9885437,0.007957978,0.0008412213,0.0012273941,0.0010520492,0.00037766848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012976322,0.0007157933,0.0013065739,0.001197429,0.0014215492,0.0026762127,0.002264155,0.002174541,0.007855428],"category_scores_gemma":[0.01547231,0.0006806458,0.0015900809,0.0008677102,0.0022508842,0.005525802,0.0036934703,0.0016277954,0.00083847943],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019002286,0.00041087624,0.007741033,0.00062555977,0.00027875506,0.0024857721,0.0008124325,0.6981817,0.015364215,0.17092797,0.008676792,0.09259469],"study_design_scores_gemma":[0.000079219295,0.00010092435,0.0006750209,0.00003075513,0.00003861908,0.00011561338,0.00017629053,0.8821378,0.006376453,0.109328814,0.0009113222,0.00002924207],"about_ca_topic_score_codex":0.013587389,"about_ca_topic_score_gemma":0.01030153,"teacher_disagreement_score":0.013587389,"about_ca_system_score_codex":0.0010651706,"about_ca_system_score_gemma":0.0024608662,"threshold_uncertainty_score":0.02701658},"labels":[],"label_agreement":null},{"id":"W1493636406","doi":"10.1007/978-3-642-15763-9_28","title":"Almost Optimal Asynchronous Rendezvous in Infinite Multidimensional Grids","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal","funders":"Agence Nationale de la Recherche","keywords":"Rendezvous; Asynchronous communication; Computer science; Traverse; Visibility; Euclidean space; Grid; Position (finance); Upper and lower bounds; Dimension (graph theory); Trajectory; RADIUS; Euclidean distance; Algorithm; Topology (electrical circuits); Discrete mathematics; Theoretical computer science; Combinatorics; Mathematics; Geometry; Artificial intelligence; Spacecraft; Mathematical analysis","score_opus":0.015741446759445415,"score_gpt":0.25260131241725203,"score_spread":0.23685986565780662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1493636406","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23582867,0.00097436924,0.7235356,0.0005743661,0.00025344576,0.000059577276,0.00021665228,0.00070715335,0.037850175],"genre_scores_gemma":[0.93686986,0.00038625853,0.05210736,0.00007117615,0.00006308528,0.00007614633,0.0001354512,0.00018363618,0.010107005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960655,0.00013069692,0.000020753936,0.00006544435,0.000105291794,0.0000713102],"domain_scores_gemma":[0.9985979,0.0008648768,0.000094588984,0.00025019108,0.00008193757,0.00011052689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045470567,0.0005172217,0.0011426732,0.00044082134,0.00070421235,0.0010932372,0.0010891826,0.00065545546,0.0048092008],"category_scores_gemma":[0.003296241,0.00044993218,0.0003769326,0.00060422084,0.0011705607,0.0018798528,0.0022588766,0.0010657025,0.00047744042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000519903,0.00005366731,0.00032825334,0.00014804218,0.00003421082,0.000118131764,0.00016540124,0.54298896,0.008283047,0.41663206,0.003028979,0.02769926],"study_design_scores_gemma":[0.000039633673,0.000024651461,0.00007575817,0.000009555287,0.0000050935732,0.00002976757,0.000047591086,0.8430073,0.0011746392,0.15467969,0.00089593726,0.000010451363],"about_ca_topic_score_codex":0.0012036895,"about_ca_topic_score_gemma":0.0010556208,"teacher_disagreement_score":0.0048092008,"about_ca_system_score_codex":0.00058632344,"about_ca_system_score_gemma":0.00035418454,"threshold_uncertainty_score":0.016088367},"labels":[],"label_agreement":null},{"id":"W1495262204","doi":"10.1007/978-3-642-34862-4_18","title":"FIFO Queueing Policies for Packets with Heterogeneous Processing","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"FIFO (computing and electronics); Network packet; Computer science; Queueing theory; Queue; FIFO and LIFO accounting; Bounded function; Throughput; Computer network; Distributed computing; Real-time computing; Telecommunications; Mathematics; Operating system; Wireless","score_opus":0.027340042047799384,"score_gpt":0.27158548266187577,"score_spread":0.24424544061407638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1495262204","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02448745,0.0024240273,0.9624729,0.0006809961,0.00053208607,0.00013771777,0.00010450791,0.00060933526,0.008550998],"genre_scores_gemma":[0.78840995,0.0032109926,0.18539388,0.000585487,0.000780528,0.00030486146,0.00022020107,0.00037023472,0.020723736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99827635,0.0003848615,0.00011900505,0.00020394899,0.0006047352,0.00041102915],"domain_scores_gemma":[0.9961578,0.0023552577,0.0002539967,0.00047909777,0.0005009662,0.0002527629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040720883,0.0013115946,0.0012520046,0.00086965243,0.001259642,0.002824354,0.0034347335,0.0011838919,0.0037203722],"category_scores_gemma":[0.009740133,0.0006899294,0.00058175303,0.0011783207,0.0010919684,0.0027801804,0.0016532667,0.0019573616,0.00061853003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094707595,0.00035370735,0.0010289437,0.00037809645,0.00008627046,0.00023385296,0.0003719266,0.45473793,0.006566182,0.3597686,0.01247187,0.16305548],"study_design_scores_gemma":[0.00006063837,0.000073465904,0.0001722544,0.000039040602,0.0000395741,0.0000765059,0.00004054597,0.9077318,0.0015309677,0.08676702,0.003440019,0.00002820199],"about_ca_topic_score_codex":0.0032189114,"about_ca_topic_score_gemma":0.0025681842,"teacher_disagreement_score":0.0040720883,"about_ca_system_score_codex":0.0032160394,"about_ca_system_score_gemma":0.0028179395,"threshold_uncertainty_score":0.023334146},"labels":[],"label_agreement":null},{"id":"W1498202041","doi":"10.1007/978-3-642-24100-0_42","title":"Synchronous Rendezvous for Location-Aware Agents","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Asynchronous communication; Computer science; Simple (philosophy); Euclidean distance; Euclidean space; Euclidean geometry; Point (geometry); Combinatorics; Discrete mathematics; Mathematics; Topology (electrical circuits); Artificial intelligence; Computer network; Geometry; Physics; Spacecraft","score_opus":0.03711144743406031,"score_gpt":0.2726075377252521,"score_spread":0.23549609029119178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1498202041","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053854067,0.0005259796,0.9200452,0.00020958057,0.00020836966,0.000077735924,0.00014142413,0.0028926684,0.022044932],"genre_scores_gemma":[0.86328745,0.00036720565,0.11680369,0.00005893478,0.00007532713,0.00011959626,0.00024321298,0.0002728968,0.01877165],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996276,0.00005944291,0.000019760682,0.000107852684,0.00009979509,0.00008553023],"domain_scores_gemma":[0.9993622,0.00021713982,0.00004916375,0.00021827761,0.000079093435,0.00007413748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038810124,0.0007089495,0.00080076547,0.00036604807,0.0010135976,0.0011244045,0.001718653,0.0006971792,0.006371194],"category_scores_gemma":[0.0016682373,0.0004206536,0.00039804325,0.00047025876,0.00066359015,0.0018061092,0.0023236454,0.0009800405,0.0014231502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001301243,0.00023515044,0.0010950576,0.0004884965,0.000108475346,0.00080991886,0.0011254738,0.3256903,0.05146672,0.30792427,0.016486116,0.29326874],"study_design_scores_gemma":[0.00011156863,0.00013290257,0.00028674255,0.000020208587,0.00004439409,0.00024043545,0.00023345734,0.8841645,0.01272108,0.08591425,0.01609875,0.000031762323],"about_ca_topic_score_codex":0.0028910006,"about_ca_topic_score_gemma":0.004416472,"teacher_disagreement_score":0.006371194,"about_ca_system_score_codex":0.00054100255,"about_ca_system_score_gemma":0.0006120889,"threshold_uncertainty_score":0.021313787},"labels":[],"label_agreement":null},{"id":"W1499381808","doi":"10.1007/978-3-540-69311-6_20","title":"Searching Trees with Sources and Targets","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Monotonic function; Clearance; Set (abstract data type); Search problem; Computer science; Tree (set theory); Time complexity; Search algorithm; Search tree; Combinatorics; Mathematics; Theoretical computer science; Algorithm","score_opus":0.017028414232843833,"score_gpt":0.2362092110254312,"score_spread":0.21918079679258734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1499381808","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022350727,0.0019823313,0.9381065,0.00072972436,0.00015735455,0.000063190666,0.00081332447,0.0018561385,0.03394071],"genre_scores_gemma":[0.15054993,0.00210093,0.8180696,0.00024495725,0.00010917672,0.00013498364,0.0020307621,0.0011304187,0.02562921],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99960726,0.000079395744,0.00002647796,0.00009545806,0.00014685525,0.000044631284],"domain_scores_gemma":[0.9986268,0.00095847226,0.000056247205,0.00018255354,0.00012337769,0.000052591717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005521044,0.0005972625,0.00092731783,0.0010285048,0.0006939026,0.0016792056,0.0013652075,0.0016049884,0.01002832],"category_scores_gemma":[0.004755793,0.0007736466,0.0008047409,0.00216739,0.0006724602,0.0038931447,0.0019625812,0.0018888931,0.0048563113],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028982072,0.00012780887,0.0009623413,0.0009271244,0.00007823671,0.00027488708,0.0005726167,0.07685913,0.009172923,0.31125695,0.043285914,0.5561922],"study_design_scores_gemma":[0.00006400644,0.00009837836,0.00028600465,0.00018415466,0.00008098583,0.00062129175,0.00020742576,0.2731194,0.008311583,0.6726261,0.044364195,0.000036492453],"about_ca_topic_score_codex":0.0005351227,"about_ca_topic_score_gemma":0.0012908396,"teacher_disagreement_score":0.01002832,"about_ca_system_score_codex":0.00043253312,"about_ca_system_score_gemma":0.00055491587,"threshold_uncertainty_score":0.033548117},"labels":[],"label_agreement":null},{"id":"W1501234213","doi":"10.1007/11821069_2","title":"Tree Exploration with an Oracle","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Oracle; Traverse; Tree (set theory); Tree traversal; Competitive analysis; Computer science; Enhanced Data Rates for GSM Evolution; Algorithm; Mathematics; Mathematical optimization; Theoretical computer science; Combinatorics; Artificial intelligence; Upper and lower bounds; Geography","score_opus":0.02826344014817172,"score_gpt":0.25439264767817255,"score_spread":0.22612920753000082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1501234213","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019352902,0.0018480744,0.9175825,0.0008839055,0.00027617227,0.00017055061,0.00077571376,0.0060470696,0.053063042],"genre_scores_gemma":[0.23452304,0.0011756277,0.72511375,0.00036869585,0.00015756734,0.00022771528,0.0016751186,0.0015267968,0.03523171],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994916,0.0001392373,0.000031779688,0.00010646828,0.0001656236,0.00006531816],"domain_scores_gemma":[0.9988211,0.0006237495,0.00003129673,0.00036715408,0.000092983566,0.00006368478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006530234,0.00061069534,0.0009013192,0.0007058904,0.000438562,0.0012279856,0.0012290792,0.0010772096,0.014601996],"category_scores_gemma":[0.003950267,0.00036809524,0.0008339043,0.0012219376,0.00060448813,0.0030742718,0.002172611,0.0019267886,0.0039254646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058782817,0.00017574112,0.00066476647,0.0005173586,0.000058357913,0.00019930738,0.00020339817,0.054441165,0.009893319,0.15243712,0.03938929,0.7414324],"study_design_scores_gemma":[0.00012239163,0.00023092901,0.00044895167,0.00019386815,0.00008224269,0.00065175706,0.000086929234,0.5227126,0.011508175,0.40761873,0.056304086,0.000039274553],"about_ca_topic_score_codex":0.00047623593,"about_ca_topic_score_gemma":0.0010588922,"teacher_disagreement_score":0.014601996,"about_ca_system_score_codex":0.0003505268,"about_ca_system_score_gemma":0.00068047846,"threshold_uncertainty_score":0.04884857},"labels":[],"label_agreement":null},{"id":"W1508354613","doi":"10.1007/11764298_10","title":"Lists on Lists: A Framework for Self-organizing Lists in Environments with Locality of Reference","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Locality; Computer science; Locality of reference; Information retrieval; Operating system","score_opus":0.02173025080978708,"score_gpt":0.25813699526109396,"score_spread":0.23640674445130688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1508354613","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0039918153,0.0005678946,0.984106,0.00046056442,0.00012072405,0.00011164319,0.00029722383,0.00220569,0.00813834],"genre_scores_gemma":[0.13860486,0.0013455742,0.83085334,0.00036020728,0.00036855807,0.0006908155,0.00117104,0.0010367209,0.025568845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983486,0.00049913855,0.00014370403,0.00027935387,0.0005098615,0.00021941107],"domain_scores_gemma":[0.99708587,0.000981017,0.0002411527,0.00087744335,0.00045231788,0.00036222613],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017529716,0.0007329523,0.0011694117,0.0025785791,0.003499244,0.0066715665,0.0044777486,0.0024066668,0.013402833],"category_scores_gemma":[0.0061932104,0.00084847596,0.0013453477,0.0048400573,0.0026259217,0.0119462805,0.0062283985,0.0021630155,0.0051013916],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011033072,0.000056462777,0.0003903142,0.0002400081,0.000028611377,0.0001690808,0.0009205672,0.018682815,0.0019888245,0.8856925,0.013489106,0.07823136],"study_design_scores_gemma":[0.000051325693,0.00008376856,0.0001676425,0.00008551512,0.00006682185,0.0002416056,0.00056015374,0.14937864,0.0032412673,0.7460442,0.100001045,0.000077924065],"about_ca_topic_score_codex":0.0042716507,"about_ca_topic_score_gemma":0.0063876,"teacher_disagreement_score":0.013402833,"about_ca_system_score_codex":0.0013414219,"about_ca_system_score_gemma":0.0020094833,"threshold_uncertainty_score":0.04483688},"labels":[],"label_agreement":null},{"id":"W1516838788","doi":"10.1007/978-3-642-10684-2_72","title":"A Markov Model for Multiagent Patrolling in Continuous Time","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Patrolling; Computer science; Asynchronous communication; Multi-agent system; Markov chain; Artificial intelligence; Markov decision process; Distributed computing; Markov process; Machine learning; Computer network; Mathematics","score_opus":0.020520106502168504,"score_gpt":0.2563511251970211,"score_spread":0.23583101869485257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1516838788","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023860354,0.00077390217,0.96267736,0.0011753656,0.00015432028,0.000078234356,0.0005716217,0.00035544948,0.010353324],"genre_scores_gemma":[0.86429197,0.0019394781,0.08546369,0.00041770888,0.00035863553,0.0006609856,0.0009395771,0.0002569847,0.0456709],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983424,0.0005229223,0.000086454456,0.00042572542,0.00031745652,0.00030519482],"domain_scores_gemma":[0.99459064,0.0037004761,0.0006999169,0.00027440893,0.000377922,0.0003567793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021132948,0.0015960641,0.0028764424,0.0012221017,0.0012117518,0.002918843,0.00489419,0.0040474297,0.013000076],"category_scores_gemma":[0.007280256,0.0016628664,0.00183245,0.0018293103,0.0027745797,0.0040442767,0.0023543807,0.0035573656,0.0019754197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007768981,0.000056447665,0.0005008663,0.000087575296,0.00004581973,0.00013594839,0.00012754617,0.7908836,0.00045820582,0.20068447,0.0015396293,0.0054021566],"study_design_scores_gemma":[0.00001923314,0.000021088308,0.00009546175,0.0000098722385,0.000011899281,0.0000228885,0.000013388728,0.95309407,0.00004425329,0.04615303,0.00049993827,0.000014728879],"about_ca_topic_score_codex":0.019453704,"about_ca_topic_score_gemma":0.01372423,"teacher_disagreement_score":0.019453704,"about_ca_system_score_codex":0.0026650045,"about_ca_system_score_gemma":0.0019261508,"threshold_uncertainty_score":0.043489575},"labels":[],"label_agreement":null},{"id":"W1520420558","doi":"","title":"Parallel Rollout for Online Solution of Dec-POMDPs.","year":2008,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Scalability; Bounded function; Computer science; Dynamic programming; Mathematical optimization; Horizon; Online algorithm; Algorithm; Mathematics","score_opus":0.06884681804730829,"score_gpt":0.29775692275143795,"score_spread":0.22891010470412965,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1520420558","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013967375,0.00029001175,0.980201,0.00014462548,0.000051575964,0.000112298185,0.00009441991,0.0018127586,0.0033260072],"genre_scores_gemma":[0.5834043,0.0003064797,0.4121288,0.00014071878,0.000030463003,0.00036340184,0.00037572582,0.00018845165,0.0030616655],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99950385,0.00016588235,0.000025044155,0.000115833485,0.00011120916,0.00007829483],"domain_scores_gemma":[0.9984975,0.0010030953,0.00012566865,0.00019954325,0.0000984628,0.000075777745],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011338309,0.0010536691,0.0010524838,0.00038133882,0.00065560197,0.00096991454,0.0010598928,0.00082062976,0.004501853],"category_scores_gemma":[0.0032587813,0.00046913567,0.00068072556,0.0004012922,0.00068891165,0.0011323165,0.0011939195,0.0017286014,0.0005195965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026711146,0.00013990737,0.0006157468,0.000164826,0.00004542101,0.00010268399,0.00007509419,0.8988209,0.0022337292,0.0133962985,0.0019107717,0.08222752],"study_design_scores_gemma":[0.000018506375,0.000028968765,0.00004840421,0.0000064550086,0.0000043257805,0.000012001031,0.00001292159,0.9940562,0.00074579025,0.0044200537,0.000643092,0.0000031615355],"about_ca_topic_score_codex":0.0065350006,"about_ca_topic_score_gemma":0.008597268,"teacher_disagreement_score":0.0065350006,"about_ca_system_score_codex":0.0008171459,"about_ca_system_score_gemma":0.0018330109,"threshold_uncertainty_score":0.015060186},"labels":[],"label_agreement":null},{"id":"W1521899940","doi":"10.1109/robot.1999.770053","title":"Efficient topological exploration","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Traverse; Vertex (graph theory); Robot; Computer science; Compass; Planar graph; Feedback vertex set; Planar; Graph; Topology (electrical circuits); Undirected graph; Topological graph; Artificial intelligence; Combinatorics; Algorithm; Mathematics; Computer vision; Theoretical computer science; Physics; Geography; Computer graphics (images)","score_opus":0.054035900229201815,"score_gpt":0.2823753491163944,"score_spread":0.22833944888719257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1521899940","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06334802,0.0004701316,0.9292408,0.00025607826,0.000024971943,0.00006747584,0.00024847712,0.0010320554,0.005312004],"genre_scores_gemma":[0.58530325,0.0006957288,0.40888748,0.000078478035,0.000040206505,0.00022905799,0.00087571156,0.00020728982,0.003682881],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99959487,0.00013722738,0.000017858925,0.000088039946,0.00009976661,0.00006227732],"domain_scores_gemma":[0.9991242,0.0005279738,0.00008191293,0.0001374464,0.0000747137,0.00005371294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004481302,0.0008011963,0.0010094282,0.00067932316,0.00056560605,0.0009052292,0.0012728027,0.0010190663,0.0032745805],"category_scores_gemma":[0.0034037398,0.00038149298,0.00058300723,0.0011212624,0.0008754711,0.0024352784,0.0017359076,0.0005408633,0.00065295777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017295967,0.00006289943,0.0007128558,0.00020959199,0.00003865639,0.00013979798,0.00012851249,0.8697773,0.0023996166,0.021227036,0.0021015431,0.10302932],"study_design_scores_gemma":[0.000026169644,0.000080252496,0.0002130057,0.000008479211,0.00001242569,0.00007947244,0.000052049512,0.9597991,0.00094580126,0.03678563,0.001988068,0.000009522929],"about_ca_topic_score_codex":0.0016316553,"about_ca_topic_score_gemma":0.0019777676,"teacher_disagreement_score":0.0032745805,"about_ca_system_score_codex":0.00046154557,"about_ca_system_score_gemma":0.00057193,"threshold_uncertainty_score":0.010954618},"labels":[],"label_agreement":null},{"id":"W1523671205","doi":"","title":"On-line Network Synthesis","year":2007,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Competitive analysis; A priori and a posteriori; Set (abstract data type); Line (geometry); Key (lock); Algorithm; Computer science; Matching (statistics); Mathematical optimization; Upper and lower bounds; Mathematics; Statistics","score_opus":0.03409576217455546,"score_gpt":0.28734709955784293,"score_spread":0.2532513373832875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1523671205","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07339194,0.0004126787,0.8904706,0.00054911984,0.00010324575,0.0003261145,0.00042808914,0.0009875988,0.033330634],"genre_scores_gemma":[0.62821484,0.00043762306,0.35318917,0.00038392458,0.00008598715,0.0004196204,0.0007536323,0.0003260837,0.016189167],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99892634,0.00035298307,0.00004041665,0.00022511405,0.0002467909,0.00020849172],"domain_scores_gemma":[0.99793977,0.0012571423,0.00024251238,0.00025723642,0.00021892627,0.00008442822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009325529,0.0013834843,0.0013041892,0.0006005212,0.0006510603,0.001617245,0.0018118755,0.0018482035,0.017699534],"category_scores_gemma":[0.0041603334,0.00052886666,0.0007429131,0.00090366416,0.0007780085,0.0023157275,0.0016564068,0.00093034445,0.0013682299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016885219,0.00011685715,0.00039211957,0.00017047931,0.000033269393,0.00014238645,0.00006857077,0.9250433,0.0020468307,0.013234617,0.002410518,0.05617225],"study_design_scores_gemma":[0.000043392592,0.00008642817,0.00007006258,0.000013841319,0.000011929355,0.000056273577,0.000052438587,0.9777033,0.0018944993,0.017669657,0.0023911071,0.000007161543],"about_ca_topic_score_codex":0.0030791904,"about_ca_topic_score_gemma":0.0038423901,"teacher_disagreement_score":0.017699534,"about_ca_system_score_codex":0.0015546859,"about_ca_system_score_gemma":0.0010647065,"threshold_uncertainty_score":0.059210837},"labels":[],"label_agreement":null},{"id":"W1527958811","doi":"","title":"Canadian traveler problem with remote sensing","year":2009,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Heuristics; Computer science; Minification; Task (project management); Mathematical optimization; Graph; Total cost; Operations research; Theoretical computer science; Engineering; Mathematics; Systems engineering","score_opus":0.012325172932560882,"score_gpt":0.2222813787133415,"score_spread":0.2099562057807806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1527958811","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1953388,0.004254225,0.40821022,0.0144597655,0.00070159114,0.0013636845,0.015973125,0.002533523,0.3571651],"genre_scores_gemma":[0.7431115,0.0020984442,0.137195,0.0011236479,0.00015241315,0.00040741186,0.007469211,0.00040981383,0.1080325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889463,0.00019692231,0.000031207415,0.00027189899,0.00025697474,0.00034842337],"domain_scores_gemma":[0.99905246,0.00038942666,0.00007703015,0.00008844311,0.0001966717,0.00019598809],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008386457,0.0013514097,0.0012973116,0.0009071412,0.003089821,0.0025642433,0.0027328858,0.0029983046,0.027429663],"category_scores_gemma":[0.0030023414,0.00060119294,0.00083305605,0.0027481567,0.0014770685,0.003182532,0.0015482221,0.00215808,0.0013691266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055659824,0.00023282207,0.0021430512,0.00047088123,0.00011498411,0.0010331088,0.00039250695,0.4928419,0.0016200868,0.31444186,0.10804372,0.07810847],"study_design_scores_gemma":[0.0002727888,0.00011293404,0.0021771388,0.00008449741,0.000102984246,0.0005676203,0.000749117,0.7403741,0.0014094,0.14975975,0.10423859,0.00015106941],"about_ca_topic_score_codex":0.60156626,"about_ca_topic_score_gemma":0.579352,"teacher_disagreement_score":0.60156626,"about_ca_system_score_codex":0.0090656765,"about_ca_system_score_gemma":0.01365886,"threshold_uncertainty_score":0.8015604},"labels":[],"label_agreement":null},{"id":"W1537048078","doi":"10.1002/9781118884614.ch6","title":"Swarm Intelligence and the Evolution of Personality Traits","year":2014,"lang":"en","type":"other","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Swarm robotics; Swarm behaviour; Artificial intelligence; Robot; Computer science; Swarm intelligence; Robotics; Ant robotics; Personality psychology; Machine learning; Personality; Mobile robot; Robot control; Particle swarm optimization; Psychology","score_opus":0.021448062346671726,"score_gpt":0.2561666072956732,"score_spread":0.23471854494900146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1537048078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53360283,0.015610885,0.16037533,0.012008959,0.00045618007,0.00013217251,0.00026581707,0.00022844847,0.27731943],"genre_scores_gemma":[0.9586917,0.0033506122,0.019561896,0.00028503514,0.00007278367,0.000046489193,0.000088675966,0.00002452515,0.017878143],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995447,0.00019649517,0.000020394626,0.000065604385,0.00011625955,0.000056467103],"domain_scores_gemma":[0.9991025,0.0003771423,0.00018794868,0.000078321325,0.00012460428,0.00012956622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068101566,0.00029628235,0.00024990685,0.00052348245,0.00063261425,0.0020689936,0.00024775934,0.0006008215,0.0022086136],"category_scores_gemma":[0.0026587192,0.0001475841,0.00028446887,0.00053909793,0.0018405801,0.0010994965,0.0009017323,0.00081297295,0.00029581043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007212256,0.000074123,0.024410892,0.0001991512,0.000108436085,0.0010224209,0.0057660234,0.025003087,0.007539374,0.7566798,0.005337839,0.17378667],"study_design_scores_gemma":[0.000031657386,0.00022303566,0.07134852,0.00020442305,0.000055491342,0.001923989,0.0039020854,0.044272896,0.0017010166,0.76654494,0.109679244,0.00011269596],"about_ca_topic_score_codex":0.0014542103,"about_ca_topic_score_gemma":0.0011206074,"teacher_disagreement_score":0.0022086136,"about_ca_system_score_codex":0.0008126353,"about_ca_system_score_gemma":0.00043064207,"threshold_uncertainty_score":0.0073885918},"labels":[],"label_agreement":null},{"id":"W1537414353","doi":"10.1007/978-3-642-04128-0_23","title":"Optimality and Competitiveness of Exploring Polygons by Mobile Robots","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Polygon (computer graphics); Simple polygon; Mobile robot; Focus (optics); Computer science; Robot; Trajectory; Boundary (topology); Metric (unit); Point (geometry); Square (algebra); Convex polygon; Point in polygon; Motion planning; Computer vision; Artificial intelligence; Regular polygon; Mathematics; Computer graphics (images); Geometry; Engineering","score_opus":0.032012159208564914,"score_gpt":0.26406943252698734,"score_spread":0.2320572733184224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1537414353","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56711847,0.002916074,0.2971343,0.0017299507,0.00022129128,0.00016350111,0.00081565336,0.0004800522,0.12942074],"genre_scores_gemma":[0.8861283,0.0014454116,0.0923435,0.0001232047,0.00020406238,0.0002132875,0.0007557265,0.0005391051,0.01824735],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99872977,0.00033803182,0.00005335719,0.00022142933,0.00032463094,0.0003327664],"domain_scores_gemma":[0.995675,0.0029384247,0.000325287,0.00031034957,0.0002601549,0.000490679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010164895,0.0009265455,0.0021944572,0.0011095178,0.001021165,0.0032392116,0.0022363237,0.0016776354,0.008525225],"category_scores_gemma":[0.0071665947,0.000834673,0.0015085139,0.0017965757,0.003246684,0.003742098,0.002461837,0.0022572414,0.0008896523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009633589,0.0001611635,0.0028255687,0.00039343708,0.00007495656,0.00026291423,0.0005356424,0.30935174,0.007682095,0.6156241,0.0071911854,0.054933798],"study_design_scores_gemma":[0.00014704833,0.00025011747,0.0021986265,0.00006966119,0.00005226615,0.00030141356,0.00035427228,0.34251556,0.0034353526,0.6435816,0.0070507647,0.000043291744],"about_ca_topic_score_codex":0.0038923817,"about_ca_topic_score_gemma":0.0031200114,"teacher_disagreement_score":0.008525225,"about_ca_system_score_codex":0.0013662461,"about_ca_system_score_gemma":0.0013397263,"threshold_uncertainty_score":0.02851969},"labels":[],"label_agreement":null},{"id":"W1539553127","doi":"10.1007/978-3-540-45193-8_125","title":"Restart Strategies: Analysis and Simulation","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cutoff; Mathematical optimization; Algorithm; Mathematics","score_opus":0.02271104224915202,"score_gpt":0.2800543574949932,"score_spread":0.2573433152458412,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1539553127","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0857584,0.009323515,0.83970207,0.0011199496,0.00023147177,0.00017317846,0.00041407565,0.00079680857,0.0624805],"genre_scores_gemma":[0.84971774,0.006755923,0.10622326,0.00031474247,0.00020746147,0.00053988036,0.0004140081,0.0006260673,0.035200853],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993926,0.00024073772,0.000021428865,0.00005996729,0.0001680859,0.000117077056],"domain_scores_gemma":[0.9948414,0.0040871543,0.0002914346,0.0002735974,0.00037188755,0.000134611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013575662,0.0013516581,0.0020005829,0.0012377464,0.0008104823,0.0023414376,0.0026742446,0.0018779929,0.009944246],"category_scores_gemma":[0.010721337,0.00071187626,0.0012520379,0.0018668275,0.0014665778,0.0032078521,0.0012257928,0.00189775,0.001302743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017022586,0.00010631402,0.00060778647,0.0001935132,0.000052096286,0.0000960885,0.00013424839,0.6845357,0.0007548546,0.2709514,0.008093057,0.03430476],"study_design_scores_gemma":[0.000010797484,0.000014770366,0.00009477193,0.000013507879,0.000013237457,0.000024790214,0.000018916917,0.9668422,0.00016377466,0.032112062,0.00068486173,0.000006283772],"about_ca_topic_score_codex":0.0076014474,"about_ca_topic_score_gemma":0.0043095755,"teacher_disagreement_score":0.009944246,"about_ca_system_score_codex":0.0016364214,"about_ca_system_score_gemma":0.0012275793,"threshold_uncertainty_score":0.033266842},"labels":[],"label_agreement":null},{"id":"W1549492047","doi":"10.1007/978-3-540-77891-2_2","title":"Closing the Gap Between Theory and Practice: New Measures for On-Line Algorithm Analysis","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Closing (real estate); Line (geometry); Algorithm; Computer science; Mathematics; Political science; Law; Geometry","score_opus":0.07252690889965911,"score_gpt":0.33353765075610664,"score_spread":0.2610107418564475,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1549492047","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030336229,0.0022969446,0.98834616,0.00145904,0.00021510087,0.00003744686,0.00003495238,0.00027114313,0.0043055844],"genre_scores_gemma":[0.22240399,0.0029895194,0.7644464,0.0012394604,0.0018731131,0.00045875434,0.00017909722,0.0012844832,0.0051252623],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9786227,0.011932158,0.0009172578,0.0016129381,0.006346937,0.00056796346],"domain_scores_gemma":[0.9175868,0.058043707,0.0041942205,0.011383289,0.006647676,0.002144285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014729478,0.0026381314,0.0028430938,0.0040088557,0.0016326117,0.00828228,0.005841082,0.0047186804,0.0059806393],"category_scores_gemma":[0.09179481,0.0012594945,0.001522376,0.0039642127,0.010697053,0.021451995,0.007986011,0.011055237,0.0014127546],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010663715,0.0001357981,0.0007440488,0.00028793514,0.00007638491,0.000029819821,0.00027899703,0.029979333,0.0009358157,0.8317308,0.00681406,0.12888029],"study_design_scores_gemma":[0.000021740507,0.00010250648,0.0002834211,0.00012276917,0.00002783524,0.000053238884,0.00007264474,0.22860429,0.0008179204,0.7621793,0.007682471,0.000031849377],"about_ca_topic_score_codex":0.00086055294,"about_ca_topic_score_gemma":0.00060502096,"teacher_disagreement_score":0.014729478,"about_ca_system_score_codex":0.003059525,"about_ca_system_score_gemma":0.0020154056,"threshold_uncertainty_score":0.07789791},"labels":[],"label_agreement":null},{"id":"W1550403096","doi":"10.1007/978-3-540-72870-2_4","title":"Digraph Strong Searching: Monotonicity and Complexity","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Digraph; Monotonic function; Combinatorics; Enhanced Data Rates for GSM Evolution; Mathematics; Discrete mathematics; Computer science; Artificial intelligence","score_opus":0.0658866268132134,"score_gpt":0.3033950996447445,"score_spread":0.2375084728315311,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550403096","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.124137655,0.0068948334,0.6753688,0.0061882474,0.00029306614,0.00020319934,0.0010915183,0.00056541077,0.18525718],"genre_scores_gemma":[0.76439846,0.0055129686,0.18200499,0.0008471234,0.0004742615,0.00028878768,0.00080302695,0.0002710234,0.045399312],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992539,0.00019669841,0.000045693923,0.00016566574,0.0002519525,0.000086055166],"domain_scores_gemma":[0.99398637,0.004523331,0.00022320753,0.0005891687,0.00040032915,0.0002774429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096818304,0.00052684057,0.0011520304,0.001133861,0.0010831578,0.003775071,0.0016103436,0.0012690303,0.008406003],"category_scores_gemma":[0.0073643825,0.000731404,0.00091749354,0.0022885958,0.0023592713,0.008661766,0.0019493446,0.0033578896,0.00063774624],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004108479,0.00003377838,0.00023866461,0.00018137315,0.000011057642,0.000046368845,0.00009096753,0.005554114,0.0006199215,0.9589441,0.0041307593,0.030107886],"study_design_scores_gemma":[0.000013460275,0.0000143191255,0.00013753054,0.000020597547,0.000010291966,0.0001198273,0.000031965053,0.021886544,0.00041718097,0.97369236,0.0036485994,0.0000073446954],"about_ca_topic_score_codex":0.0014237671,"about_ca_topic_score_gemma":0.0018306534,"teacher_disagreement_score":0.008406003,"about_ca_system_score_codex":0.0019546454,"about_ca_system_score_gemma":0.0014420176,"threshold_uncertainty_score":0.028120935},"labels":[],"label_agreement":null},{"id":"W1550484269","doi":"","title":"Modeling a domain in a tutorial-like system using learning automata","year":2010,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Benchmark (surveying); Domain (mathematical analysis); Process (computing); Representation (politics); Range (aeronautics); Action (physics); Artificial intelligence; Scaling; Theoretical computer science; Programming language; Mathematics","score_opus":0.02102450492435127,"score_gpt":0.26501057412391765,"score_spread":0.2439860691995664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1550484269","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058082506,0.00011133129,0.9343458,0.0003061212,0.000033413726,0.00010064258,0.00014317516,0.00065716007,0.0062198327],"genre_scores_gemma":[0.7021429,0.00026679234,0.28842402,0.00013049936,0.00004389776,0.0005226575,0.00029874055,0.00010909049,0.0080614],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948335,0.00021972666,0.000037215832,0.00012227346,0.00007808555,0.000059431157],"domain_scores_gemma":[0.9988405,0.0006313732,0.00009890222,0.00016017018,0.00016261199,0.00010640979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061514956,0.0005162897,0.00055301125,0.00039753906,0.00043004233,0.0014258206,0.0014460303,0.0014856014,0.0044583282],"category_scores_gemma":[0.0023292291,0.000313228,0.00069631764,0.0003182428,0.0009812032,0.0025187584,0.0011370579,0.0011626811,0.000837293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001034033,0.000160054,0.0015889003,0.0001427966,0.00004493303,0.00027250077,0.00035771553,0.8304998,0.008679876,0.13785434,0.00080894656,0.01948667],"study_design_scores_gemma":[0.000013706089,0.000036829944,0.00010397913,0.000008706364,0.000009613777,0.00003082691,0.000022484875,0.9811219,0.0010639214,0.015945846,0.0016333536,0.0000088236975],"about_ca_topic_score_codex":0.002904645,"about_ca_topic_score_gemma":0.003023126,"teacher_disagreement_score":0.0044583282,"about_ca_system_score_codex":0.0008548651,"about_ca_system_score_gemma":0.0009570455,"threshold_uncertainty_score":0.014914632},"labels":[],"label_agreement":null},{"id":"W1553045544","doi":"10.1007/978-3-540-72792-7_24","title":"DINS, a MIP Improvement Heuristic","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Solver; Heuristics; Computer science; Benchmark (surveying); Mathematical optimization; Neighbourhood (mathematics); Heuristic; Integer programming; Search tree; Algorithm; Mathematics; Search algorithm","score_opus":0.02662322317191979,"score_gpt":0.27321937636394344,"score_spread":0.24659615319202366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1553045544","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013133169,0.0019781555,0.8598537,0.0010576767,0.0017509832,0.00038392478,0.000901914,0.0055104517,0.11543001],"genre_scores_gemma":[0.11553183,0.0009892342,0.8409887,0.0009074217,0.00026498295,0.00034443586,0.0015987233,0.0010352893,0.038339406],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927825,0.0001645146,0.0000316494,0.000101135614,0.00029411,0.00013036847],"domain_scores_gemma":[0.999373,0.00023564155,0.000043611177,0.00012611577,0.00015417492,0.00006744821],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009261995,0.0015554775,0.0012603838,0.0018076453,0.000877116,0.0013308066,0.0023472938,0.0012437968,0.024788594],"category_scores_gemma":[0.0029140676,0.0006907004,0.0012459329,0.002023108,0.0006579038,0.0015550841,0.0019326297,0.002769202,0.0033100983],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047399223,0.00039188992,0.00042559096,0.0005895498,0.00009941383,0.00013288192,0.00007396317,0.25607175,0.0042857844,0.07279319,0.061085913,0.6035761],"study_design_scores_gemma":[0.00020016437,0.00025732737,0.00036222313,0.00015032664,0.00010739223,0.00019281164,0.00007876459,0.8787564,0.0046169204,0.042626966,0.07261273,0.00003791158],"about_ca_topic_score_codex":0.0032407485,"about_ca_topic_score_gemma":0.007527886,"teacher_disagreement_score":0.024788594,"about_ca_system_score_codex":0.0012698622,"about_ca_system_score_gemma":0.0020393624,"threshold_uncertainty_score":0.082926095},"labels":[],"label_agreement":null},{"id":"W1555558392","doi":"10.1007/11930242_11","title":"A Fixed Structure Learning Automaton Micro-aggregation Technique for Secure Statistical Databases","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Heuristic; Automaton; Cellular automaton; Scheme (mathematics); Learning automata; Theoretical computer science; Algorithm; Data mining; Artificial intelligence; Mathematics","score_opus":0.01717331659407111,"score_gpt":0.27487022260351857,"score_spread":0.25769690600944745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1555558392","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005949417,0.00009281408,0.9923666,0.00009807227,0.000030311825,0.00003059963,0.000048940383,0.0006746772,0.00070861157],"genre_scores_gemma":[0.37181547,0.00021664746,0.62160236,0.00018414357,0.000119100274,0.00020732684,0.00027694443,0.00021902403,0.005359001],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985322,0.00036618602,0.00012097895,0.0003068037,0.00052783615,0.00014610923],"domain_scores_gemma":[0.9967572,0.0010419994,0.00015431111,0.0015200209,0.00042253235,0.000103854116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014082185,0.00047925932,0.0013916787,0.00083579554,0.0009430566,0.0012702226,0.002213118,0.0008059542,0.0031564764],"category_scores_gemma":[0.004615102,0.0004865171,0.0010928379,0.0014444683,0.0010400877,0.0023822654,0.0026682573,0.0019652206,0.0009003493],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051043427,0.00021937463,0.0013276838,0.00013136977,0.00014580482,0.00020214307,0.00033643522,0.22667736,0.016925056,0.3025153,0.007885999,0.44312304],"study_design_scores_gemma":[0.000014062171,0.00006978539,0.00013297219,0.000007592385,0.000022670522,0.000085714295,0.000021514803,0.8991457,0.003572453,0.09487515,0.002038442,0.00001389911],"about_ca_topic_score_codex":0.0018306804,"about_ca_topic_score_gemma":0.0028573314,"teacher_disagreement_score":0.0031564764,"about_ca_system_score_codex":0.0010795961,"about_ca_system_score_gemma":0.0014194449,"threshold_uncertainty_score":0.010559499},"labels":[],"label_agreement":null},{"id":"W1563914202","doi":"10.1007/11947950_1","title":"Distributed Security Algorithms by Mobile Agents","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science; Mobile agent; Distributed computing; Natural computing; Theoretical computer science; Mobile computing; Computer network","score_opus":0.013383201721492401,"score_gpt":0.2554056648301265,"score_spread":0.2420224631086341,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1563914202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064440207,0.0010236447,0.9730809,0.00068868,0.00022465548,0.000078129306,0.00002265301,0.0005059851,0.017931342],"genre_scores_gemma":[0.37731197,0.0018472888,0.56578225,0.00038230946,0.00030271505,0.00053054676,0.00013711954,0.00031866963,0.053387176],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991394,0.0003410439,0.000040178293,0.00012528714,0.00028164135,0.00007238849],"domain_scores_gemma":[0.9980646,0.0011256571,0.00009276121,0.00046574793,0.00017864341,0.00007266711],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011506436,0.0008519499,0.00076582225,0.0005944454,0.00077107974,0.001837422,0.0013941971,0.001407144,0.00631458],"category_scores_gemma":[0.0048661213,0.00054762594,0.0005639997,0.0007011112,0.0015868662,0.0029739551,0.0021319806,0.0027274627,0.001784174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017818867,0.00006289231,0.00019404665,0.00019261443,0.00004625013,0.00007843364,0.00022456092,0.08175967,0.0053109135,0.75140715,0.009693186,0.15085208],"study_design_scores_gemma":[0.00010380719,0.00007388046,0.00007121859,0.00005656546,0.000026201202,0.00015174037,0.000048373637,0.40199363,0.0050714454,0.55862707,0.03376056,0.000015470656],"about_ca_topic_score_codex":0.00028484038,"about_ca_topic_score_gemma":0.00029513377,"teacher_disagreement_score":0.00631458,"about_ca_system_score_codex":0.0007562188,"about_ca_system_score_gemma":0.00055069034,"threshold_uncertainty_score":0.021124363},"labels":[],"label_agreement":null},{"id":"W1566553893","doi":"10.1007/3-540-45253-2_7","title":"Online Algorithms for Caching Multimedia Streams","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Computer science; Cache; Cache algorithms; False sharing; Competitive analysis; CPU cache; The Internet; Computer network; Online algorithm; Metric (unit); Smart Cache; Algorithm; Parallel computing; Operating system; Upper and lower bounds","score_opus":0.029720099908789127,"score_gpt":0.2885864229711798,"score_spread":0.25886632306239066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1566553893","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018275797,0.0014790944,0.9696527,0.0005505889,0.00024992443,0.00017990432,0.00030212896,0.0031597854,0.0061500734],"genre_scores_gemma":[0.28955942,0.0014799273,0.691951,0.00031751473,0.0004790241,0.00054270006,0.0010049604,0.0005976685,0.014067871],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99819654,0.00042266396,0.0001335296,0.00033690958,0.0005617503,0.0003485799],"domain_scores_gemma":[0.99250257,0.00437257,0.00040214483,0.0017137501,0.0007386058,0.000270249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024353515,0.0019525421,0.0027498205,0.0017446887,0.0014631881,0.0038165583,0.0051951245,0.0025739989,0.012060032],"category_scores_gemma":[0.012911694,0.0010380786,0.0008624935,0.004661851,0.0014502703,0.0072519425,0.002800638,0.002435012,0.002097066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014848553,0.00066845963,0.0009791722,0.00040955338,0.00012631342,0.00011106966,0.00017752402,0.34086117,0.00518277,0.11567574,0.034533076,0.49979022],"study_design_scores_gemma":[0.00012889931,0.000058858484,0.00008981569,0.000018755407,0.000031359024,0.00006912226,0.000035488203,0.9192309,0.0015401691,0.07665592,0.0021267706,0.000014050125],"about_ca_topic_score_codex":0.0047120047,"about_ca_topic_score_gemma":0.0058427714,"teacher_disagreement_score":0.012060032,"about_ca_system_score_codex":0.0027122549,"about_ca_system_score_gemma":0.0022955507,"threshold_uncertainty_score":0.040344894},"labels":[],"label_agreement":null},{"id":"W1568409091","doi":"10.1007/978-3-540-68825-9_31","title":"A Stochastic Point-Based Algorithm for POMDPs","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Algorithm; Benchmark (surveying); Operator (biology); Bellman equation; Markov decision process; Mathematical optimization; Markov process; Mathematics","score_opus":0.022704779862040107,"score_gpt":0.25775837026379134,"score_spread":0.23505359040175122,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1568409091","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015117148,0.000057023448,0.9965062,0.000054558008,0.00003587808,0.0000604476,0.000038843842,0.00046468028,0.0012706796],"genre_scores_gemma":[0.0762539,0.0001301159,0.9203716,0.000099070814,0.000052507738,0.00043700173,0.00022948199,0.00025969863,0.002166646],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987379,0.00031115048,0.00008591366,0.0002463667,0.0004885629,0.000130042],"domain_scores_gemma":[0.99792445,0.001405826,0.000086208776,0.00015449227,0.00032703206,0.00010189486],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024120524,0.001596229,0.0025644384,0.001119067,0.0010990953,0.0017654897,0.003255142,0.0027689135,0.008718968],"category_scores_gemma":[0.005850554,0.0014168695,0.0019687507,0.0017177999,0.0015375664,0.0018700432,0.0035702274,0.0033189668,0.0016618605],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015122956,0.00009151697,0.00024166738,0.00014747844,0.000071328366,0.000052294952,0.00007866552,0.81873125,0.0010074421,0.046911452,0.0026531506,0.12986253],"study_design_scores_gemma":[0.00004047205,0.000019738463,0.000020806878,0.000010320308,0.000008476828,0.000010275868,0.0000057628217,0.9857655,0.00021181724,0.013247465,0.00065273,0.0000065926747],"about_ca_topic_score_codex":0.0087594455,"about_ca_topic_score_gemma":0.0087524885,"teacher_disagreement_score":0.0087594455,"about_ca_system_score_codex":0.0017694134,"about_ca_system_score_gemma":0.0031131492,"threshold_uncertainty_score":0.029167831},"labels":[],"label_agreement":null},{"id":"W1573954828","doi":"10.1007/11561071_29","title":"Cache-Oblivious Comparison-Based Algorithms on Multisets","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cache; Cache algorithms; Block (permutation group theory); CPU cache; Randomized algorithm; Context (archaeology); Cache-oblivious algorithm; Factor (programming language); Block size; Constant (computer programming); Algorithm; Upper and lower bounds; Parallel computing; Mathematics; Key (lock); Combinatorics","score_opus":0.03047518635121663,"score_gpt":0.28839035740204444,"score_spread":0.2579151710508278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1573954828","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049328584,0.002798893,0.9255091,0.0007661694,0.0003617494,0.0002132412,0.00044025487,0.005820585,0.014761465],"genre_scores_gemma":[0.34850067,0.0007911558,0.6328394,0.00041702017,0.00025008628,0.00048450884,0.00087605545,0.0010961341,0.014744959],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970018,0.0007195842,0.00022290082,0.0005427295,0.001103945,0.00040913158],"domain_scores_gemma":[0.991916,0.0037255227,0.0003547241,0.0031115396,0.000690133,0.00020209084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021763367,0.0012644309,0.0028268704,0.0022455256,0.0025855186,0.003044814,0.0052888896,0.0019024705,0.011032934],"category_scores_gemma":[0.0099349925,0.001259179,0.001386872,0.0065315994,0.001940493,0.009925185,0.005566577,0.0034310191,0.0024263784],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023539835,0.00041488223,0.00094310666,0.000705571,0.0002070561,0.00014757329,0.00051308447,0.16800582,0.011797851,0.23115622,0.029515177,0.5542397],"study_design_scores_gemma":[0.00021434123,0.00026894925,0.0003168552,0.0000969964,0.000098123666,0.00024118987,0.000098754346,0.5061718,0.011436254,0.4710662,0.009936133,0.000054370474],"about_ca_topic_score_codex":0.0016507651,"about_ca_topic_score_gemma":0.0027592685,"teacher_disagreement_score":0.011032934,"about_ca_system_score_codex":0.002574633,"about_ca_system_score_gemma":0.002288966,"threshold_uncertainty_score":0.036908865},"labels":[],"label_agreement":null},{"id":"W1577356920","doi":"10.1007/978-3-540-73545-8_38","title":"An Improved Algorithm for Online Unit Clustering","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Cluster analysis; Computer science; Partition (number theory); Online algorithm; Dimension (graph theory); Upper and lower bounds; Algorithm; Randomized algorithm; Sequence (biology); Unit (ring theory); Combinatorics; Mathematics; Artificial intelligence","score_opus":0.04442696935424467,"score_gpt":0.3146518800575907,"score_spread":0.27022491070334603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1577356920","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0047022686,0.00021042603,0.9885882,0.00012786328,0.00021294504,0.00014935734,0.00019131937,0.0029996822,0.0028179085],"genre_scores_gemma":[0.032201797,0.00010056554,0.95914584,0.00011811957,0.00009334247,0.0002714229,0.0005740491,0.00041952214,0.0070752213],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99820876,0.0003518402,0.00011593687,0.00042740515,0.0006546615,0.00024132851],"domain_scores_gemma":[0.99792993,0.00057356065,0.00009465498,0.00064891245,0.0006108544,0.00014205535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013991245,0.0017147706,0.0029275587,0.0022737137,0.0019183935,0.0020772645,0.005533118,0.0026209634,0.017262958],"category_scores_gemma":[0.0051686727,0.00094490714,0.001572216,0.0044882633,0.0008610693,0.003122207,0.0041727345,0.0023024105,0.0075187106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059740775,0.00030891586,0.00045909977,0.00019205337,0.00008763025,0.00008435714,0.00014384477,0.12913162,0.006050168,0.02076457,0.024660883,0.81751937],"study_design_scores_gemma":[0.00010919886,0.00007247201,0.00023404806,0.0000144710175,0.000033354372,0.00009687723,0.000046518475,0.9738338,0.0032664915,0.015600451,0.00666471,0.000027625545],"about_ca_topic_score_codex":0.008805747,"about_ca_topic_score_gemma":0.012624195,"teacher_disagreement_score":0.017262958,"about_ca_system_score_codex":0.0019306935,"about_ca_system_score_gemma":0.0030247907,"threshold_uncertainty_score":0.057750344},"labels":[],"label_agreement":null},{"id":"W1580603885","doi":"","title":"Mobile Facility Location","year":2008,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Computer science; Facility location problem; Engineering; Operations research","score_opus":0.03474948807836565,"score_gpt":0.26069029442504194,"score_spread":0.2259408063466763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1580603885","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02601291,0.0014454233,0.9647261,0.00042773766,0.000089576555,0.00008379334,0.00046681694,0.0003408401,0.0064067803],"genre_scores_gemma":[0.7701122,0.0023338143,0.21530427,0.00016659584,0.0002964626,0.00019015865,0.0010612108,0.00014216386,0.010393188],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984244,0.00036744005,0.0000502271,0.00044474204,0.00047316455,0.00024003934],"domain_scores_gemma":[0.99706715,0.0013898058,0.00062396785,0.0003098879,0.00043298097,0.00017613155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001187742,0.0010721101,0.0012705027,0.0016632425,0.00091403007,0.0024684877,0.0031669273,0.0021844297,0.005624459],"category_scores_gemma":[0.0073868083,0.0005413881,0.00063461455,0.0025152208,0.0012654985,0.00451353,0.0023153916,0.0011263372,0.0019881404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035034,0.00006420739,0.0042438637,0.0005071964,0.00008522888,0.00037502393,0.00017759329,0.63697404,0.005139972,0.24548262,0.0068860166,0.09971393],"study_design_scores_gemma":[0.000032641055,0.0002576783,0.0015819629,0.00007838856,0.000053951153,0.00090288214,0.00023797875,0.87104285,0.0053257504,0.099636726,0.020781055,0.000068081725],"about_ca_topic_score_codex":0.0024086311,"about_ca_topic_score_gemma":0.0017530258,"teacher_disagreement_score":0.005624459,"about_ca_system_score_codex":0.0022764467,"about_ca_system_score_gemma":0.0009127715,"threshold_uncertainty_score":0.018815756},"labels":[],"label_agreement":null},{"id":"W1581952794","doi":"10.1007/11424918_49","title":"Real-Time Decision Making for Large POMDPs","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Artificial intelligence; Time complexity; Machine learning; Algorithm","score_opus":0.020460163069960756,"score_gpt":0.2921280880127875,"score_spread":0.27166792494282677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1581952794","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017493322,0.0005503492,0.9735796,0.0004693787,0.00009039128,0.00009612023,0.00014515963,0.000453145,0.0071224924],"genre_scores_gemma":[0.5943746,0.0009662194,0.39356133,0.00018599915,0.00016507585,0.00046555782,0.00053516513,0.00034835585,0.009397615],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857426,0.00046562374,0.00010678281,0.00032903877,0.00032224652,0.0002020685],"domain_scores_gemma":[0.9919321,0.0069545163,0.00029275753,0.00033704573,0.0002446062,0.00023896132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003559905,0.0012692248,0.002014533,0.00050828926,0.0011354235,0.002684978,0.0021310607,0.0016356271,0.009692225],"category_scores_gemma":[0.009661964,0.0015040705,0.0016058183,0.0009892833,0.0017911966,0.0043769847,0.0023386145,0.00394673,0.0008054521],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018440376,0.00008340631,0.00022144747,0.0002918135,0.000063553074,0.00012957805,0.00017004652,0.86695457,0.0013233087,0.08476146,0.0024043012,0.04341225],"study_design_scores_gemma":[0.000027046859,0.00002161247,0.000042086645,0.000011968104,0.000011817171,0.000019974661,0.00002656823,0.91639745,0.00037455477,0.08223492,0.00082288065,0.000009067645],"about_ca_topic_score_codex":0.004458925,"about_ca_topic_score_gemma":0.0054581147,"teacher_disagreement_score":0.009692225,"about_ca_system_score_codex":0.0018796212,"about_ca_system_score_gemma":0.0018004228,"threshold_uncertainty_score":0.032423735},"labels":[],"label_agreement":null},{"id":"W1583311479","doi":"10.1007/3-540-46506-5_10","title":"Parallel Job Scheduling: A Performance Perspective","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Multiprocessing; Scheduling (production processes); Parallel computing; Distributed computing; Perspective (graphical); Range (aeronautics); Software; Multiprocessor scheduling; Dynamic priority scheduling; Two-level scheduling; Operating system; Mathematical optimization; Artificial intelligence","score_opus":0.02235564977128326,"score_gpt":0.26122483651582196,"score_spread":0.2388691867445387,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1583311479","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024140073,0.058912173,0.6624368,0.021170313,0.0044476525,0.0001187948,0.0005647388,0.0023598608,0.22584964],"genre_scores_gemma":[0.60423046,0.073095396,0.1633358,0.0028478687,0.021812411,0.0002831483,0.0006201739,0.0026932706,0.13108148],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982285,0.00033158972,0.00007501037,0.00021004766,0.0008934848,0.00026145217],"domain_scores_gemma":[0.9967757,0.0019256963,0.00017469097,0.0003530406,0.0005774817,0.00019338242],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024651121,0.002516671,0.0017514427,0.0014261879,0.0010889475,0.00493591,0.004149878,0.0023485883,0.01189159],"category_scores_gemma":[0.006287637,0.0011895281,0.0005766593,0.0034910766,0.0021869878,0.009147994,0.0015759659,0.0041276733,0.0043990244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000474941,0.00027116106,0.00039188896,0.0012261437,0.0000634697,0.0001983904,0.00013378855,0.14097033,0.011957257,0.67219764,0.027990246,0.14412467],"study_design_scores_gemma":[0.000053936943,0.00037654003,0.0007433435,0.00022586466,0.000092246766,0.0004810216,0.0001815933,0.35811982,0.014935555,0.53669167,0.088035256,0.00006320865],"about_ca_topic_score_codex":0.0010302071,"about_ca_topic_score_gemma":0.0008091439,"teacher_disagreement_score":0.01189159,"about_ca_system_score_codex":0.001958709,"about_ca_system_score_gemma":0.0009147396,"threshold_uncertainty_score":0.03978139},"labels":[],"label_agreement":null},{"id":"W1585579633","doi":"10.1007/978-3-540-74466-5_65","title":"A Decentralized Solution for Locating Mobile Agents","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Tree traversal; Mobile agent; Distributed computing; Path (computing); Tracking (education); Task (project management); Computer network; Artificial intelligence; Algorithm","score_opus":0.049261638637743486,"score_gpt":0.31638860147827047,"score_spread":0.267126962840527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1585579633","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0052559017,0.00010096441,0.9897092,0.00015877903,0.00005782277,0.0000659638,0.000042611937,0.00029181136,0.004316902],"genre_scores_gemma":[0.23983851,0.00031589714,0.7411439,0.0001323244,0.00011684628,0.0006189019,0.00019304013,0.00013140851,0.017509185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957556,0.000112987946,0.000019324909,0.00010256762,0.00013147494,0.000058156664],"domain_scores_gemma":[0.99960107,0.00019292136,0.000037986116,0.00005552205,0.00008128565,0.000031253618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071892916,0.0008016763,0.0013009921,0.0007135556,0.0010808449,0.0007758082,0.0020770263,0.002368934,0.0064117415],"category_scores_gemma":[0.0022593332,0.00058791274,0.0006736677,0.0011186113,0.00078690186,0.0012462877,0.0024089187,0.0009181529,0.0010491912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021271114,0.00011271885,0.00023005457,0.00025079088,0.0000479917,0.00016486588,0.00017707511,0.724361,0.00678829,0.071964845,0.008717384,0.18697226],"study_design_scores_gemma":[0.000102606675,0.00008109506,0.000075040734,0.0000141665205,0.000018731525,0.00007830233,0.000044377517,0.968073,0.00094841653,0.026663592,0.0038896091,0.000011090771],"about_ca_topic_score_codex":0.0021401371,"about_ca_topic_score_gemma":0.0034054986,"teacher_disagreement_score":0.0064117415,"about_ca_system_score_codex":0.0006716736,"about_ca_system_score_gemma":0.0012424155,"threshold_uncertainty_score":0.021449387},"labels":[],"label_agreement":null},{"id":"W1586507268","doi":"10.1007/978-3-642-12450-1_10","title":"Parameterized Analysis of Paging and List Update Algorithms","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paging; Computer science; Parameterized complexity; Locality; Cache; Locality of reference; Algorithm; Online algorithm; Set (abstract data type); Cache algorithms; Working set; Memory hierarchy; CPU cache; Theoretical computer science; Parallel computing","score_opus":0.017475784857701803,"score_gpt":0.2632109931213892,"score_spread":0.2457352082636874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1586507268","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.054928366,0.0028416193,0.90383947,0.0024381063,0.00026182603,0.00025181295,0.0010618852,0.0023357898,0.03204125],"genre_scores_gemma":[0.7057191,0.002919869,0.24997286,0.00074071577,0.0012272286,0.0008025451,0.0029372121,0.002825219,0.032855168],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9930862,0.0023471133,0.00029829697,0.00084394444,0.0021518057,0.0012726942],"domain_scores_gemma":[0.96496624,0.023877822,0.0018739933,0.005883382,0.0024258655,0.00097278436],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005112497,0.0021815856,0.002685541,0.0027093429,0.0018935429,0.0076258094,0.007190526,0.0028488445,0.022014517],"category_scores_gemma":[0.04667685,0.0018316192,0.0024480566,0.0058274274,0.0026443917,0.013979813,0.003592102,0.005427893,0.0028455441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006404231,0.00034403012,0.0021467935,0.00038034137,0.0001471996,0.00011886801,0.0003294152,0.34889975,0.0029928407,0.5374619,0.02242359,0.08411489],"study_design_scores_gemma":[0.00004333493,0.000038874754,0.00044338993,0.00003526359,0.000061283754,0.00006409015,0.000044038563,0.75207126,0.00094671466,0.24344876,0.0027773755,0.000025575584],"about_ca_topic_score_codex":0.004756529,"about_ca_topic_score_gemma":0.0041046883,"teacher_disagreement_score":0.022014517,"about_ca_system_score_codex":0.0068757175,"about_ca_system_score_gemma":0.0049037975,"threshold_uncertainty_score":0.07364595},"labels":[],"label_agreement":null},{"id":"W1588435642","doi":"","title":"Exact Algorithms for the Canadian Traveller Problem on Paths and Trees","year":2008,"lang":"en","type":"article","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Traverse; Generalization; Approximation algorithm; Combinatorics; Computer science; Enhanced Data Rates for GSM Evolution; Algorithm; Exact solutions in general relativity; Discrete mathematics; Mathematics; Theoretical computer science; Artificial intelligence","score_opus":0.032464090857766255,"score_gpt":0.2568305085769395,"score_spread":0.22436641771917326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1588435642","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051533524,0.001916674,0.9160363,0.002799348,0.0001585152,0.00040694684,0.0016042927,0.0024269512,0.023117572],"genre_scores_gemma":[0.3037579,0.0013777309,0.67332846,0.00048787,0.00017812192,0.0005027824,0.002794701,0.00069199235,0.01688042],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984983,0.00032513568,0.00007182974,0.00039160246,0.00031604723,0.00039710032],"domain_scores_gemma":[0.9959241,0.0028700668,0.00024236254,0.00045280298,0.00026991227,0.00024079891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017716569,0.0016561268,0.0019419934,0.0014894394,0.0015785506,0.0027609002,0.0036593666,0.0027844512,0.014729306],"category_scores_gemma":[0.010544786,0.00088705873,0.0012631298,0.0042127245,0.0016417737,0.005842046,0.0027771443,0.0030885949,0.0017100004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026566826,0.00026258914,0.0010722105,0.00031788743,0.00008102293,0.00011054072,0.00033444646,0.62499195,0.00058621546,0.21155173,0.029785581,0.13064009],"study_design_scores_gemma":[0.00010658286,0.000032443993,0.00023433486,0.000026689331,0.000022529606,0.000061051716,0.000099423385,0.7709908,0.00026364357,0.2244018,0.0037406755,0.000020086462],"about_ca_topic_score_codex":0.04795165,"about_ca_topic_score_gemma":0.07218896,"teacher_disagreement_score":0.04795165,"about_ca_system_score_codex":0.0052970033,"about_ca_system_score_gemma":0.006273433,"threshold_uncertainty_score":0.09534508},"labels":[],"label_agreement":null},{"id":"W1591135906","doi":"10.1007/978-3-540-77891-2_19","title":"On Certain New Models for Paging with Locality of Reference","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Locality; Paging; Computer science; Locality of reference; Competitive analysis; Context (archaeology); Metric (unit); Reference model; Algorithm; Theoretical computer science; Mathematics; Upper and lower bounds; Engineering","score_opus":0.05689773143409504,"score_gpt":0.2729436992893933,"score_spread":0.21604596785529828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1591135906","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04993362,0.001689469,0.873934,0.0074205277,0.00045263764,0.00019452577,0.0009842395,0.0015079047,0.06388316],"genre_scores_gemma":[0.7529076,0.0030382536,0.16059047,0.0027521711,0.0018343382,0.0007049607,0.0014711361,0.0015305269,0.075170614],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99603856,0.001306356,0.0003011906,0.00072830357,0.0008791807,0.0007464135],"domain_scores_gemma":[0.97767794,0.011190647,0.0019785413,0.0059817447,0.0017893605,0.0013816892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037402073,0.0014097953,0.0029928929,0.0025474923,0.003983108,0.008147967,0.00716053,0.0066432115,0.020661015],"category_scores_gemma":[0.028589772,0.001781734,0.0033729798,0.0054411534,0.006320959,0.024381852,0.0056336457,0.008384631,0.0028463698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040422125,0.000029198913,0.00013662806,0.000041017433,0.000009318979,0.00005705535,0.00014258949,0.008820505,0.00016143074,0.98413557,0.0032070293,0.0032193004],"study_design_scores_gemma":[0.00002284804,0.000012348559,0.00004244306,0.000017061908,0.000014695231,0.00008209108,0.00004480055,0.056450464,0.000120646386,0.94050884,0.0026645774,0.00001920916],"about_ca_topic_score_codex":0.004434666,"about_ca_topic_score_gemma":0.0041890773,"teacher_disagreement_score":0.020661015,"about_ca_system_score_codex":0.004849403,"about_ca_system_score_gemma":0.0024269256,"threshold_uncertainty_score":0.06911802},"labels":[],"label_agreement":null},{"id":"W1592266906","doi":"10.1007/978-3-642-14162-1_42","title":"Tell Me Where I Am So I Can Meet You Sooner","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec; Université du Québec à Montréal","funders":"","keywords":"Rendezvous; Computer science; Asynchronous communication; Visibility; Bounded function; Plane (geometry); Multi-agent system; Position (finance); Algorithm; Artificial intelligence; Mathematics; Telecommunications","score_opus":0.01581950816149603,"score_gpt":0.24394778007968862,"score_spread":0.2281282719181926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1592266906","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018226133,0.0077909953,0.012108505,0.029217754,0.017136386,0.000097464785,0.00040384664,0.0009951971,0.9304273],"genre_scores_gemma":[0.0028723378,0.002189962,0.001221624,0.0040073236,0.00084396184,0.00003283787,0.000071578,0.0001911202,0.98856914],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99985147,0.00002293895,0.000004160528,0.000026673291,0.00007106328,0.000023638662],"domain_scores_gemma":[0.9995735,0.000066679095,0.00002601904,0.00003740023,0.00012581379,0.00017063582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002906631,0.0008547255,0.0006033812,0.0004974327,0.001706529,0.0027477462,0.0006010922,0.0012548752,0.2515537],"category_scores_gemma":[0.0016467371,0.00032439598,0.00047905336,0.00047743745,0.0005357455,0.0036475912,0.0019630522,0.003740419,0.2632955],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018578494,0.000027811828,0.00011485664,0.000052638887,0.00000568474,0.000064546686,0.00037782983,0.000053873926,0.00040994622,0.008129718,0.9061352,0.08460932],"study_design_scores_gemma":[0.000004555624,0.000013298592,0.00017083135,0.00007343659,0.000004181787,0.00020609044,0.00037723785,0.000055987726,0.000108777305,0.0035082633,0.9954704,0.0000069318653],"about_ca_topic_score_codex":0.0008120988,"about_ca_topic_score_gemma":0.0019563157,"teacher_disagreement_score":0.2515537,"about_ca_system_score_codex":0.00043707978,"about_ca_system_score_gemma":0.0004910626,"threshold_uncertainty_score":0.84153104},"labels":[],"label_agreement":null},{"id":"W1593308833","doi":"10.1007/978-3-642-13036-6_13","title":"Secretary Problems via Linear Programming","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Secretary problem; Linear programming; Context (archaeology); Set (abstract data type); Polytope; Order (exchange); Mathematical optimization; Common value auction; Operations research; Algorithm; Programming language; Mathematics; Optimal stopping","score_opus":0.018958559996648274,"score_gpt":0.25072657685951816,"score_spread":0.23176801686286988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1593308833","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018180193,0.0043216436,0.41391745,0.006916281,0.0009828805,0.00012689587,0.00063098496,0.00062951085,0.55429417],"genre_scores_gemma":[0.4425639,0.008862992,0.14159323,0.0017379171,0.0024823532,0.00087628677,0.0019282863,0.00095845404,0.39899665],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993262,0.0002765049,0.000027272155,0.00011341961,0.00017217327,0.000084497486],"domain_scores_gemma":[0.9994373,0.00034908723,0.00004107122,0.0000712748,0.00004715733,0.00005403944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079978403,0.0009901182,0.0011543939,0.00092108344,0.0010879372,0.0040639997,0.0012137954,0.0013477106,0.027977692],"category_scores_gemma":[0.002803328,0.00059280545,0.0012710036,0.0016279481,0.0019192201,0.004788884,0.0022351034,0.006518743,0.0053845523],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014379131,0.000023438493,0.000028368477,0.00006486695,0.000007051485,0.000010436936,0.000060342605,0.0018293373,0.00017414463,0.96567565,0.0111295525,0.02098238],"study_design_scores_gemma":[0.00001339949,0.000009289578,0.000029759383,0.000020446421,0.0000058266232,0.00002628915,0.000035381854,0.0075474894,0.0002153229,0.9768063,0.015284444,0.0000060700713],"about_ca_topic_score_codex":0.00050314324,"about_ca_topic_score_gemma":0.00050289655,"teacher_disagreement_score":0.027977692,"about_ca_system_score_codex":0.0013401111,"about_ca_system_score_gemma":0.0007585135,"threshold_uncertainty_score":0.09359473},"labels":[],"label_agreement":null},{"id":"W1594260854","doi":"10.1007/978-3-540-24677-0_26","title":"Stochastic Learning Automata-Based Dynamic Algorithms for the Single Source Shortest Path Problem","year":2004,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Shortest path problem; Computer science; Shortest Path Faster Algorithm; K shortest path routing; Yen's algorithm; Algorithm; Widest path problem; Floyd–Warshall algorithm; Learning automata; Graph; Euclidean shortest path; Constrained Shortest Path First; Automaton; Dijkstra's algorithm; Mathematical optimization; Theoretical computer science; Mathematics","score_opus":0.017924304915619162,"score_gpt":0.2598657693234213,"score_spread":0.24194146440780215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1594260854","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014123517,0.0005362633,0.97961926,0.0003459559,0.00009874822,0.000056751396,0.000117127485,0.00053420773,0.004568217],"genre_scores_gemma":[0.5124037,0.0012036411,0.47454324,0.00023380783,0.0001719523,0.0005198743,0.00063251954,0.0003880208,0.009903135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923813,0.0002214774,0.000051069725,0.00020375472,0.00019212035,0.000093437884],"domain_scores_gemma":[0.9960014,0.0031212983,0.00017845683,0.00020928463,0.00036194883,0.00012766062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011935203,0.0010533108,0.0019345004,0.0011399563,0.0008883186,0.0015334929,0.00282793,0.0018148187,0.0050301673],"category_scores_gemma":[0.0062521845,0.00077997154,0.0010626384,0.0017317836,0.0015586488,0.0026276195,0.0021323257,0.0029393225,0.00076326577],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006298119,0.000045746918,0.00018855378,0.00006866948,0.000026917653,0.000018115245,0.000050509414,0.9107169,0.0003972676,0.04029357,0.0017542365,0.046376508],"study_design_scores_gemma":[0.0000108088325,0.0000091995935,0.000018775978,0.0000046390905,0.0000041443877,0.000006297099,0.0000046281802,0.97413945,0.000086931585,0.025406139,0.00030482627,0.0000041655594],"about_ca_topic_score_codex":0.008943189,"about_ca_topic_score_gemma":0.009102129,"teacher_disagreement_score":0.008943189,"about_ca_system_score_codex":0.0019074125,"about_ca_system_score_gemma":0.001985629,"threshold_uncertainty_score":0.01778227},"labels":[],"label_agreement":null},{"id":"W1600549686","doi":"10.1007/11564751_110","title":"Scheduling with Uncertain Start Dates","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Scheduling (production processes); Tuple; Mathematical optimization; Schedule; Job shop scheduling; Sample (material); Operations research; Mathematics","score_opus":0.02581523720451846,"score_gpt":0.2610899292324612,"score_spread":0.23527469202794277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1600549686","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04009816,0.0020713639,0.9159019,0.00091556244,0.000787194,0.00022746138,0.0008195926,0.0008981926,0.038280576],"genre_scores_gemma":[0.6886258,0.0028372577,0.24890482,0.00028110304,0.0010274549,0.0003538788,0.0012609643,0.00053060916,0.05617822],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928904,0.00019692887,0.00003961658,0.00016427384,0.00018546567,0.00012457193],"domain_scores_gemma":[0.9984977,0.0008550162,0.00013777321,0.00022846596,0.00012561405,0.00015549564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013629807,0.0012451836,0.0018064256,0.0005674195,0.00084353087,0.0019942143,0.002000559,0.0010941144,0.010487992],"category_scores_gemma":[0.0035910015,0.0010652676,0.00078750384,0.0017238666,0.0006942807,0.0018352842,0.0009917388,0.001612539,0.0019952937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008080056,0.0001279718,0.00024742342,0.00047252112,0.000080002406,0.00020824614,0.00010884031,0.7572469,0.0046503767,0.13591316,0.01451967,0.08561689],"study_design_scores_gemma":[0.0000976203,0.00014334086,0.00021042794,0.000034603512,0.000033928718,0.00008218329,0.000036134432,0.7988553,0.0020177276,0.18652594,0.011934097,0.000028626617],"about_ca_topic_score_codex":0.0019752665,"about_ca_topic_score_gemma":0.0019178989,"teacher_disagreement_score":0.010487992,"about_ca_system_score_codex":0.0013533321,"about_ca_system_score_gemma":0.001442653,"threshold_uncertainty_score":0.035085857},"labels":[],"label_agreement":null},{"id":"W1602680134","doi":"10.1007/978-3-642-29116-6_13","title":"A New Perspective on List Update: Probabilistic Locality and Working Set","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Locality; Working set; Property (philosophy); Set (abstract data type); Perspective (graphical); Probabilistic logic; Context (archaeology); Theoretical computer science; Algorithm; Locality of reference; Data mining; Artificial intelligence; Parallel computing","score_opus":0.03294439704847021,"score_gpt":0.2807151596800382,"score_spread":0.24777076263156797,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1602680134","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011598312,0.010013911,0.92529196,0.013464085,0.0010062791,0.00005815719,0.0003778693,0.00051218,0.03767721],"genre_scores_gemma":[0.5958213,0.015364644,0.3232796,0.0045123813,0.010945732,0.0005194722,0.0006613364,0.0011362677,0.047759216],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954797,0.00171742,0.00023254936,0.0008695409,0.0013523314,0.00034830463],"domain_scores_gemma":[0.982173,0.011295052,0.0008815525,0.0039397315,0.0011672166,0.0005434393],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004437901,0.0008242167,0.0025128722,0.002329464,0.0028353704,0.0069478406,0.0068733445,0.0046792105,0.013477174],"category_scores_gemma":[0.023369214,0.0012679851,0.0015816138,0.00637267,0.007611422,0.028645823,0.0051543904,0.0071703717,0.0017596756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031242656,0.000022349888,0.00013440354,0.00008118153,0.000011828487,0.000034319888,0.00015707134,0.0051381686,0.00014936554,0.9733085,0.0047819065,0.016149668],"study_design_scores_gemma":[0.000010891402,0.000014598649,0.000054057753,0.000020621921,0.00001360047,0.00007372229,0.000043646327,0.031340618,0.00018162743,0.9614275,0.006803278,0.000015890237],"about_ca_topic_score_codex":0.0029610125,"about_ca_topic_score_gemma":0.0020893428,"teacher_disagreement_score":0.013477174,"about_ca_system_score_codex":0.003114172,"about_ca_system_score_gemma":0.0018859528,"threshold_uncertainty_score":0.04508567},"labels":[],"label_agreement":null},{"id":"W1605516979","doi":"10.1007/978-3-642-14165-2_16","title":"Faster Algorithms for Semi-matching Problems (Extended Abstract)","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Algorithm; Matching (statistics); Theoretical computer science; Mathematics","score_opus":0.028262169147844112,"score_gpt":0.27737858354945577,"score_spread":0.24911641440161167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1605516979","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011755497,0.0015130374,0.9682484,0.00063695566,0.0006645829,0.00017136367,0.00041250626,0.0028619084,0.013735707],"genre_scores_gemma":[0.067944065,0.0006812875,0.91250515,0.00043258956,0.00035026408,0.00038040028,0.0015843378,0.0011572646,0.014964703],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99793434,0.00041313644,0.00013346602,0.0005355982,0.0007186866,0.00026475615],"domain_scores_gemma":[0.9960924,0.0017283063,0.00020637659,0.0012703324,0.00055780914,0.00014470736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002356819,0.0020252485,0.0024148065,0.0018770582,0.0011128173,0.0027507334,0.0037104646,0.0024973906,0.04017836],"category_scores_gemma":[0.00881612,0.0012273799,0.0029054887,0.004779119,0.0010973278,0.0082845595,0.0037416576,0.004425604,0.010944779],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000912419,0.000613401,0.0006077563,0.0010659967,0.00020001199,0.00010580517,0.00024647405,0.078805685,0.008907556,0.14512046,0.056737617,0.70667684],"study_design_scores_gemma":[0.00038754448,0.00016688013,0.0006925896,0.00011798391,0.0001037155,0.0002576873,0.0000900808,0.55623186,0.006621837,0.4083936,0.026886303,0.000049918148],"about_ca_topic_score_codex":0.0035359734,"about_ca_topic_score_gemma":0.0044688405,"teacher_disagreement_score":0.04017836,"about_ca_system_score_codex":0.0017061105,"about_ca_system_score_gemma":0.0017557982,"threshold_uncertainty_score":0.13441002},"labels":[],"label_agreement":null},{"id":"W163770788","doi":"10.1007/978-3-642-33651-5_24","title":"Position Discovery for a System of Bouncing Robots","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Position (finance); Bang-bang robot; Mobile robot; Computer science; Point (geometry); Algorithm; Artificial intelligence; Computer vision; Robot control; Control theory (sociology); Mathematics; Control (management); Geometry","score_opus":0.022518641598899238,"score_gpt":0.2526001113165232,"score_spread":0.23008146971762397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W163770788","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.064122155,0.0005200835,0.9250274,0.0006181884,0.0000911202,0.00007657359,0.0001386394,0.00095200224,0.008453857],"genre_scores_gemma":[0.7144669,0.0004568372,0.26602033,0.00009689319,0.00007121824,0.00011101806,0.00026002098,0.000115920535,0.018400803],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99965465,0.00005108721,0.000028986533,0.000108947694,0.000098024175,0.000058243633],"domain_scores_gemma":[0.9992048,0.00045522203,0.0000714988,0.00008344241,0.00012111669,0.000063955806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006890778,0.0007252386,0.0011570101,0.0007234915,0.0017458585,0.0016175206,0.002016984,0.0025646482,0.006595518],"category_scores_gemma":[0.002818206,0.0007593774,0.0007286449,0.00084414874,0.0012430121,0.0017861988,0.0021284756,0.0012092821,0.0009539147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00088265014,0.00009471706,0.0020044653,0.00040896877,0.00009513458,0.00064464624,0.00051352073,0.7926477,0.014509141,0.067357644,0.002358722,0.118482724],"study_design_scores_gemma":[0.00004313749,0.00010034216,0.00028252686,0.00001392367,0.000025621226,0.00013343805,0.000045352797,0.9798663,0.0019223435,0.016361726,0.0011786125,0.000026604079],"about_ca_topic_score_codex":0.008264634,"about_ca_topic_score_gemma":0.0065286886,"teacher_disagreement_score":0.008264634,"about_ca_system_score_codex":0.00085283036,"about_ca_system_score_gemma":0.0010502512,"threshold_uncertainty_score":0.022064209},"labels":[],"label_agreement":null},{"id":"W1647172251","doi":"10.1109/icsmc.1999.812557","title":"A comparison of continuous and discretized pursuit learning schemes","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Indian Institute of Science","keywords":"Learning automata; Discretization; Computer science; Reinforcement learning; Automaton; Artificial intelligence; Action (physics); Class (philosophy); Term (time); Machine learning; Theoretical computer science; Mathematics","score_opus":0.02638279250675315,"score_gpt":0.31825700524902745,"score_spread":0.2918742127422743,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1647172251","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04204788,0.0014972915,0.94460976,0.0004520004,0.00008960441,0.00007720443,0.000066516746,0.00034884908,0.01081083],"genre_scores_gemma":[0.7509547,0.000999913,0.24328122,0.00012815386,0.00007430938,0.00013041329,0.000112381254,0.000057219357,0.004261769],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879384,0.00033207823,0.00007228978,0.00013794674,0.0005756948,0.00008817106],"domain_scores_gemma":[0.9965737,0.0019270347,0.00021099474,0.0007180709,0.00037990027,0.0001903675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016025244,0.00029206037,0.0005427537,0.00060336164,0.000356579,0.0013823004,0.0015669328,0.001033689,0.0031015908],"category_scores_gemma":[0.007259994,0.00020573025,0.00041109129,0.00079453277,0.0014755868,0.002056519,0.0015978446,0.0010121308,0.00036656947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036901166,0.00012018532,0.0011701108,0.00023719978,0.00005747164,0.000054967735,0.00022491725,0.4834713,0.0042364206,0.3113235,0.001649641,0.19708534],"study_design_scores_gemma":[0.000041379528,0.0001282671,0.00023543855,0.000019428258,0.00000833373,0.00004135767,0.00002398127,0.965202,0.0007890752,0.031878013,0.001620377,0.000012461601],"about_ca_topic_score_codex":0.0018080006,"about_ca_topic_score_gemma":0.0010272352,"teacher_disagreement_score":0.0031015908,"about_ca_system_score_codex":0.0011399096,"about_ca_system_score_gemma":0.0009887528,"threshold_uncertainty_score":0.010375857},"labels":[],"label_agreement":null},{"id":"W1655324574","doi":"10.1007/978-3-319-30139-6_6","title":"Optimal Distributed Searching in the Plane with and Without Uncertainty","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Visibility; Search and rescue; Drone; Robot; Task (project management); Plane (geometry); Artificial intelligence; Search problem; Algorithm; Mathematics","score_opus":0.017686002502897518,"score_gpt":0.2565475571251601,"score_spread":0.23886155462226258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1655324574","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032008663,0.0020871395,0.9476651,0.0007754362,0.00009992436,0.000027403332,0.000105277366,0.000112438654,0.017118594],"genre_scores_gemma":[0.7851818,0.0019476282,0.19846277,0.00018982733,0.00021928086,0.00015889901,0.00020942492,0.00017201313,0.013458284],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991716,0.00033905669,0.00003686749,0.00014775869,0.00021252366,0.000092167975],"domain_scores_gemma":[0.9978504,0.0016148072,0.00014080158,0.00015196054,0.00015264348,0.00008937433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014640439,0.00081789115,0.0017466173,0.00072264223,0.00042123467,0.0017084741,0.0013886039,0.00194907,0.0033902798],"category_scores_gemma":[0.0071208016,0.0005791909,0.00065398164,0.0014357168,0.0016071849,0.0026443177,0.00206962,0.0014829914,0.0003492338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027434406,0.000038811606,0.00011994582,0.00012388745,0.000030236426,0.00003766359,0.00005250494,0.7992036,0.0010006467,0.16794334,0.0018513643,0.029323654],"study_design_scores_gemma":[0.00003658447,0.00003464961,0.000057608668,0.000015806769,0.0000057101533,0.000022406035,0.000014352477,0.8778973,0.00018619961,0.12104622,0.00067503593,0.000008114604],"about_ca_topic_score_codex":0.0012666115,"about_ca_topic_score_gemma":0.00066482957,"teacher_disagreement_score":0.0033902798,"about_ca_system_score_codex":0.0011345446,"about_ca_system_score_gemma":0.0008033629,"threshold_uncertainty_score":0.011341631},"labels":[],"label_agreement":null},{"id":"W171011166","doi":"10.1007/978-3-642-27848-8_594-1","title":"Uniform Covering of Rings and Lines by Memoryless Mobile Sensors","year":2014,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science","score_opus":0.008348345353350049,"score_gpt":0.22546899510173013,"score_spread":0.21712064974838008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W171011166","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.080278054,0.002362796,0.89555156,0.00019134909,0.0001407647,0.000045017066,0.00031245028,0.0006252067,0.02049278],"genre_scores_gemma":[0.8247289,0.003624855,0.15007655,0.00012504478,0.0001716466,0.00013435692,0.00039914474,0.0001561467,0.020583356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99944824,0.00015074112,0.000025819478,0.00015285292,0.00012310268,0.000099231074],"domain_scores_gemma":[0.9992399,0.00030740147,0.0001472678,0.00020074294,0.00006199056,0.000042804764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002386409,0.0007877418,0.0007726034,0.00039433193,0.000384984,0.0010526933,0.0013362749,0.0006713322,0.0028361604],"category_scores_gemma":[0.0015209089,0.0004489607,0.0005631335,0.0007766041,0.0008856264,0.0020897246,0.001620289,0.0006520744,0.0007282294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083600864,0.00007925885,0.0008388438,0.0006602892,0.00010667082,0.00038712076,0.0003133351,0.39946747,0.04826527,0.35660946,0.008757948,0.1836784],"study_design_scores_gemma":[0.00006866178,0.00036644225,0.000678357,0.00006574586,0.000049838818,0.00063001545,0.000127597,0.7533848,0.029997217,0.19104306,0.023517378,0.00007081404],"about_ca_topic_score_codex":0.0005944361,"about_ca_topic_score_gemma":0.00041293883,"teacher_disagreement_score":0.0028361604,"about_ca_system_score_codex":0.00046692527,"about_ca_system_score_gemma":0.00023719094,"threshold_uncertainty_score":0.009487927},"labels":[],"label_agreement":null},{"id":"W1717727751","doi":"10.1016/j.dam.2015.07.036","title":"Contraction obstructions for connected graph searching","year":2015,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mitacs; University of British Columbia","funders":"European Social Fund; Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Mitacs","keywords":"Mathematics; Monotone polygon; Combinatorics; Connected component; Finite set; Bounded function; Discrete mathematics; Graph; Mixed graph; Strongly connected component; Induced subgraph; Contraction (grammar); Line graph; Voltage graph","score_opus":0.05334818489376948,"score_gpt":0.299537856910135,"score_spread":0.24618967201636555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1717727751","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14971142,0.0022568258,0.7692838,0.005740235,0.00049502344,0.00017991869,0.00045602393,0.0007603673,0.07111634],"genre_scores_gemma":[0.81480205,0.0015741985,0.14129554,0.0010429006,0.0005353433,0.0004859617,0.00056471204,0.0007122614,0.038986914],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986518,0.00055565714,0.000057531794,0.00021043252,0.00033086934,0.00019380887],"domain_scores_gemma":[0.9884039,0.008848316,0.0005439109,0.000731379,0.0004273664,0.0010451294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022905194,0.0009292003,0.0022025576,0.0021189132,0.002247086,0.0026231634,0.0026826207,0.0025478655,0.0124971885],"category_scores_gemma":[0.024028841,0.00086804386,0.0015019273,0.0023819017,0.0048026866,0.0060820743,0.005439711,0.005805669,0.00068174105],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007453344,0.00003327641,0.00016621345,0.00008810012,0.000012258786,0.000050055805,0.00013807401,0.017225863,0.00041630334,0.9718169,0.0027667142,0.0072117085],"study_design_scores_gemma":[0.000034369492,0.000019569368,0.000100705605,0.000019385401,0.000009340026,0.000038620845,0.000042867483,0.10004912,0.00016597912,0.89770144,0.0018073301,0.000011193065],"about_ca_topic_score_codex":0.0025775505,"about_ca_topic_score_gemma":0.0024836077,"teacher_disagreement_score":0.0124971885,"about_ca_system_score_codex":0.0018608937,"about_ca_system_score_gemma":0.0015739617,"threshold_uncertainty_score":0.041807234},"labels":[],"label_agreement":null},{"id":"W1725687346","doi":"10.1007/s00453-011-9542-1","title":"Layered Working-Set Trees","year":2011,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Binary search tree; Binary tree; Combinatorics; Element (criminal law); Mathematics; Upper and lower bounds; Amortized analysis; Multiplicative function; Theory of computation; Set (abstract data type); Ternary search tree; Tree (set theory); Search tree; Binary number; Data structure; Discrete mathematics; Logarithm; Computer science; Search algorithm; Algorithm; Tree structure; Interval tree; Arithmetic","score_opus":0.0813956022466798,"score_gpt":0.2568467713904636,"score_spread":0.17545116914378378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1725687346","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032156143,0.0007634385,0.9427376,0.00090023957,0.00010409656,0.00007143734,0.00061533967,0.00094885286,0.02170296],"genre_scores_gemma":[0.38441303,0.0011033232,0.5765502,0.00045193319,0.00020456445,0.00034560854,0.002182765,0.00081917446,0.033929475],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99882966,0.0003278595,0.000074393734,0.00019640912,0.00038042563,0.00019120102],"domain_scores_gemma":[0.99571544,0.001974912,0.00019530105,0.0013472611,0.00041048645,0.00035668138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017911172,0.00076616026,0.0014079623,0.0014949085,0.0014688616,0.0042063184,0.0026184455,0.0018509896,0.017179817],"category_scores_gemma":[0.01138822,0.0009452277,0.00162983,0.0022308645,0.0015764897,0.007137097,0.0041370355,0.0039773346,0.004012227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013482527,0.0001097921,0.00093141105,0.00015113658,0.00006400826,0.00010249142,0.00023886624,0.044969603,0.0018979441,0.8133235,0.012221435,0.12585504],"study_design_scores_gemma":[0.00001793285,0.000030790623,0.00019657431,0.00003726092,0.000030336307,0.00012108132,0.00004713713,0.14408475,0.0011086438,0.84638757,0.007924133,0.000013822429],"about_ca_topic_score_codex":0.0007493118,"about_ca_topic_score_gemma":0.0014015103,"teacher_disagreement_score":0.017179817,"about_ca_system_score_codex":0.0010600716,"about_ca_system_score_gemma":0.001084794,"threshold_uncertainty_score":0.05747223},"labels":[],"label_agreement":null},{"id":"W1729082581","doi":"10.1023/a:1022985808959","title":"Tight Bounds on the Competitive Ratio on Accommodating Sequences for the Seat Reservation Problem","year":2003,"lang":"en","type":"article","venue":"Journal of Scheduling","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science","score_opus":0.06805300057024483,"score_gpt":0.3062754475526015,"score_spread":0.23822244698235667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1729082581","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27503756,0.013015085,0.54721016,0.008221693,0.001243607,0.000715206,0.0023451047,0.0016518151,0.15055977],"genre_scores_gemma":[0.83762205,0.0076743434,0.13184294,0.0019501265,0.0017712933,0.0008330075,0.0017651502,0.0010111823,0.015529981],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9920718,0.002976337,0.0002391507,0.0006178263,0.0021168988,0.0019779275],"domain_scores_gemma":[0.93409526,0.05637984,0.002032271,0.0019508164,0.0025658088,0.002975999],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010094541,0.004593094,0.0060675154,0.0036672137,0.002723819,0.0075936127,0.006481047,0.004262837,0.018848745],"category_scores_gemma":[0.05372881,0.0020714074,0.0021550644,0.0054553435,0.0030784574,0.008603452,0.0041204584,0.0084842965,0.0025679497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004284109,0.0013567775,0.001985692,0.0012805964,0.00028854556,0.0003380597,0.0005415043,0.5424319,0.009144973,0.32260385,0.025668956,0.090075076],"study_design_scores_gemma":[0.00020589324,0.00049988064,0.00057320995,0.0001299619,0.00009374169,0.00024754027,0.00016312834,0.8067396,0.0013853603,0.18666372,0.0032394642,0.00005844751],"about_ca_topic_score_codex":0.004699998,"about_ca_topic_score_gemma":0.0044021145,"teacher_disagreement_score":0.018848745,"about_ca_system_score_codex":0.004434586,"about_ca_system_score_gemma":0.005050736,"threshold_uncertainty_score":0.06305534},"labels":[],"label_agreement":null},{"id":"W174485529","doi":"10.1007/978-3-642-38016-7_13","title":"Minimizing Cache Usage in Paging","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paging; Computer science; Cache; Cache algorithms; Competitive analysis; Page cache; Smart Cache; Cache invalidation; Cache-oblivious algorithm; Cache coloring; CPU cache; Parallel computing; Cache pollution; Online algorithm; Algorithm; Computer network; Upper and lower bounds; Mathematics","score_opus":0.027506684045857103,"score_gpt":0.2567483282238566,"score_spread":0.22924164417799953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W174485529","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20194973,0.009596265,0.7477758,0.0011608631,0.00053845136,0.00025456818,0.0006474777,0.0038084092,0.034268487],"genre_scores_gemma":[0.815641,0.0028644346,0.16522034,0.00017426028,0.00025773852,0.00014767023,0.00038871804,0.0007900808,0.0145158265],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989542,0.00029341408,0.00006500677,0.00013887156,0.0002806283,0.00026786423],"domain_scores_gemma":[0.9976732,0.0010584563,0.00017639094,0.0006122794,0.0003448252,0.0001349473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008466597,0.0013881386,0.0019155227,0.00093885005,0.0007864183,0.0022983043,0.0023311777,0.001164839,0.004510692],"category_scores_gemma":[0.005657201,0.0007473051,0.0005206954,0.003393781,0.00066592917,0.0027554964,0.001179825,0.0012413149,0.00089792523],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007679644,0.00027622894,0.0019216209,0.00068083766,0.00010829171,0.00025403668,0.00020960858,0.52733254,0.014909195,0.054425165,0.01920188,0.37991267],"study_design_scores_gemma":[0.00004389945,0.0002594311,0.000808777,0.00009148453,0.00011749883,0.00044561113,0.00012266594,0.9278124,0.0067072,0.05628456,0.007277924,0.000028505308],"about_ca_topic_score_codex":0.0020456442,"about_ca_topic_score_gemma":0.0026475426,"teacher_disagreement_score":0.004510692,"about_ca_system_score_codex":0.0013707587,"about_ca_system_score_gemma":0.0013610778,"threshold_uncertainty_score":0.01508981},"labels":[],"label_agreement":null},{"id":"W1751505773","doi":"10.1023/a:1011219024159","title":"Collaborative Robot Exploration and Rendezvous: Algorithms, Performance Bounds and Observations","year":2001,"lang":"en","type":"article","venue":"Autonomous Robots","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":145,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Rendezvous; Computer science; Robot; Set (abstract data type); Constraint (computer-aided design); Distributed computing; Artificial intelligence; Human–computer interaction; Mathematics","score_opus":0.03879281381989205,"score_gpt":0.2616732478660249,"score_spread":0.22288043404613286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1751505773","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012035563,0.0027931863,0.9814798,0.00032949777,0.000049722938,0.00003442992,0.00006514842,0.00035911132,0.0028535174],"genre_scores_gemma":[0.7885866,0.004359784,0.19858642,0.00013248711,0.0004420383,0.00044189248,0.00037339196,0.00037295953,0.0067043565],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99698985,0.0008998564,0.00010185478,0.0006092732,0.0010992556,0.00029984242],"domain_scores_gemma":[0.9823262,0.012995226,0.0014808872,0.0017951251,0.0010731425,0.00032940708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003454835,0.0026358513,0.0030867953,0.0012242753,0.001221798,0.00364109,0.004019213,0.0035512906,0.0026185403],"category_scores_gemma":[0.02123289,0.0014747657,0.0008575329,0.0025751535,0.0038699294,0.006409482,0.005255879,0.0040640845,0.0008478295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005223101,0.00011984215,0.0008535293,0.00038313004,0.00008720848,0.000072881114,0.00018751928,0.8079648,0.002315256,0.09943136,0.0033482404,0.08471398],"study_design_scores_gemma":[0.000027607883,0.000045398483,0.00023397135,0.000031560114,0.000018173574,0.000042064807,0.000032567965,0.933587,0.0014541764,0.063583165,0.00092246436,0.000021859658],"about_ca_topic_score_codex":0.0046171793,"about_ca_topic_score_gemma":0.0028057965,"teacher_disagreement_score":0.0046171793,"about_ca_system_score_codex":0.0018594665,"about_ca_system_score_gemma":0.0015085255,"threshold_uncertainty_score":0.018271148},"labels":[],"label_agreement":null},{"id":"W1759574848","doi":"10.1007/978-3-642-31104-8_25","title":"Time of Anonymous Rendezvous in Trees: Determinism vs. Randomization","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Bounded function; Computer science; Node (physics); Tree (set theory); Upper and lower bounds; Randomized algorithm; Degree (music); Constant (computer programming); Tree traversal; Time complexity; Algorithm; Deterministic algorithm; Combinatorics; Mathematics","score_opus":0.015361322825506415,"score_gpt":0.24348352680076954,"score_spread":0.22812220397526312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1759574848","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26613104,0.0035056872,0.65732336,0.005683139,0.0007324308,0.00022263036,0.0013744019,0.0026009392,0.0624264],"genre_scores_gemma":[0.93886733,0.0009643112,0.041309703,0.00034375166,0.0005194543,0.00023091493,0.00048721486,0.00095047924,0.016326824],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99447244,0.0017143117,0.0003229387,0.0013637888,0.0010664182,0.001060161],"domain_scores_gemma":[0.96186835,0.027208483,0.002104344,0.005929858,0.0013129732,0.0015759923],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048546316,0.00076588977,0.0020480666,0.0013200991,0.00254704,0.0055954037,0.0030732858,0.0021619217,0.012245808],"category_scores_gemma":[0.033784658,0.0011194758,0.0017484857,0.0017256868,0.0039878534,0.013125001,0.003320109,0.0039913454,0.0013335675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009069118,0.000058273887,0.000844914,0.00023228204,0.00008134255,0.00011307303,0.00046200858,0.053364426,0.002173539,0.9134886,0.0056132115,0.022661421],"study_design_scores_gemma":[0.000083533545,0.000070388196,0.00026134163,0.0000413839,0.000051465242,0.000115102936,0.00009071511,0.117162965,0.0015246976,0.8778387,0.0027185106,0.00004115704],"about_ca_topic_score_codex":0.0017335562,"about_ca_topic_score_gemma":0.0017851526,"teacher_disagreement_score":0.012245808,"about_ca_system_score_codex":0.002750965,"about_ca_system_score_gemma":0.0030459461,"threshold_uncertainty_score":0.040966272},"labels":[],"label_agreement":null},{"id":"W1766799846","doi":"10.23638/dmtcs-22-4-4","title":"Evacuating Robots from a Disk Using Face-to-Face Communication","year":2020,"lang":"en","type":"preprint","venue":"Discrete Mathematics & Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Unit disk; Approx; Upper and lower bounds; Face (sociological concept); Boundary (topology); Computer science; Unit (ring theory); Algorithm; Combinatorics; Mathematics; Artificial intelligence; Mathematical analysis; Operating system","score_opus":0.055592122959191664,"score_gpt":0.3286861245468449,"score_spread":0.2730940015876533,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1766799846","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11419894,0.00054277445,0.8544178,0.003494052,0.0002525101,0.00029294507,0.00036661953,0.002726493,0.023707962],"genre_scores_gemma":[0.51587325,0.00040090873,0.46923578,0.00068719126,0.00005913962,0.00025152322,0.00058162864,0.0002560671,0.0126545215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990953,0.00021709612,0.000052324354,0.00023646471,0.00022389118,0.00017498915],"domain_scores_gemma":[0.9974879,0.001255122,0.00021921397,0.0006286869,0.00025383543,0.00015508468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085762155,0.0009450178,0.0008479951,0.00043480002,0.0014622778,0.0009446038,0.0029232732,0.0019917437,0.007655576],"category_scores_gemma":[0.00506429,0.0003972402,0.00086393906,0.00056096946,0.0013949071,0.0032607676,0.0032526597,0.0019370025,0.002881036],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030436928,0.00034790608,0.0045973863,0.001370149,0.00013576448,0.0017169645,0.0020651307,0.5317238,0.036643907,0.12884903,0.042817675,0.24668866],"study_design_scores_gemma":[0.00021491709,0.00048141467,0.0012384799,0.00013287285,0.000046644578,0.0012366257,0.001300269,0.8405063,0.053398322,0.06584866,0.03548817,0.00010727706],"about_ca_topic_score_codex":0.002655329,"about_ca_topic_score_gemma":0.0037337008,"teacher_disagreement_score":0.007655576,"about_ca_system_score_codex":0.00092139153,"about_ca_system_score_gemma":0.0008191948,"threshold_uncertainty_score":0.025610507},"labels":[],"label_agreement":null},{"id":"W1779195044","doi":"10.1007/978-3-662-46078-8_23","title":"Efficient Online Strategies for Renting Servers in the Cloud","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Server; Cloud computing; Renting; Database; Operating system","score_opus":0.05569048927228374,"score_gpt":0.3030071800178352,"score_spread":0.2473166907455515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1779195044","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09967973,0.0025870565,0.8584384,0.0012914975,0.00029204032,0.00059216085,0.0006118297,0.0012783344,0.035228994],"genre_scores_gemma":[0.7350367,0.0013230891,0.24613687,0.00013839387,0.0001685075,0.0002551209,0.0004056442,0.00035855,0.016177164],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987141,0.00036932883,0.00006571887,0.00017022817,0.00027101708,0.00040962265],"domain_scores_gemma":[0.99805814,0.001159248,0.00010162299,0.00033141204,0.00015830042,0.00019122413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011169305,0.0014791059,0.002965952,0.0008882542,0.0013406223,0.0036252248,0.0040311604,0.0021520997,0.01679766],"category_scores_gemma":[0.005028015,0.0010209267,0.0011799308,0.0021880558,0.0008629699,0.0051892796,0.0024714896,0.0017647864,0.0022538002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001250534,0.00081734674,0.0011511322,0.0005935446,0.00013245323,0.00030414795,0.00026193936,0.50312394,0.011041738,0.1864837,0.03307878,0.26176077],"study_design_scores_gemma":[0.000070514005,0.000086757456,0.00019033064,0.0000261574,0.00003190192,0.0001351581,0.00011589253,0.9377499,0.0013912921,0.057650287,0.002531041,0.00002063618],"about_ca_topic_score_codex":0.0039990833,"about_ca_topic_score_gemma":0.0055395863,"teacher_disagreement_score":0.01679766,"about_ca_system_score_codex":0.0019646876,"about_ca_system_score_gemma":0.002329033,"threshold_uncertainty_score":0.05619377},"labels":[],"label_agreement":null},{"id":"W1784211297","doi":"10.1007/11604655_17","title":"Cleaning an Arbitrary Regular Network with Mobile Agents","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Graph; Relation (database); Mobile agent; Task (project management); Mobile genetic elements; Theoretical computer science; Distributed computing; Data mining","score_opus":0.018198049037657742,"score_gpt":0.2504142197784038,"score_spread":0.23221617074074605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1784211297","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.092624344,0.00029401248,0.89562696,0.00066915556,0.00020901182,0.00014432472,0.00028665527,0.00095107267,0.009194474],"genre_scores_gemma":[0.51283437,0.0005424219,0.458923,0.00022012451,0.00017099644,0.0002076976,0.00070634723,0.00044917862,0.025945915],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99900657,0.00022741561,0.000055421177,0.00033987194,0.00019828601,0.00017254105],"domain_scores_gemma":[0.9977513,0.00084818795,0.0001876036,0.0008556968,0.00019090279,0.00016639076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010545739,0.00074237207,0.0013139959,0.00079458085,0.0014469946,0.0014707666,0.0025713218,0.0016931221,0.004088654],"category_scores_gemma":[0.0057044923,0.00071119,0.0011369236,0.0010493431,0.0012777774,0.003404196,0.003135645,0.0015078887,0.00085448474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010565895,0.00020281292,0.001684802,0.0004010717,0.00015661321,0.0008490725,0.00030040974,0.7076098,0.016318971,0.14897747,0.01034941,0.11209299],"study_design_scores_gemma":[0.000045569333,0.00010406761,0.0002414861,0.00002037095,0.000038740345,0.00021717201,0.00010238952,0.88560075,0.004746206,0.10217359,0.006690454,0.000019248955],"about_ca_topic_score_codex":0.0015961636,"about_ca_topic_score_gemma":0.0015467015,"teacher_disagreement_score":0.004088654,"about_ca_system_score_codex":0.00058163994,"about_ca_system_score_gemma":0.00063493283,"threshold_uncertainty_score":0.013677835},"labels":[],"label_agreement":null},{"id":"W1793615280","doi":"10.1007/s00453-016-0224-x","title":"The Power and Limitations of Static Binary Search Trees with Lazy Finger","year":2016,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Division of Computing and Communication Foundations; Center for Massive Data Algorithmics; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Fonds De La Recherche Scientifique - FNRS","keywords":"Optimal binary search tree; Binary search tree; Binary tree; Random binary tree; Theory of computation; Mathematics; Tree (set theory); Self-balancing binary search tree; Search tree; Computer science; Algorithm; Entropy (arrow of time); Dynamic programming; Ternary search tree; K-ary tree; Combinatorics; Tree structure; Interval tree; Search algorithm","score_opus":0.030737890943844638,"score_gpt":0.25304085483676614,"score_spread":0.2223029638929215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1793615280","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0819635,0.010216479,0.85609484,0.0040536295,0.00031396138,0.00008352415,0.0001616706,0.0021123914,0.045000035],"genre_scores_gemma":[0.74282575,0.004849875,0.23969,0.0007314979,0.00043010846,0.00015895456,0.00014648384,0.0008472557,0.010320049],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9951834,0.0019928897,0.0002691809,0.0005426693,0.0015946364,0.00041711854],"domain_scores_gemma":[0.97597164,0.0171989,0.00064600765,0.0048698154,0.00095895235,0.00035469024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077732475,0.00061014236,0.0018068271,0.001763992,0.0018277793,0.0043855645,0.0030127128,0.0022781715,0.006920649],"category_scores_gemma":[0.03532615,0.0011149272,0.001017546,0.0032153316,0.005807698,0.01613967,0.0041001085,0.0031254396,0.0020586436],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005053002,0.00013018149,0.0016807956,0.00031079067,0.000062335006,0.00011033345,0.0004089841,0.10229224,0.0018081659,0.6408342,0.0054297852,0.24642694],"study_design_scores_gemma":[0.00007333488,0.00010220873,0.0002157223,0.00010707011,0.00006119206,0.00017843633,0.00009081465,0.32295892,0.0020579372,0.6660079,0.008100422,0.000046073077],"about_ca_topic_score_codex":0.0021333355,"about_ca_topic_score_gemma":0.002333942,"teacher_disagreement_score":0.0077732475,"about_ca_system_score_codex":0.0012983438,"about_ca_system_score_gemma":0.0019617623,"threshold_uncertainty_score":0.041109383},"labels":[],"label_agreement":null},{"id":"W1801923375","doi":"10.1007/978-0-387-34735-6_5","title":"Distributed Algorithms for Autonomous Mobile Robots","year":2006,"lang":"en","type":"book-chapter","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Mobile robot; Robot; Robotics; Computer science; Artificial intelligence; Focus (optics); Variety (cybernetics); Set (abstract data type); Task (project management); Computability; Distributed computing; Human–computer interaction; Point (geometry); Algorithm; Engineering; Mathematics; Systems engineering","score_opus":0.029647890575216617,"score_gpt":0.2671263455842537,"score_spread":0.23747845500903708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1801923375","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0027579041,0.03274965,0.90792435,0.002790862,0.0009823252,0.000108311484,0.0001393555,0.0006495863,0.0518976],"genre_scores_gemma":[0.2466332,0.041638356,0.62379205,0.0016997766,0.002234769,0.0014671474,0.000899811,0.00051920384,0.08111563],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993075,0.00022272748,0.000033825334,0.00010526411,0.00028219694,0.000048448303],"domain_scores_gemma":[0.99947447,0.0003169928,0.000027813938,0.00007316084,0.000085087355,0.000022564142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072772196,0.0011251235,0.0008489414,0.00060032064,0.00046924746,0.0016242231,0.0014179609,0.0014565574,0.00636181],"category_scores_gemma":[0.002984822,0.00034630692,0.00037532442,0.0013967109,0.0012099671,0.0017442105,0.0016077559,0.0024703955,0.0025115316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026974023,0.000036017453,0.00014823113,0.00031465816,0.000038232265,0.00007421745,0.00017103933,0.067970745,0.00073331076,0.7595937,0.032668795,0.13822402],"study_design_scores_gemma":[0.000050326948,0.000027606204,0.00010612941,0.00007844523,0.0000111764775,0.00009673205,0.00005107012,0.16451988,0.00026433865,0.7187455,0.11603758,0.000011219964],"about_ca_topic_score_codex":0.0013878313,"about_ca_topic_score_gemma":0.0009911532,"teacher_disagreement_score":0.00636181,"about_ca_system_score_codex":0.0013543862,"about_ca_system_score_gemma":0.00083505886,"threshold_uncertainty_score":0.021282375},"labels":[],"label_agreement":null},{"id":"W1802748673","doi":"10.1016/j.tcs.2015.09.018","title":"Autonomous mobile robots with lights","year":2015,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":145,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dell’Istruzione, dell’Università e della Ricerca; Ministry of Education, Culture, Sports, Science and Technology; Agence Nationale de la Recherche","keywords":"Asynchronous communication; Robot; Computer science; Mobile robot; Distributed computing; Artificial intelligence","score_opus":0.016159626412135412,"score_gpt":0.2576801945142401,"score_spread":0.2415205681021047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1802748673","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13336013,0.0012926873,0.80979306,0.0010095721,0.0004949393,0.00007541559,0.00013969086,0.0011859238,0.05264858],"genre_scores_gemma":[0.8973924,0.0006000262,0.07558684,0.00023047367,0.00010799086,0.000087102664,0.000085854794,0.00011679224,0.025792621],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998355,0.000035377245,0.0000041525177,0.00004177484,0.00005677375,0.000026369635],"domain_scores_gemma":[0.9997743,0.000087951514,0.000026829937,0.000035494704,0.00003383371,0.000041600222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014606188,0.00033565,0.00040458867,0.00033042353,0.000653077,0.0008827308,0.00057817216,0.0007018155,0.004169195],"category_scores_gemma":[0.0007058558,0.00031808688,0.00039464128,0.00030643205,0.0008744968,0.001177617,0.0019289955,0.0008138038,0.000848605],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007468097,0.00016630125,0.0018415168,0.0003963845,0.000083493636,0.00045581526,0.0004342249,0.26743641,0.07333029,0.4053531,0.01098801,0.23876765],"study_design_scores_gemma":[0.00008610415,0.0002557535,0.0007175678,0.000032410822,0.000033164968,0.00019527298,0.00017449007,0.72738576,0.0100647425,0.23594378,0.025063112,0.00004783067],"about_ca_topic_score_codex":0.00082126143,"about_ca_topic_score_gemma":0.0008590385,"teacher_disagreement_score":0.004169195,"about_ca_system_score_codex":0.00032076184,"about_ca_system_score_gemma":0.0003035557,"threshold_uncertainty_score":0.013947368},"labels":[],"label_agreement":null},{"id":"W1803135286","doi":"10.1016/j.ic.2016.06.007","title":"On the list update problem with advice","year":2016,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Villum Fonden","keywords":"Advice (programming); Computer science; Information retrieval; Programming language","score_opus":0.0087912005124182,"score_gpt":0.2228605443273354,"score_spread":0.2140693438149172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1803135286","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09645324,0.0038978076,0.84537697,0.012928919,0.0005552114,0.00025202765,0.0008519402,0.0011208741,0.038563043],"genre_scores_gemma":[0.57317185,0.0026964687,0.36594856,0.0018537791,0.0012813888,0.0003904994,0.0015656955,0.0009162216,0.05217557],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99787927,0.0008206102,0.00010513873,0.00035225778,0.00050450565,0.00033820324],"domain_scores_gemma":[0.9803812,0.016607834,0.00050149375,0.001043151,0.00092342106,0.00054300664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032799323,0.0011248956,0.0026671307,0.0015840206,0.001727199,0.003218284,0.0030180742,0.0047779335,0.015302625],"category_scores_gemma":[0.03166251,0.0009050593,0.00096450397,0.003174733,0.0028390733,0.008724076,0.00305159,0.0038421534,0.0012781],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012697941,0.00047430774,0.002091864,0.00062805606,0.000120364675,0.00030408715,0.0005532758,0.21695961,0.0009304774,0.55412793,0.052066058,0.17047419],"study_design_scores_gemma":[0.00015962482,0.000052870306,0.0002510729,0.00005553346,0.00004083713,0.00006339544,0.00006416928,0.48738086,0.00032098015,0.5083214,0.003269065,0.00002027245],"about_ca_topic_score_codex":0.010017944,"about_ca_topic_score_gemma":0.009678677,"teacher_disagreement_score":0.015302625,"about_ca_system_score_codex":0.0020455741,"about_ca_system_score_gemma":0.0024207502,"threshold_uncertainty_score":0.051192403},"labels":[],"label_agreement":null},{"id":"W181500213","doi":"10.1007/978-3-319-14472-6_18","title":"Tradeoffs between Cost and Information for Rendezvous and Treasure Hunt","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Treasure; Rendezvous; Computer science; Node (physics); Oracle; Traverse; Network topology; Computer network; Theoretical computer science; Topology (electrical circuits); Mathematics; Combinatorics; Geography","score_opus":0.02409095994760135,"score_gpt":0.25103313663737603,"score_spread":0.22694217668977468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W181500213","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39051035,0.008929308,0.4243317,0.0035633787,0.00037220318,0.00016344745,0.0006858666,0.0016074884,0.16983621],"genre_scores_gemma":[0.96046764,0.0010673353,0.028152937,0.00008157665,0.00009372542,0.000036834757,0.00015626125,0.00023033429,0.009713353],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99833655,0.00049284624,0.00006046756,0.00020700417,0.0005540596,0.0003489977],"domain_scores_gemma":[0.98301125,0.014055016,0.00048447278,0.0013834897,0.0006769712,0.0003888837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023064164,0.0008564648,0.001503978,0.0014903871,0.0008718947,0.0034701333,0.002503955,0.0023109897,0.018435717],"category_scores_gemma":[0.022354884,0.0006942409,0.00067771494,0.0014386907,0.0017645672,0.0075214617,0.0024159877,0.0015824444,0.0016309262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036858749,0.00027342862,0.0023874105,0.000664042,0.00015553946,0.00039571486,0.00037705127,0.3259463,0.01753339,0.41329676,0.0062644454,0.22902009],"study_design_scores_gemma":[0.00016599336,0.00042244748,0.002239932,0.00012618731,0.00014292666,0.00075667887,0.0004331007,0.6482343,0.007504228,0.3350454,0.004808189,0.000120691475],"about_ca_topic_score_codex":0.0015695653,"about_ca_topic_score_gemma":0.0021019932,"teacher_disagreement_score":0.018435717,"about_ca_system_score_codex":0.0012695579,"about_ca_system_score_gemma":0.0007960333,"threshold_uncertainty_score":0.06167364},"labels":[],"label_agreement":null},{"id":"W1853304843","doi":"10.1007/s10107-016-1079-2","title":"Tight MIP formulations for bounded up/down times and interval-dependent start-ups","year":2016,"lang":"en","type":"article","venue":"Mathematical Programming","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Mathematics; Bounded function; Interval (graph theory); Integer programming; Convex hull; Quadratic programming; Linear programming; Upper and lower bounds; Integer (computer science); Mathematical optimization; Combinatorics; Discrete mathematics; Regular polygon; Computer science","score_opus":0.03800690496063752,"score_gpt":0.2958300606662771,"score_spread":0.2578231557056396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1853304843","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011454449,0.0018704134,0.97093505,0.0010775148,0.0002530098,0.00021127086,0.0007543019,0.0005491657,0.012894823],"genre_scores_gemma":[0.4884538,0.003415828,0.4857958,0.0011516822,0.0008350555,0.0011477219,0.0015008824,0.0011754609,0.016523782],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99556583,0.0012757734,0.00023540431,0.00076458085,0.0010003056,0.0011580146],"domain_scores_gemma":[0.9886951,0.008040808,0.00089527393,0.00073518185,0.00097154843,0.000662102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063989195,0.0039241225,0.0043594423,0.0017855987,0.0011781063,0.006036074,0.004891901,0.0038626574,0.015282138],"category_scores_gemma":[0.023252526,0.0025827142,0.0031656795,0.0032921797,0.0019206017,0.006332164,0.0032694219,0.00818796,0.0016817158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031254132,0.00020508577,0.0002779543,0.00062863197,0.00009224997,0.00014079822,0.00014477277,0.8814324,0.0016312479,0.080868654,0.0071802773,0.027085384],"study_design_scores_gemma":[0.000033701835,0.00006488317,0.00013114775,0.00007346388,0.00004444317,0.00004306639,0.000050507024,0.95455635,0.00050459936,0.043217875,0.0012615501,0.000018383424],"about_ca_topic_score_codex":0.004451157,"about_ca_topic_score_gemma":0.004331475,"teacher_disagreement_score":0.015282138,"about_ca_system_score_codex":0.0036622225,"about_ca_system_score_gemma":0.003953516,"threshold_uncertainty_score":0.051123798},"labels":[],"label_agreement":null},{"id":"W1854056485","doi":"10.1109/istcs.1993.253458","title":"The mortgage problem","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Competitive analysis; Line (geometry); Interest rate; Sequence (biology); Database transaction; Economics; Computer science; Upper and lower bounds; Mathematical economics; Actuarial science; Monetary economics; Mathematics; Chemistry; Database; Mathematical analysis","score_opus":0.027863168969227123,"score_gpt":0.22907029774901336,"score_spread":0.20120712877978625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1854056485","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16132508,0.007908546,0.5780146,0.015151663,0.00078871095,0.00088741456,0.0054941284,0.00065196835,0.22977784],"genre_scores_gemma":[0.7736704,0.004808636,0.14299215,0.0012840198,0.0007935638,0.0007031316,0.0037559571,0.00027759038,0.07171458],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99800605,0.00088318594,0.00009595522,0.00044138983,0.00028313216,0.0002901717],"domain_scores_gemma":[0.9977552,0.0015922085,0.00021007404,0.000103478764,0.00014735403,0.0001917094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015840982,0.0012706395,0.001840066,0.0005996473,0.0011337061,0.003518714,0.0016204418,0.0040701455,0.026610197],"category_scores_gemma":[0.005425374,0.00055747986,0.00093265466,0.0011305544,0.0014178305,0.0047656777,0.0018606252,0.002737973,0.0022885108],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045881615,0.0003337139,0.0016335483,0.00060964626,0.0001792907,0.0005726174,0.00022071185,0.19121285,0.0010577705,0.6957007,0.042639412,0.06538096],"study_design_scores_gemma":[0.00027822918,0.0002875095,0.00086413196,0.000105642626,0.000064900196,0.000508462,0.0003249606,0.39756292,0.00094436936,0.53964394,0.059369203,0.000045751047],"about_ca_topic_score_codex":0.002958173,"about_ca_topic_score_gemma":0.0021088487,"teacher_disagreement_score":0.026610197,"about_ca_system_score_codex":0.0016000789,"about_ca_system_score_gemma":0.0015462185,"threshold_uncertainty_score":0.089019954},"labels":[],"label_agreement":null},{"id":"W1869091735","doi":"","title":"Sequential and parallel algorithms for frontier A* with delayed duplicate detection","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Workload; Computer science; Workstation; Sequence (biology); Parallel computing; Algorithm; Cluster (spacecraft); Real-time computing; Operating system","score_opus":0.01717291195064878,"score_gpt":0.24477512865869927,"score_spread":0.22760221670805048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1869091735","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005843085,0.0001866313,0.9900012,0.00011596105,0.00005376591,0.00008621933,0.00006460406,0.0014122644,0.0022363486],"genre_scores_gemma":[0.064784534,0.0001187473,0.9325306,0.000055222044,0.00004214145,0.0002411664,0.00017703863,0.00016286838,0.0018876287],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99857605,0.0002849663,0.0001500423,0.00029870254,0.0005215449,0.0001687716],"domain_scores_gemma":[0.9970847,0.0012189901,0.00027573714,0.00067965075,0.0006165117,0.00012439782],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016300038,0.0011643752,0.0009900847,0.0017918326,0.0010793585,0.00127943,0.0020570515,0.0009392916,0.0046432386],"category_scores_gemma":[0.0052522602,0.00063333847,0.0011971268,0.0022699276,0.00083259185,0.0020299803,0.0021311855,0.0013964196,0.0014609783],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029951116,0.00029452142,0.0011979864,0.00028675492,0.00007737743,0.000112140835,0.00014820826,0.30175847,0.00836364,0.05144156,0.0077754064,0.62824446],"study_design_scores_gemma":[0.00009624091,0.0001375618,0.00029900306,0.00001956049,0.000026913174,0.00019026229,0.000055729826,0.92533964,0.007287759,0.05674406,0.009771585,0.000031653453],"about_ca_topic_score_codex":0.0041754935,"about_ca_topic_score_gemma":0.004215302,"teacher_disagreement_score":0.0046432386,"about_ca_system_score_codex":0.0010415214,"about_ca_system_score_gemma":0.0021360058,"threshold_uncertainty_score":0.015533149},"labels":[],"label_agreement":null},{"id":"W1871770614","doi":"10.1109/icsmc.1992.271804","title":"SEATER: a simulation environment using learning automata for telephone traffic routing","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Learning automata; Static routing; Routing (electronic design automation); Computer network; Equal-cost multi-path routing; Policy-based routing; Multipath routing; Distributed computing; Destination-Sequenced Distance Vector routing; Link-state routing protocol; Automaton; Dynamic Source Routing; Routing table; Cellular automaton; Telephone network; Routing protocol; Theoretical computer science; Algorithm","score_opus":0.04309256960504478,"score_gpt":0.283781803838169,"score_spread":0.2406892342331242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1871770614","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012653876,0.00015607169,0.9151459,0.00023929862,0.00014544929,0.0003024594,0.0015513762,0.0603696,0.009435961],"genre_scores_gemma":[0.1877711,0.00063347013,0.7854783,0.00035365668,0.00007343839,0.0022811212,0.0036316484,0.006192492,0.013584769],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992581,0.00031640084,0.000073824005,0.00011404071,0.00017754406,0.000060152346],"domain_scores_gemma":[0.9983608,0.0011997095,0.00007155936,0.00015423515,0.00012152545,0.00009221727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012384433,0.0009899357,0.0011164837,0.0006616029,0.00052076415,0.001324314,0.0025254162,0.0014280615,0.022178074],"category_scores_gemma":[0.004011154,0.0010231945,0.0009609569,0.00058291864,0.00068116526,0.0018289448,0.0017406266,0.0019197764,0.0031329887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000775926,0.00032229643,0.0013253416,0.00041864073,0.00015689,0.00033679174,0.00038808768,0.8327402,0.009428414,0.05130484,0.030226592,0.07257597],"study_design_scores_gemma":[0.00014151006,0.000059539758,0.0000863718,0.000019967358,0.000020042506,0.000032977357,0.000010811297,0.97146386,0.003285744,0.007162831,0.017688926,0.000027370257],"about_ca_topic_score_codex":0.0028420098,"about_ca_topic_score_gemma":0.0027628187,"teacher_disagreement_score":0.022178074,"about_ca_system_score_codex":0.0006127143,"about_ca_system_score_gemma":0.00091052573,"threshold_uncertainty_score":0.07419306},"labels":[],"label_agreement":null},{"id":"W1875516392","doi":"10.14778/2752939.2752950","title":"Viral marketing meets social advertising","year":2015,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Viral marketing; Leverage (statistics); Click-through rate; Computer science; Advertising; Online advertising; Regret; Context (archaeology); Host (biology); Social network (sociolinguistics); Social media; Display advertising; Business; World Wide Web; The Internet; Artificial intelligence","score_opus":0.025921147798563318,"score_gpt":0.25511025738176607,"score_spread":0.22918910958320277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1875516392","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03559246,0.0062463954,0.83401126,0.016080882,0.0010260851,0.00076569844,0.0012565725,0.0011020191,0.10391862],"genre_scores_gemma":[0.7498981,0.007162332,0.1862942,0.0036437411,0.0034534868,0.0009976227,0.0010617796,0.0006606945,0.046828035],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99545324,0.0019848815,0.00015864994,0.0010053682,0.00080134603,0.0005965238],"domain_scores_gemma":[0.9853967,0.011344717,0.00082288566,0.0010180809,0.000709547,0.0007081963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035474033,0.0032623222,0.003941571,0.0011312832,0.0021111097,0.0071483566,0.002689214,0.006686685,0.022976922],"category_scores_gemma":[0.018014919,0.0012841155,0.0016395248,0.00206267,0.0027156956,0.008650465,0.0032737292,0.007013941,0.004527421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039887056,0.0004955638,0.0010348056,0.0010644149,0.0001967571,0.0003747022,0.00031531585,0.24122716,0.0026848533,0.6351656,0.032508254,0.084533766],"study_design_scores_gemma":[0.000103485974,0.00018212011,0.0002697467,0.00006716784,0.00004209153,0.00026086185,0.000080487574,0.508438,0.0006213409,0.47280893,0.017086275,0.00003949716],"about_ca_topic_score_codex":0.0029423258,"about_ca_topic_score_gemma":0.002642736,"teacher_disagreement_score":0.022976922,"about_ca_system_score_codex":0.004023502,"about_ca_system_score_gemma":0.002997267,"threshold_uncertainty_score":0.076865494},"labels":[],"label_agreement":null},{"id":"W188340665","doi":"10.1007/978-3-662-46018-4_1","title":"The Multi-source Beachcombers’ Problem","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Waterloo; Université du Québec en Outaouais","funders":"","keywords":"Computer science","score_opus":0.04093236582003341,"score_gpt":0.2774382950420483,"score_spread":0.2365059292220149,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W188340665","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03253093,0.0020572783,0.7963231,0.008165903,0.0011614326,0.00013387584,0.00068906514,0.00052646257,0.1584119],"genre_scores_gemma":[0.52638274,0.0029357532,0.2248594,0.002171134,0.0012601548,0.00043436675,0.0014122545,0.001153318,0.23939085],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993119,0.0002141107,0.000027592814,0.00019189062,0.00016737237,0.00008702048],"domain_scores_gemma":[0.99782974,0.0015140402,0.00012032105,0.00024378761,0.00017572379,0.000116346666],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001011262,0.0011011878,0.0012151216,0.00085534627,0.0012083448,0.0025402626,0.002231442,0.004031731,0.024792388],"category_scores_gemma":[0.0074799857,0.00081123406,0.0011188943,0.0013791254,0.002213221,0.005012533,0.0035447343,0.0039905095,0.003016122],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023083392,0.00008078304,0.00034139713,0.00033393677,0.00008775751,0.0005271882,0.00018499358,0.06779036,0.0014278035,0.80236685,0.05293856,0.073689565],"study_design_scores_gemma":[0.000088775065,0.000036097328,0.00020895187,0.00007540863,0.000027831193,0.00036025827,0.00013178618,0.20404379,0.0013382321,0.7655139,0.028136289,0.000038520615],"about_ca_topic_score_codex":0.0013541734,"about_ca_topic_score_gemma":0.0013405094,"teacher_disagreement_score":0.024792388,"about_ca_system_score_codex":0.0008335087,"about_ca_system_score_gemma":0.00079441234,"threshold_uncertainty_score":0.08293885},"labels":[],"label_agreement":null},{"id":"W1886363748","doi":"10.1007/978-3-540-69733-6_6","title":"On the Monotonicity of Weak Searching","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Monotonic function; Digraph; Computer science; Enhanced Data Rates for GSM Evolution; Theoretical computer science; Algorithm; Combinatorics; Artificial intelligence; Mathematics","score_opus":0.02806827670807373,"score_gpt":0.26032164602651364,"score_spread":0.2322533693184399,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1886363748","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047520142,0.013275535,0.47776434,0.011114687,0.00074493675,0.00012233901,0.00054014707,0.00030788482,0.44861007],"genre_scores_gemma":[0.7257752,0.013224274,0.15926962,0.0027318737,0.0017665051,0.00057337666,0.000596792,0.0005374594,0.09552488],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987012,0.0005376781,0.00008039556,0.00017773827,0.00036126235,0.00014181239],"domain_scores_gemma":[0.991748,0.0061736084,0.00030331308,0.00073471974,0.0007760612,0.00026425655],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025737637,0.0007328497,0.0012248561,0.0014126934,0.0010963661,0.0023706248,0.0017373626,0.0014110229,0.014552268],"category_scores_gemma":[0.014400896,0.0007119868,0.0010432845,0.0019710136,0.0053386963,0.008349814,0.0025496692,0.0050912173,0.0016908186],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000037141515,0.000015867416,0.00014404407,0.00010679433,0.000008352088,0.000032216773,0.00010297006,0.0015578255,0.0005172058,0.97521544,0.0028971657,0.019365108],"study_design_scores_gemma":[0.000011288065,0.000020230385,0.00017425726,0.00005010078,0.0000069331772,0.00008481096,0.000051153136,0.0063452395,0.00026670453,0.98716474,0.005817462,0.0000069870352],"about_ca_topic_score_codex":0.0010332778,"about_ca_topic_score_gemma":0.0007694909,"teacher_disagreement_score":0.014552268,"about_ca_system_score_codex":0.0012090799,"about_ca_system_score_gemma":0.0009678104,"threshold_uncertainty_score":0.048682153},"labels":[],"label_agreement":null},{"id":"W1921787617","doi":"10.1109/icsmc.1989.71244","title":"Epsilon-optimal discretized pursuit learning automata","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Learning automata; Discretization; Computer science; Action (physics); Automaton; Rendering (computer graphics); Mathematical optimization; Artificial intelligence; Theoretical computer science; Algorithm; Mathematics","score_opus":0.01402014261147293,"score_gpt":0.2509054143074281,"score_spread":0.23688527169595514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1921787617","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15624696,0.0006050114,0.8265132,0.0007223093,0.00011347951,0.00005854001,0.00015745894,0.0003766786,0.015206368],"genre_scores_gemma":[0.9369031,0.00019219857,0.054980967,0.00012513758,0.000021783218,0.00011467314,0.000115587296,0.000035012643,0.0075114635],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994778,0.00013195419,0.000033603985,0.00010925292,0.00014154364,0.000105920844],"domain_scores_gemma":[0.99830985,0.0010469636,0.00017995281,0.00013076187,0.00018709133,0.0001454617],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065236125,0.00058318814,0.0010394972,0.00042124192,0.0005334327,0.0011418043,0.0011462595,0.0011885795,0.0026003432],"category_scores_gemma":[0.0038114367,0.00039726956,0.00052394223,0.00030520253,0.0014573128,0.00095837895,0.001748569,0.0011916851,0.00035104697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017550375,0.000057894198,0.00069026405,0.00007143479,0.000034246135,0.00010418343,0.00013392787,0.85784173,0.002271735,0.11756162,0.00080832565,0.020249048],"study_design_scores_gemma":[0.000014103509,0.000025510164,0.000033716056,0.000004108655,0.000002726695,0.000009092381,0.0000060074562,0.98184824,0.00025658007,0.017537732,0.00025748927,0.0000046912205],"about_ca_topic_score_codex":0.0028853307,"about_ca_topic_score_gemma":0.0022800278,"teacher_disagreement_score":0.0028853307,"about_ca_system_score_codex":0.0014280541,"about_ca_system_score_gemma":0.0008803328,"threshold_uncertainty_score":0.010361314},"labels":[],"label_agreement":null},{"id":"W1954494745","doi":"10.1007/3-540-44839-x_28","title":"Scheduling Intervals Using Independent Sets in Claw-Free Graphs","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Lethbridge","funders":"","keywords":"Computer science; Scheduling (production processes); Time complexity; Combinatorics; Execution time; Running time; Discrete mathematics; Algorithm; Parallel computing; Mathematics; Mathematical optimization","score_opus":0.03839137146645097,"score_gpt":0.28757377182614086,"score_spread":0.2491824003596899,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1954494745","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.104024865,0.0006618312,0.87815434,0.00031197083,0.00022954526,0.00031604356,0.0003465273,0.0018224284,0.014132415],"genre_scores_gemma":[0.62890977,0.0006375583,0.3616848,0.00015469089,0.00019429246,0.00034348763,0.00077038945,0.0006341582,0.0066708536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99881893,0.0002604376,0.00007895875,0.00024233514,0.0003338034,0.00026556867],"domain_scores_gemma":[0.99522734,0.0028146557,0.00038620143,0.0007834191,0.00034843574,0.00043996825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016290233,0.0012488294,0.0016856879,0.0018260238,0.0011898805,0.002146322,0.00379396,0.0009050412,0.005779712],"category_scores_gemma":[0.006534184,0.0013208934,0.0010753112,0.0030914855,0.00088014826,0.003683577,0.0017005233,0.0021794029,0.00074934826],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012970384,0.0005275464,0.0007353694,0.00044913878,0.00014643038,0.00016333042,0.0004209022,0.6025457,0.0124014625,0.1514649,0.009066825,0.22078149],"study_design_scores_gemma":[0.0001364602,0.00027200254,0.0002852444,0.000036197205,0.00006730507,0.000059140235,0.00007059499,0.82254505,0.005087777,0.16810068,0.0033010638,0.000038497896],"about_ca_topic_score_codex":0.0031755792,"about_ca_topic_score_gemma":0.0044116084,"teacher_disagreement_score":0.005779712,"about_ca_system_score_codex":0.0014829717,"about_ca_system_score_gemma":0.001659372,"threshold_uncertainty_score":0.019335091},"labels":[],"label_agreement":null},{"id":"W1964918537","doi":"10.1109/tac.2007.899024","title":"Curve Shortening and the Rendezvous Problem for Mobile Autonomous Robots","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polygon (computer graphics); Point in polygon; Mathematics; Regular polygon; Rendezvous; Mobile robot; Curvature; Convex polygon; Robot; Mathematical analysis; Geometry; Topology (electrical circuits); Computer science; Combinatorics; Artificial intelligence; Engineering","score_opus":0.013095365309660732,"score_gpt":0.2599077172297869,"score_spread":0.24681235192012616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1964918537","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2479506,0.0012775526,0.73943913,0.00085814303,0.00006972257,0.00007464618,0.0000666373,0.00020463268,0.010058931],"genre_scores_gemma":[0.8946101,0.0009027196,0.094712645,0.000042215685,0.000056922487,0.00008609314,0.00011027285,0.00005934393,0.009419588],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997838,0.000059057144,0.000009778851,0.000053856103,0.000062461724,0.000031091353],"domain_scores_gemma":[0.9994962,0.00024748477,0.00009850922,0.000051601583,0.00004141826,0.000064672284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000512676,0.00045038987,0.0004661184,0.0005082827,0.0007099924,0.0006418383,0.0006965336,0.00091661717,0.0015190113],"category_scores_gemma":[0.0019516681,0.00023833461,0.00039421543,0.0004717939,0.0019356395,0.0013299823,0.0012568065,0.00058117195,0.00018786978],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018499394,0.00003556446,0.0010565753,0.00011353698,0.000020250842,0.00023466632,0.0004012913,0.7425176,0.0063974224,0.18267,0.0013632152,0.06500493],"study_design_scores_gemma":[0.000032923297,0.00006990531,0.00030462272,0.000012792371,0.000006872338,0.00008289349,0.00010031558,0.91211045,0.0016823764,0.081687994,0.0038940872,0.000014863075],"about_ca_topic_score_codex":0.0032130692,"about_ca_topic_score_gemma":0.0015771007,"teacher_disagreement_score":0.0032130692,"about_ca_system_score_codex":0.00080148876,"about_ca_system_score_gemma":0.0004768583,"threshold_uncertainty_score":0.006388724},"labels":[],"label_agreement":null},{"id":"W1965378629","doi":"10.1007/s00224-011-9349-0","title":"Speed Scaling of Processes with Arbitrary Speedup Curves on a Multiprocessor","year":2011,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Speedup; Multiprocessing; Competitive analysis; Scaling; Parallel computing; Computer science; Upper and lower bounds; Constant (computer programming); Omega; Randomized algorithm; Mathematics; Algorithm; Physics; Mathematical analysis; Geometry","score_opus":0.05319425553936011,"score_gpt":0.25109109421144404,"score_spread":0.19789683867208394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965378629","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9198286,0.00096679275,0.060840912,0.0009898494,0.00015507228,0.000047971258,0.00014418489,0.0015781164,0.015448435],"genre_scores_gemma":[0.9862488,0.00022181326,0.011719825,0.000044266715,0.00003761327,0.000029299335,0.0000670593,0.00014202873,0.0014893934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999691,0.00007825029,0.000013232963,0.00004981957,0.00007774025,0.00008998448],"domain_scores_gemma":[0.9972275,0.0015968987,0.00014154924,0.0004536354,0.00038433398,0.00019604995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005257269,0.00047038184,0.00040570932,0.0009074088,0.00053861237,0.0009294757,0.00070090685,0.0006662882,0.0048363106],"category_scores_gemma":[0.0073108296,0.0003139922,0.00025722192,0.0009414168,0.00078574044,0.0017425142,0.00068038254,0.00078207866,0.00044394616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030479385,0.00043902136,0.0074512055,0.00035236144,0.000086071326,0.00046202686,0.0007816049,0.647944,0.08355566,0.12743726,0.010139835,0.11830307],"study_design_scores_gemma":[0.00007873023,0.00016386798,0.0021481249,0.000014898107,0.000019451893,0.000081576865,0.00010862647,0.95064116,0.014963985,0.030089615,0.001669721,0.000020193598],"about_ca_topic_score_codex":0.000968451,"about_ca_topic_score_gemma":0.000630558,"teacher_disagreement_score":0.0048363106,"about_ca_system_score_codex":0.0005597995,"about_ca_system_score_gemma":0.00046773872,"threshold_uncertainty_score":0.016179085},"labels":[],"label_agreement":null},{"id":"W1965412610","doi":"10.1155/2014/801791","title":"The High Contact Principle with Reward Functions Involving Initial Points","year":2014,"lang":"en","type":"article","venue":"Mathematical Problems in Engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"China Postdoctoral Science Foundation; Social Sciences and Humanities Research Council of Canada; Central University of Finance and Economics; National Natural Science Foundation of China; Beijing Municipal Office of Philosophy and Social Science Planning","keywords":"Constant (computer programming); Point (geometry); Class (philosophy); Mathematics; Process (computing); Applied mathematics; Calculus (dental); Mathematical analysis; Computer science; Geometry; Artificial intelligence","score_opus":0.012976978155335052,"score_gpt":0.23150550161488448,"score_spread":0.21852852345954943,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1965412610","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032755185,0.00046559056,0.94408524,0.00065035844,0.000051463805,0.000045042634,0.000028607232,0.000110542846,0.021807998],"genre_scores_gemma":[0.88115335,0.000687141,0.096717186,0.000309841,0.00020721888,0.00016445004,0.00006565507,0.0001592121,0.020535896],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980761,0.0006131643,0.00007946207,0.00032108196,0.0006813771,0.00022880221],"domain_scores_gemma":[0.99593854,0.002620902,0.00040702525,0.00041496442,0.00035450488,0.00026412564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027463564,0.0006712906,0.00086044474,0.0006684341,0.0008913704,0.0021485821,0.0016080353,0.00224464,0.0055060796],"category_scores_gemma":[0.007499702,0.00039063251,0.0009580818,0.0006643865,0.0039344,0.0035912793,0.0022378636,0.002396536,0.00073385745],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028702683,0.000021713457,0.0002445281,0.00005695513,0.000014111575,0.00013117188,0.00010616384,0.043947265,0.0014356963,0.9422673,0.000722206,0.011024238],"study_design_scores_gemma":[0.000028705297,0.00008899227,0.00031998818,0.000020875284,0.000010871657,0.00014724363,0.000039191058,0.22637133,0.00113849,0.7676679,0.0041461615,0.000020242302],"about_ca_topic_score_codex":0.00093506643,"about_ca_topic_score_gemma":0.0005585129,"teacher_disagreement_score":0.0055060796,"about_ca_system_score_codex":0.0013817272,"about_ca_system_score_gemma":0.0014220116,"threshold_uncertainty_score":0.018419623},"labels":[],"label_agreement":null},{"id":"W1967767406","doi":"10.1007/s00453-011-9496-3","title":"Ping Pong in Dangerous Graphs: Optimal Black Hole Search with Pebbles","year":2011,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; École de Technologie Supérieure; University of Ottawa","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Asynchronous communication; Topology (electrical circuits); Node (physics); Network topology; Theoretical computer science; Combinatorics; Discrete mathematics; Mathematics; Computer network; Physics","score_opus":0.03662411861360209,"score_gpt":0.24606018609382008,"score_spread":0.20943606748021798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1967767406","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20302108,0.0010882925,0.76745236,0.0026798686,0.000265512,0.0002493729,0.00014036593,0.0007724891,0.02433068],"genre_scores_gemma":[0.7383621,0.00045854924,0.2450768,0.0005658238,0.00009183709,0.00022901248,0.00021460453,0.00034723076,0.014654081],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922454,0.00039870522,0.00001849416,0.00013749441,0.00010111185,0.00011960746],"domain_scores_gemma":[0.9965186,0.0026338978,0.000156089,0.00028310466,0.00014064719,0.0002675932],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017171109,0.0010839986,0.0017837028,0.0013766137,0.0019763017,0.0013949715,0.002508789,0.0033836174,0.0069784746],"category_scores_gemma":[0.010541036,0.0010240976,0.0010670953,0.0010887831,0.0029515913,0.0040489696,0.0033091768,0.0025710834,0.0005703067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066730933,0.00029862978,0.0010501132,0.00029838568,0.00009807609,0.00030063876,0.0004175174,0.5425288,0.0016265939,0.38489363,0.010292362,0.057527885],"study_design_scores_gemma":[0.00007684386,0.000071960065,0.00007394634,0.000026255248,0.000022619994,0.000045222587,0.00007857439,0.6312192,0.00039184632,0.36676142,0.0012202095,0.000011924662],"about_ca_topic_score_codex":0.0024185162,"about_ca_topic_score_gemma":0.0028779253,"teacher_disagreement_score":0.0069784746,"about_ca_system_score_codex":0.0011506551,"about_ca_system_score_gemma":0.0013421176,"threshold_uncertainty_score":0.023345351},"labels":[],"label_agreement":null},{"id":"W1968085493","doi":"10.2298/yjor0501005b","title":"Applications of a special polynomial class of TSP","year":2005,"lang":"en","type":"article","venue":"Yugoslav journal of operations research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Class (philosophy); Mathematics; Combinatorics; Time complexity; Treasure; Measure (data warehouse); Computer science; Discrete mathematics; Mathematical optimization; Artificial intelligence; Database","score_opus":0.05777407111335551,"score_gpt":0.39140864777529727,"score_spread":0.33363457666194174,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968085493","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0779367,0.0035071366,0.7434479,0.0038622827,0.0010620872,0.00018487083,0.00062595506,0.00085121434,0.16852182],"genre_scores_gemma":[0.7709286,0.004917888,0.1858468,0.000978411,0.001687347,0.0001849564,0.0008852586,0.00033656493,0.03423415],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999432,0.00015047898,0.000022309188,0.0001265105,0.00014987319,0.00011885651],"domain_scores_gemma":[0.9987373,0.0006670497,0.00011863531,0.00022063231,0.00014353367,0.00011288049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044994292,0.00058390567,0.00069890777,0.000707494,0.0009967558,0.0008892145,0.0011567881,0.0011126656,0.011251316],"category_scores_gemma":[0.0031086742,0.0002277962,0.0010795796,0.001512203,0.00079083076,0.0013583985,0.001166529,0.001797657,0.00083287706],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013350924,0.00018842587,0.0011487708,0.00038492304,0.000056136927,0.0004644243,0.0002008361,0.26142722,0.0023268545,0.57603556,0.037789457,0.11984388],"study_design_scores_gemma":[0.000038146503,0.000054495697,0.00062737416,0.000026090851,0.000017441773,0.000513511,0.00008217531,0.62483865,0.0006298158,0.3210996,0.052058622,0.000014096613],"about_ca_topic_score_codex":0.0053416346,"about_ca_topic_score_gemma":0.0049266065,"teacher_disagreement_score":0.011251316,"about_ca_system_score_codex":0.0013466951,"about_ca_system_score_gemma":0.00081512315,"threshold_uncertainty_score":0.03763944},"labels":[],"label_agreement":null},{"id":"W1968885544","doi":"10.1016/s0304-3975(03)00141-5","title":"On polynomial-time approximation algorithms for the variable length scheduling problem","year":2003,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; University of Lethbridge","funders":"","keywords":"Approximation algorithm; Mathematics; Algorithm; Extension (predicate logic); Approximation error; Scheduling (production processes); Polynomial-time approximation scheme; Variable (mathematics); Discrete mathematics; Combinatorics; Computer science; Mathematical optimization; Mathematical analysis","score_opus":0.016075939359333716,"score_gpt":0.2594672765588951,"score_spread":0.2433913371995614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1968885544","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030166674,0.003369949,0.9452551,0.0029396384,0.00048211977,0.00020487861,0.00033918273,0.0018181567,0.015424302],"genre_scores_gemma":[0.2760889,0.0031196682,0.70487404,0.0011904286,0.00072168343,0.0004683659,0.0014131682,0.00093258556,0.011191172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960743,0.0014442095,0.00017373415,0.00063913193,0.00087971205,0.0007889494],"domain_scores_gemma":[0.98527527,0.011432782,0.0006765597,0.0014551989,0.0006945104,0.00046573402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054848143,0.0025448643,0.0027919621,0.0019315805,0.0021634847,0.0042780074,0.0049348585,0.0029169868,0.00954586],"category_scores_gemma":[0.023218166,0.0011432066,0.001775401,0.0050404854,0.00239573,0.009245046,0.003081579,0.0055457707,0.0021706312],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018962801,0.0008122934,0.001219858,0.00051092036,0.00018570482,0.00009707245,0.0004318003,0.5750553,0.0025321343,0.13881119,0.027711933,0.25073555],"study_design_scores_gemma":[0.00029755506,0.000089759495,0.000184026,0.00003947473,0.000059414204,0.000042411193,0.000090522866,0.859037,0.0005990236,0.13613752,0.0034024057,0.000020987976],"about_ca_topic_score_codex":0.014345834,"about_ca_topic_score_gemma":0.014672704,"teacher_disagreement_score":0.014345834,"about_ca_system_score_codex":0.0051281108,"about_ca_system_score_gemma":0.0054321242,"threshold_uncertainty_score":0.037207246},"labels":[],"label_agreement":null},{"id":"W1970322539","doi":"10.1016/j.tcs.2008.10.005","title":"Gathering few fat mobile robots in the plane","year":2008,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":141,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Engineering and Physical Sciences Research Council","keywords":"Robot; Asynchronous communication; Mobile robot; Computer science; Plane (geometry); Artificial intelligence; Combinatorics; Mathematics; Geometry; Telecommunications","score_opus":0.020414413547268855,"score_gpt":0.260438264394177,"score_spread":0.24002385084690814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970322539","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4746212,0.00072110957,0.51526785,0.0010591586,0.00008363174,0.000068990106,0.00018307436,0.00023388896,0.0077611543],"genre_scores_gemma":[0.82957584,0.0005757834,0.16229546,0.00014518159,0.000059090835,0.00008996598,0.00022588173,0.000057407047,0.0069753523],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978656,0.000047261972,0.0000099838135,0.000059987953,0.00004318809,0.000053077743],"domain_scores_gemma":[0.9989104,0.00065108464,0.00016208811,0.00009148665,0.000083904764,0.00010103014],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047005262,0.00063743815,0.0011230535,0.0007466933,0.0011781489,0.0010700964,0.0010523369,0.0013857399,0.0028667348],"category_scores_gemma":[0.003019142,0.0006287172,0.0005384134,0.0008049204,0.0010893184,0.0019780707,0.002350956,0.0009019708,0.0006192573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027708234,0.0001916875,0.0062249335,0.0006548898,0.00034859034,0.0016325306,0.0010708736,0.74311614,0.04455502,0.11201854,0.0043067005,0.08310929],"study_design_scores_gemma":[0.00015895591,0.0002909328,0.0010597436,0.000049968352,0.000059294707,0.00039209222,0.0005772076,0.9208407,0.004455372,0.069778755,0.0023112867,0.000025615826],"about_ca_topic_score_codex":0.0011076138,"about_ca_topic_score_gemma":0.00095914863,"teacher_disagreement_score":0.0028667348,"about_ca_system_score_codex":0.0003704657,"about_ca_system_score_gemma":0.0002699976,"threshold_uncertainty_score":0.0095902085},"labels":[],"label_agreement":null},{"id":"W1970669897","doi":"10.1016/j.ipl.2011.07.018","title":"How many oblivious robots can explore a line","year":2011,"lang":"en","type":"article","venue":"Information Processing Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais; University of Ottawa","funders":"Agence Nationale de la Recherche","keywords":"Asynchronous communication; Robot; Impossibility; Computer science; Line (geometry); Theoretical computer science; Mobile robot; Node (physics); Combinatorics; Distributed computing; Artificial intelligence; Mathematics; Computer network; Physics","score_opus":0.056753769306573394,"score_gpt":0.23498676798739124,"score_spread":0.17823299868081785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1970669897","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5203198,0.0021077853,0.41473484,0.009901595,0.00026126902,0.00014978442,0.00035749204,0.0013517481,0.050815668],"genre_scores_gemma":[0.9354521,0.00054134516,0.05211351,0.0002807441,0.00006851187,0.00010780558,0.00016494404,0.00019378301,0.011077215],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993318,0.00024139296,0.000036222464,0.0001561825,0.000090472386,0.00014401425],"domain_scores_gemma":[0.99698716,0.0019079854,0.00023893402,0.000528541,0.00014810827,0.00018937721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009012806,0.0004624951,0.00062048377,0.00033867045,0.0010638736,0.0019135989,0.0011632905,0.0014188915,0.00669868],"category_scores_gemma":[0.007256211,0.00042165208,0.0004691824,0.0005636208,0.001558907,0.005637109,0.0016593831,0.0014256272,0.000852598],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017073146,0.00025741747,0.004498696,0.0005630443,0.00025671217,0.00017798634,0.0007747339,0.49092066,0.0070528323,0.28957385,0.015322414,0.18889423],"study_design_scores_gemma":[0.00012712406,0.00025871847,0.00082270755,0.000063605905,0.0000911255,0.0001657827,0.000536617,0.557677,0.004709796,0.42755577,0.007959676,0.000032083928],"about_ca_topic_score_codex":0.00081961724,"about_ca_topic_score_gemma":0.0011751468,"teacher_disagreement_score":0.00669868,"about_ca_system_score_codex":0.0006964583,"about_ca_system_score_gemma":0.0007925191,"threshold_uncertainty_score":0.02240926},"labels":[],"label_agreement":null},{"id":"W1971694274","doi":"10.1016/j.jcss.2009.07.002","title":"Communication algorithms with advice","year":2009,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Advice (programming); Computer science; Dissemination; Node (physics); Broadcasting (networking); Computer network; Algorithm; Theoretical computer science; Telecommunications","score_opus":0.017505653996276998,"score_gpt":0.26672492767637895,"score_spread":0.24921927368010197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1971694274","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0299452,0.0011765447,0.8566803,0.005367769,0.0013138166,0.00026269193,0.0004752329,0.0103665665,0.09441203],"genre_scores_gemma":[0.4951814,0.00066479784,0.404964,0.0018534783,0.0011106629,0.0005745998,0.00086255017,0.0020245232,0.092763856],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967018,0.001109332,0.00017848423,0.0005380528,0.00097600184,0.0004964557],"domain_scores_gemma":[0.987039,0.00710016,0.00029961,0.0037565662,0.0014246581,0.00037992618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022242481,0.0012008516,0.0015061896,0.0015580442,0.0023157848,0.0027479567,0.002161748,0.002666919,0.026603144],"category_scores_gemma":[0.025179923,0.0006952368,0.0010044302,0.0016692748,0.0018583287,0.0038658236,0.0031533674,0.003949926,0.007722837],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010276921,0.00037457235,0.0013871919,0.00032303648,0.00010200812,0.00016291418,0.0004694334,0.04238336,0.002557349,0.41486514,0.09020157,0.44614574],"study_design_scores_gemma":[0.00026308626,0.0001050295,0.0002341663,0.00007887794,0.000078287776,0.00015975854,0.00007015984,0.32740697,0.004368643,0.63817096,0.029032957,0.00003105703],"about_ca_topic_score_codex":0.0027239448,"about_ca_topic_score_gemma":0.003085434,"teacher_disagreement_score":0.026603144,"about_ca_system_score_codex":0.0013877776,"about_ca_system_score_gemma":0.0024855435,"threshold_uncertainty_score":0.08899635},"labels":[],"label_agreement":null},{"id":"W1972503266","doi":"10.1109/tsmcb.2012.2224339","title":"Learning-Automaton-Based Online Discovery and Tracking of Spatiotemporal Event Patterns","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Event (particle physics); Correctness; Machine learning; Adaptation (eye); Scheme (mathematics); Artificial intelligence; Theoretical computer science; Distributed computing; Data mining; Algorithm","score_opus":0.0221934737989136,"score_gpt":0.27142645665969445,"score_spread":0.24923298286078086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972503266","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13098389,0.00021210742,0.8647268,0.00022627563,0.000043106415,0.000099481214,0.00023178213,0.0021042377,0.00137234],"genre_scores_gemma":[0.93301153,0.00007189882,0.06554837,0.000047098376,0.000012598825,0.000083727806,0.00029627918,0.00003435042,0.0008941014],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999086,0.00017327542,0.00009219577,0.00035751966,0.00019805969,0.000092964954],"domain_scores_gemma":[0.9939423,0.0038120341,0.0006565125,0.0008010322,0.0005968307,0.00019124855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012977127,0.0005410709,0.00092190126,0.00076782267,0.00045584005,0.0010592816,0.001868979,0.00083299173,0.0010056898],"category_scores_gemma":[0.0077850614,0.0003668715,0.0006750231,0.000552938,0.0008749165,0.0014675558,0.0013226161,0.0011807836,0.0003212558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040211208,0.00022062985,0.01463219,0.0001484535,0.00009233032,0.00023463805,0.00039525586,0.80638856,0.009182532,0.008926664,0.0009448401,0.15843184],"study_design_scores_gemma":[0.0000034424745,0.000026998203,0.00033222884,0.0000023035213,0.0000050842523,0.000022103295,0.000008786056,0.99720013,0.0009516769,0.0013174072,0.00012608181,0.000003802685],"about_ca_topic_score_codex":0.008043423,"about_ca_topic_score_gemma":0.007656185,"teacher_disagreement_score":0.008043423,"about_ca_system_score_codex":0.0008575186,"about_ca_system_score_gemma":0.0012459008,"threshold_uncertainty_score":0.015993178},"labels":[],"label_agreement":null},{"id":"W1972775782","doi":"10.1007/s00446-011-0141-9","title":"How to meet when you forget: log-space rendezvous in arbitrary graphs","year":2011,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":97,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Binary logarithm; Computer science; Upper and lower bounds; Graph; Combinatorics; Matching (statistics); Discrete mathematics; Node (physics); Mathematics; Theoretical computer science","score_opus":0.035370928479806094,"score_gpt":0.2406513227041873,"score_spread":0.2052803942243812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972775782","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2927701,0.0013373895,0.66872543,0.008788339,0.0005333234,0.00013760678,0.0004042942,0.0033632678,0.023940297],"genre_scores_gemma":[0.920525,0.00036509597,0.06597112,0.0003279146,0.00008372366,0.000067620815,0.00020844175,0.0005681103,0.011882902],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99915147,0.00032981162,0.000028043798,0.00017226387,0.00014711889,0.00017141858],"domain_scores_gemma":[0.9953087,0.0026553764,0.00019202134,0.0011113777,0.0002667903,0.0004656976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013376315,0.0005717441,0.0013130197,0.0005386437,0.0024084696,0.0020448908,0.001879113,0.0019290836,0.006696729],"category_scores_gemma":[0.0125420205,0.0004763996,0.0005480371,0.001144963,0.002904287,0.007260653,0.0035570678,0.002526334,0.0012839418],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018991586,0.00023428911,0.0018796006,0.0002810437,0.00009777004,0.00057823595,0.0020695638,0.4001177,0.0063309297,0.42209688,0.035097636,0.12931722],"study_design_scores_gemma":[0.00008884924,0.000053456442,0.00018641946,0.000021248403,0.000023852748,0.00015357233,0.0007218623,0.57869816,0.0024775004,0.4119942,0.005550333,0.000030495594],"about_ca_topic_score_codex":0.0050291363,"about_ca_topic_score_gemma":0.005290134,"teacher_disagreement_score":0.006696729,"about_ca_system_score_codex":0.000809992,"about_ca_system_score_gemma":0.00096176896,"threshold_uncertainty_score":0.022402823},"labels":[],"label_agreement":null},{"id":"W1973963219","doi":"10.1109/icsssm.2011.5959522","title":"Online routing of hazardous materials transportation based on risk equity","year":2011,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Beijing University of Chemical Technology; National Natural Science Foundation of China; Beijing University of Technology; Ryerson University","keywords":"Hazardous waste; Equity (law); Computer science; Node (physics); Transport engineering; Flow network; Risk analysis (engineering); Operations research; Business; Engineering; Mathematical optimization; Mathematics","score_opus":0.06880667339669169,"score_gpt":0.29590137927632887,"score_spread":0.22709470587963718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1973963219","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14640173,0.00041968378,0.8394621,0.00061664195,0.0000819578,0.00021314791,0.00019605045,0.00044370786,0.012164915],"genre_scores_gemma":[0.88189673,0.00032719376,0.109474756,0.00014070093,0.00004674115,0.00014183759,0.00028048165,0.000080785176,0.007610658],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992828,0.00024565324,0.000025286166,0.00015336036,0.00014420248,0.00014867075],"domain_scores_gemma":[0.99893206,0.00054493133,0.00019502538,0.00008726792,0.000106510415,0.00013415536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007499848,0.00083671993,0.0013440613,0.0007167831,0.00075127056,0.0013175581,0.0014253013,0.0012252645,0.004606093],"category_scores_gemma":[0.002424483,0.00058203697,0.0006896483,0.0009419427,0.0006933662,0.0020383059,0.0011290531,0.00068066135,0.00034061246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015583985,0.000098870405,0.00064142514,0.000052317828,0.000035983416,0.00006197049,0.0000561313,0.94510674,0.0011228422,0.016753541,0.0017797326,0.034134556],"study_design_scores_gemma":[0.000010504154,0.000032777072,0.00007618282,0.000002689431,0.000005914523,0.0000150096585,0.000012201242,0.99355465,0.00023057121,0.005655793,0.0004004202,0.0000033937472],"about_ca_topic_score_codex":0.00495851,"about_ca_topic_score_gemma":0.0037055186,"teacher_disagreement_score":0.00495851,"about_ca_system_score_codex":0.0017331172,"about_ca_system_score_gemma":0.0013337764,"threshold_uncertainty_score":0.015408933},"labels":[],"label_agreement":null},{"id":"W1974010905","doi":"10.1109/cdc.2014.7039415","title":"Robot monitoring for the detection and confirmation of stochastic events","year":2014,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Patrolling; Event (particle physics); Robot; Traverse; Computer science; Path (computing); False positive paradox; Artificial intelligence; Simple (philosophy); Algorithm","score_opus":0.04424917438107049,"score_gpt":0.30155702493265635,"score_spread":0.25730785055158584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974010905","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11319617,0.0005280502,0.882357,0.00077749917,0.00005800257,0.000115608585,0.00020579212,0.0009054241,0.0018564211],"genre_scores_gemma":[0.88596207,0.00019919359,0.111244366,0.00011735028,0.00006893906,0.000088049535,0.00021817586,0.0000871892,0.0020147252],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998072,0.0006223997,0.000080838036,0.0006820648,0.00033874478,0.00020392086],"domain_scores_gemma":[0.9877802,0.008942783,0.0018295206,0.0007256958,0.0004154264,0.00030631485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019547578,0.0008317909,0.0013544041,0.00071214867,0.0007422613,0.0011978596,0.0020199558,0.0015289905,0.00213303],"category_scores_gemma":[0.011983666,0.0007725614,0.00075082935,0.0008756729,0.0014217828,0.0021081285,0.0010932029,0.0013666033,0.00027225842],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005902038,0.00016736209,0.006487845,0.0003006112,0.00015274677,0.0005086427,0.00025744413,0.8810075,0.0075228424,0.034683425,0.0024444133,0.065876946],"study_design_scores_gemma":[0.000022892313,0.00006563991,0.00094025687,0.0000101351,0.00001608241,0.000103118065,0.000031029467,0.980737,0.0015619405,0.015793346,0.00070690503,0.000011748919],"about_ca_topic_score_codex":0.0035130156,"about_ca_topic_score_gemma":0.0032571321,"teacher_disagreement_score":0.0035130156,"about_ca_system_score_codex":0.0013568436,"about_ca_system_score_gemma":0.0010613893,"threshold_uncertainty_score":0.010337889},"labels":[],"label_agreement":null},{"id":"W1974192323","doi":"10.1016/s0166-218x(03)00189-6","title":"Searching with mobile agents in networks with liars","year":2003,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Bounded function; Hypercube; Node (physics); Computer science; Graph; Theoretical computer science; Shortest path problem; Path (computing); Mathematics; Combinatorics; Discrete mathematics; Topology (electrical circuits); Computer network","score_opus":0.018882787564954387,"score_gpt":0.26042773149044907,"score_spread":0.2415449439254947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974192323","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2440708,0.0017673594,0.7375764,0.0027759173,0.000160636,0.00013526494,0.000102400765,0.0002995194,0.013111543],"genre_scores_gemma":[0.93350816,0.0006948946,0.053798467,0.00023935894,0.00017126469,0.00020035058,0.000070572074,0.000045193443,0.01127172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999111,0.00047072544,0.00004363477,0.00014785232,0.000094931456,0.00013183345],"domain_scores_gemma":[0.9913761,0.0065840436,0.0009930428,0.00020989108,0.00033902415,0.0004978397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027199052,0.00080501544,0.0019040512,0.0016402901,0.0015590518,0.0028695236,0.0019965284,0.0034219087,0.0030708848],"category_scores_gemma":[0.014218669,0.0008078118,0.00088011223,0.0011467055,0.0023981952,0.00379429,0.0026450043,0.0013376456,0.00044020306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038240512,0.000101733654,0.0015474327,0.0001948459,0.00012961327,0.0004590113,0.00027920582,0.79869497,0.0012600869,0.18193325,0.0017105143,0.013306833],"study_design_scores_gemma":[0.00006413998,0.00006676866,0.00007565816,0.000015635966,0.000020194266,0.000040994542,0.000059502738,0.9541123,0.00027752703,0.04465796,0.00059939694,0.000009799642],"about_ca_topic_score_codex":0.002473884,"about_ca_topic_score_gemma":0.0018031603,"teacher_disagreement_score":0.0034219087,"about_ca_system_score_codex":0.0011728962,"about_ca_system_score_gemma":0.00068751135,"threshold_uncertainty_score":0.0143844485},"labels":[],"label_agreement":null},{"id":"W1974563358","doi":"10.1155/2012/841291","title":"Market-Based Approach to Mobile Surveillance Systems","year":2012,"lang":"en","type":"article","venue":"Journal of Robotics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Task (project management); Software deployment; Interoperability; Computer security; Sensor fusion; Real-time computing; Artificial intelligence; Systems engineering; World Wide Web","score_opus":0.025783443565970055,"score_gpt":0.2628814565871655,"score_spread":0.23709801302119543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974563358","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01179788,0.0016124268,0.94762987,0.0029076708,0.00019415119,0.0001483286,0.00011714572,0.000101629565,0.035491],"genre_scores_gemma":[0.7962881,0.003248345,0.16126168,0.000634989,0.0007238632,0.0005522386,0.00012951977,0.00007666828,0.037084628],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989568,0.00043761192,0.000038237336,0.00019930689,0.00026372744,0.0001042475],"domain_scores_gemma":[0.99920493,0.00040972352,0.00010119303,0.00004936507,0.00016461742,0.00007011155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013418422,0.00081013096,0.0009294739,0.00076397345,0.00075990765,0.002306638,0.0017667615,0.002434778,0.006536069],"category_scores_gemma":[0.0019738625,0.00039405856,0.0008743773,0.00073283084,0.0016420903,0.0029933725,0.001605443,0.0015198801,0.0005843711],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003384174,0.000052196636,0.00021937178,0.00009655724,0.00003745993,0.0003083979,0.00012355231,0.1482676,0.0011821638,0.8327456,0.0026127168,0.014320473],"study_design_scores_gemma":[0.00003208833,0.00006491016,0.00013250348,0.00001972022,0.000013481602,0.00012107492,0.000053683794,0.69702494,0.00029826167,0.29147115,0.010743126,0.000025069525],"about_ca_topic_score_codex":0.002196211,"about_ca_topic_score_gemma":0.0016787642,"teacher_disagreement_score":0.006536069,"about_ca_system_score_codex":0.0018328862,"about_ca_system_score_gemma":0.00095894525,"threshold_uncertainty_score":0.021865308},"labels":[],"label_agreement":null},{"id":"W1975011672","doi":"10.1007/s00446-008-0076-y","title":"Distributed computing with advice: information sensitivity of graph coloring","year":2009,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Advice (programming); Computer science; Graph; Computation; Graph coloring; Sensitivity (control systems); Theoretical computer science; Greedy coloring; Algorithm; Line graph","score_opus":0.009462218466195972,"score_gpt":0.23770859518744922,"score_spread":0.22824637672125325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975011672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15360351,0.0013914475,0.81017077,0.004263989,0.00039191957,0.00017197664,0.00025633414,0.0015159635,0.02823412],"genre_scores_gemma":[0.93447363,0.00060176745,0.05854094,0.00055592036,0.00023032624,0.000098227174,0.000118199845,0.00030840904,0.005072545],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966708,0.0016344438,0.0000792048,0.00043211022,0.00074610877,0.0004372747],"domain_scores_gemma":[0.95692134,0.03628909,0.0010380899,0.0031333864,0.0017870227,0.0008311703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038423284,0.0008321191,0.0018243368,0.0015308041,0.0013721439,0.0023787732,0.0021797617,0.0021365718,0.004930954],"category_scores_gemma":[0.04708641,0.0008454504,0.0009329546,0.0018720139,0.0023128847,0.0038635435,0.0024741078,0.0033870845,0.00036311222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006632699,0.00027838087,0.0017049937,0.00025446218,0.00008965328,0.00021889182,0.00035185763,0.6188512,0.003667652,0.30450484,0.011299399,0.058115464],"study_design_scores_gemma":[0.000029817242,0.000021151818,0.00017449536,0.00001172002,0.000021227092,0.000045405806,0.000027628086,0.836578,0.0009063092,0.16140923,0.00076445966,0.000010500419],"about_ca_topic_score_codex":0.0060590724,"about_ca_topic_score_gemma":0.0041960706,"teacher_disagreement_score":0.0060590724,"about_ca_system_score_codex":0.002881511,"about_ca_system_score_gemma":0.0023243907,"threshold_uncertainty_score":0.020906925},"labels":[],"label_agreement":null},{"id":"W1975531816","doi":"10.1016/j.tcs.2008.07.026","title":"Arbitrary pattern formation by asynchronous, anonymous, oblivious robots","year":2008,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":224,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Robot; Task (project management); Asynchronous communication; Set (abstract data type); Computer science; Mobile robot; Compass; Point (geometry); Artificial intelligence; Mathematics; Engineering; Geography; Geometry; Programming language","score_opus":0.011354233580310269,"score_gpt":0.22968399274611032,"score_spread":0.21832975916580005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975531816","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20880981,0.000116498806,0.77938783,0.000470522,0.00007969046,0.00011600412,0.00009944763,0.000623357,0.01029684],"genre_scores_gemma":[0.9206671,0.00008738089,0.07088132,0.0000800151,0.00002542027,0.0001398035,0.00007945278,0.00007702561,0.007962399],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990056,0.0003081476,0.000055791163,0.0002113711,0.00025640693,0.0001627301],"domain_scores_gemma":[0.9964223,0.0015275222,0.0005377168,0.0009343752,0.00026626428,0.00031182336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011569986,0.00037385587,0.0006703352,0.0004687843,0.00080780685,0.0009565131,0.0018279299,0.0009046169,0.0023095312],"category_scores_gemma":[0.006495263,0.0004439388,0.0005124789,0.0006595819,0.0014564721,0.0020051007,0.0024176892,0.00086173695,0.00047166483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010577441,0.00019403324,0.002547722,0.00020251003,0.000099882476,0.00046780903,0.00055504474,0.5667864,0.02004783,0.31660393,0.0035680623,0.087869115],"study_design_scores_gemma":[0.00011127653,0.00012639585,0.00034379066,0.0000090078,0.000022322687,0.00012661435,0.000088157874,0.827382,0.0052520875,0.16445686,0.0020635074,0.000017955079],"about_ca_topic_score_codex":0.00072322745,"about_ca_topic_score_gemma":0.00090881134,"teacher_disagreement_score":0.0023095312,"about_ca_system_score_codex":0.0004936854,"about_ca_system_score_gemma":0.00083132816,"threshold_uncertainty_score":0.007726133},"labels":[],"label_agreement":null},{"id":"W1976011284","doi":"10.1007/s00224-007-9085-7","title":"A Randomized Algorithm for Online Unit Clustering","year":2007,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Online algorithm; Randomized algorithm; Cluster analysis; Partition (number theory); Upper and lower bounds; Extension (predicate logic); Computer science; Set (abstract data type); Mathematics; Combinatorics; Unit (ring theory); Algorithm; Artificial intelligence","score_opus":0.04092833779722757,"score_gpt":0.3136730632364606,"score_spread":0.272744725439233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976011284","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010135339,0.00031881785,0.9832882,0.0005108789,0.00018323399,0.0002738194,0.00024418026,0.0022249222,0.0028205547],"genre_scores_gemma":[0.13441776,0.00017920848,0.856681,0.00035601392,0.0001776903,0.00073167525,0.00085092697,0.0004617096,0.006144099],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964185,0.0012892835,0.00020289706,0.0009005191,0.00073145935,0.00045735686],"domain_scores_gemma":[0.9924453,0.003962278,0.00045237888,0.0017373933,0.00089170184,0.00051099],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031166405,0.0016781458,0.0037821915,0.002057724,0.0023733838,0.0023854533,0.007577334,0.003874513,0.012301389],"category_scores_gemma":[0.014582922,0.001351229,0.0017753815,0.0039107497,0.0018112195,0.004698691,0.004733569,0.0031716905,0.003653806],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020751753,0.0008811692,0.0009051385,0.000424417,0.00021383831,0.0001028334,0.0002492089,0.43420208,0.004632124,0.08764973,0.035209678,0.43345454],"study_design_scores_gemma":[0.00027888926,0.00010963045,0.00013663039,0.000015384852,0.000031116306,0.000051777657,0.000034534707,0.9602669,0.0010361528,0.03614939,0.0018626044,0.000027119606],"about_ca_topic_score_codex":0.007180906,"about_ca_topic_score_gemma":0.009716865,"teacher_disagreement_score":0.012301389,"about_ca_system_score_codex":0.003366675,"about_ca_system_score_gemma":0.005099775,"threshold_uncertainty_score":0.04115224},"labels":[],"label_agreement":null},{"id":"W1976290517","doi":"10.1007/s10846-010-9536-2","title":"Complex Task Allocation in Mobile Surveillance Systems","year":2011,"lang":"en","type":"article","venue":"Journal of Intelligent & Robotic Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Task (project management); Computer science; Set (abstract data type); Tree (set theory); Mobile robot; Artificial intelligence; Distributed computing; Real-time computing; Robot; Data mining; Engineering","score_opus":0.07189908800088718,"score_gpt":0.2843704492275869,"score_spread":0.21247136122669974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1976290517","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23882937,0.0005898862,0.7560538,0.00040619084,0.00006458623,0.00007935958,0.0000797313,0.00012208088,0.0037749475],"genre_scores_gemma":[0.977105,0.00013081243,0.020680912,0.000041427313,0.00003138702,0.00005892435,0.000032642507,0.000029446765,0.0018895123],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947053,0.00019308629,0.00002575277,0.00010476957,0.00008092645,0.00012495775],"domain_scores_gemma":[0.99790996,0.0014367112,0.00020559841,0.00011656159,0.00017206852,0.00015918988],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010175514,0.0005215433,0.0011188452,0.00044109288,0.00057643646,0.0012577759,0.00084134936,0.00093293196,0.002649572],"category_scores_gemma":[0.0039988933,0.00046988396,0.00033024527,0.0005882285,0.0007167517,0.0013824077,0.0010687226,0.00073551224,0.00022314876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002224515,0.00007027733,0.00050281617,0.000047751975,0.000024262401,0.00006241922,0.000079870806,0.9587132,0.0020931223,0.012282116,0.000656058,0.025245631],"study_design_scores_gemma":[0.000009572726,0.000029897787,0.00022502756,0.0000022401753,0.000004396721,0.000011948905,0.000018127595,0.99259514,0.0001874838,0.006780623,0.00013160762,0.000003916429],"about_ca_topic_score_codex":0.0031897135,"about_ca_topic_score_gemma":0.0021728177,"teacher_disagreement_score":0.0031897135,"about_ca_system_score_codex":0.00070400833,"about_ca_system_score_gemma":0.00062140584,"threshold_uncertainty_score":0.0088636875},"labels":[],"label_agreement":null},{"id":"W1977093483","doi":"10.1142/9789812776136_0002","title":"FRESCO: FLEXIBLE ALIGNMENT WITH RECTANGLE SCORING SCHEMES","year":2007,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Rectangle; Fresco; Computer science; Artificial intelligence; Mathematics; Geometry; History","score_opus":0.017076907947766323,"score_gpt":0.2584471713434894,"score_spread":0.24137026339572307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977093483","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013791389,0.00046325533,0.96292925,0.00019713226,0.00012056982,0.00020303314,0.00060763035,0.01724231,0.004445508],"genre_scores_gemma":[0.07584269,0.0003343572,0.9147674,0.00022613602,0.00005158719,0.0004022911,0.0017296469,0.0031097338,0.0035362428],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99720937,0.0010816477,0.00020328986,0.00049849955,0.00077771494,0.00022953436],"domain_scores_gemma":[0.99727875,0.0009934554,0.00034937714,0.0007474818,0.0004800231,0.00015091465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004019314,0.001615902,0.0013380648,0.0018375595,0.001042383,0.0015142795,0.0025891415,0.0021417618,0.009932573],"category_scores_gemma":[0.012086263,0.00096197927,0.0012227206,0.0024220736,0.00088700803,0.0028407315,0.0020516738,0.0020748116,0.006066989],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001657944,0.00029188232,0.0034647,0.00087052624,0.00022859473,0.0006008774,0.0005461219,0.13368562,0.06697087,0.1390377,0.0845148,0.5681303],"study_design_scores_gemma":[0.00032680514,0.00038376762,0.0012065527,0.000116717696,0.00005655948,0.0008186308,0.00010817418,0.8342394,0.045424465,0.045694664,0.071371056,0.00025314066],"about_ca_topic_score_codex":0.0022326845,"about_ca_topic_score_gemma":0.0027168866,"teacher_disagreement_score":0.009932573,"about_ca_system_score_codex":0.0008477031,"about_ca_system_score_gemma":0.0017598582,"threshold_uncertainty_score":0.0332278},"labels":[],"label_agreement":null},{"id":"W1977603728","doi":"10.1016/j.tcs.2008.04.034","title":"Memoryless search algorithms in a network with faulty advice","year":2008,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bounded function; Advice (programming); Node (physics); Shortest path problem; Computer science; Network topology; Graph; Combinatorics; Enhanced Data Rates for GSM Evolution; Path (computing); Discrete mathematics; Mathematics; Randomized algorithm; Algorithm; Theoretical computer science; Computer network; Artificial intelligence","score_opus":0.01864963886820921,"score_gpt":0.2649793731140586,"score_spread":0.24632973424584942,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977603728","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4333864,0.0012227194,0.55168635,0.0044968743,0.00023320456,0.00011000151,0.00036717733,0.0018509177,0.006646406],"genre_scores_gemma":[0.89577353,0.00028933433,0.09632033,0.00029158275,0.00013149007,0.00009485664,0.0001508627,0.00016145263,0.00678668],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984554,0.0004921557,0.000097366246,0.00032349795,0.00034245392,0.0002891546],"domain_scores_gemma":[0.96706665,0.025821049,0.0014673232,0.0030143603,0.001808548,0.0008220425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027933419,0.00075496413,0.0017158402,0.0016452185,0.0019155756,0.0022320345,0.003398106,0.0033259904,0.0030837727],"category_scores_gemma":[0.032289308,0.0008101314,0.00060386164,0.0015482891,0.002327602,0.0045038112,0.002439727,0.0026114874,0.00042528013],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024871742,0.00022266858,0.0042113364,0.00031678326,0.00014893223,0.0006279,0.00072739867,0.76030535,0.0037256612,0.14371586,0.008159156,0.075351775],"study_design_scores_gemma":[0.00009698999,0.0000514149,0.00014000498,0.000014622855,0.0000313165,0.000063268555,0.000041877265,0.89470935,0.0012562048,0.10309635,0.00048918114,0.0000094277375],"about_ca_topic_score_codex":0.0055959057,"about_ca_topic_score_gemma":0.005580949,"teacher_disagreement_score":0.0055959057,"about_ca_system_score_codex":0.0018614802,"about_ca_system_score_gemma":0.0016891918,"threshold_uncertainty_score":0.014772773},"labels":[],"label_agreement":null},{"id":"W1977638907","doi":"10.1109/cse.2014.40","title":"On Utilizing Stochastic Non-linear Fractional Bin Packing to Resolve Distributed Web Crawling","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Crawling; Computer science; Scheme (mathematics); Task (project management); Resource allocation; Distributed computing; Bin packing problem; Bin; Knapsack problem; Software deployment; Web server; Linear programming; Mathematical optimization; Theoretical computer science; Algorithm; The Internet; Mathematics; World Wide Web; Computer network; Engineering","score_opus":0.028487858279956927,"score_gpt":0.29194799869205523,"score_spread":0.2634601404120983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977638907","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024438605,0.00019231447,0.9730674,0.0001669911,0.00004577956,0.000059867176,0.000028846276,0.00040175847,0.0015983409],"genre_scores_gemma":[0.598159,0.0003023799,0.39880323,0.0002535009,0.00008287651,0.00018815238,0.00013691602,0.00009193992,0.0019819497],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914706,0.00027676346,0.000055489578,0.0001661196,0.00022617272,0.00012832823],"domain_scores_gemma":[0.99712545,0.0017772873,0.00029268122,0.0003627373,0.00026550578,0.00017635363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001406795,0.0006439065,0.0014574288,0.00079231255,0.00089327537,0.0012356745,0.0012497712,0.0012484376,0.0013268333],"category_scores_gemma":[0.0049292743,0.0003590353,0.0006130455,0.0011820648,0.0011341529,0.001734767,0.0018874084,0.0011487768,0.00032309748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013068973,0.00015327659,0.0007654641,0.00010399182,0.000032787575,0.000075990385,0.00009934558,0.8916313,0.004247992,0.028121147,0.0012319075,0.07340611],"study_design_scores_gemma":[0.0000048168677,0.000018484321,0.000033331708,0.0000029174628,0.000002658552,0.00001274784,0.000007739193,0.99455476,0.00041990395,0.004677103,0.00026220546,0.0000032745936],"about_ca_topic_score_codex":0.0024377357,"about_ca_topic_score_gemma":0.0027825942,"teacher_disagreement_score":0.0024377357,"about_ca_system_score_codex":0.00082903716,"about_ca_system_score_gemma":0.0012249629,"threshold_uncertainty_score":0.0074399114},"labels":[],"label_agreement":null},{"id":"W1977849109","doi":"10.1109/syscon.2014.6819239","title":"FPGA implementation of multiple Pursuit-Evasion games with decentralized Learning Automata","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Field-programmable gate array; Computer science; Learning automata; VHDL; Hardware description language; Markov chain; Reconfigurable computing; Embedded system; Automaton; Artificial intelligence; Machine learning","score_opus":0.015751810129448214,"score_gpt":0.28147534086640064,"score_spread":0.26572353073695243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1977849109","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22760122,0.0005268471,0.7428642,0.00021722435,0.00019416977,0.0001922564,0.00014041144,0.0033076783,0.024956062],"genre_scores_gemma":[0.9437624,0.00007146128,0.054194905,0.00003228984,0.00000955659,0.00007846009,0.000042147843,0.000015413783,0.0017932431],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998012,0.00004585243,0.00001715918,0.00003728914,0.00006117748,0.000037361366],"domain_scores_gemma":[0.99979633,0.00007204483,0.00002984235,0.00003387016,0.000052227217,0.000015753898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018007608,0.00033041218,0.00032802808,0.00025133844,0.00025583562,0.00048296436,0.0007152287,0.00033385755,0.0026761757],"category_scores_gemma":[0.00043409097,0.00013218206,0.00024731067,0.00014941039,0.00020273338,0.0003024372,0.0002280372,0.00032324166,0.00024914366],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043871455,0.00022749232,0.003497586,0.00033716,0.000110921865,0.00050370063,0.0001683057,0.77260697,0.036580212,0.027571328,0.001861077,0.15609644],"study_design_scores_gemma":[0.0000731728,0.00028489277,0.00054473145,0.000014761639,0.000022822143,0.00011351949,0.00001742095,0.9813985,0.012747775,0.001953179,0.0028164727,0.000012760449],"about_ca_topic_score_codex":0.0026071996,"about_ca_topic_score_gemma":0.002291337,"teacher_disagreement_score":0.0026761757,"about_ca_system_score_codex":0.0004313175,"about_ca_system_score_gemma":0.00051024434,"threshold_uncertainty_score":0.008952737},"labels":[],"label_agreement":null},{"id":"W1979499253","doi":"","title":"Dynamic optimality for skip lists and B-trees","year":2008,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Upper and lower bounds; Binary tree; Computer science; Binary search tree; Tree (set theory); Set (abstract data type); Weight-balanced tree; Branching (polymer chemistry); Combinatorics; Class (philosophy); Sequence (biology); Optimal binary search tree; Context (archaeology); Search tree; Ternary search tree; Binary number; Binary decision diagram; Discrete mathematics; Theoretical computer science; Mathematics; Interval tree; Algorithm; Search algorithm; Tree structure; Arithmetic; Artificial intelligence","score_opus":0.02942393810886324,"score_gpt":0.2859440844393497,"score_spread":0.2565201463304865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979499253","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16635838,0.0014840674,0.8059504,0.00096751994,0.00007509875,0.000097543794,0.0007725506,0.0012091156,0.02308538],"genre_scores_gemma":[0.5830116,0.0013873202,0.40230203,0.00048633365,0.00015293859,0.00035969424,0.00148214,0.0008473013,0.009970571],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986078,0.00024722915,0.000105845305,0.00029038906,0.00047546905,0.00027329056],"domain_scores_gemma":[0.9954104,0.0027448742,0.00036834972,0.0008227515,0.000445821,0.00020788374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015547904,0.0005319803,0.00087467226,0.0011459723,0.0010755244,0.0021977914,0.0015361396,0.0011855537,0.007041266],"category_scores_gemma":[0.011118677,0.0005734261,0.0006697525,0.0019963547,0.0013037979,0.005881113,0.0020340716,0.0019344221,0.0014663523],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045706163,0.00018050683,0.002130619,0.0003413281,0.0000438308,0.000110316374,0.00034233136,0.12728745,0.013427773,0.72633743,0.00854112,0.12080032],"study_design_scores_gemma":[0.000046901514,0.00013097013,0.0006500589,0.00006038699,0.000027116981,0.00014795695,0.00008828058,0.29290298,0.0070243636,0.6897675,0.009122677,0.00003079014],"about_ca_topic_score_codex":0.0014463692,"about_ca_topic_score_gemma":0.0016122458,"teacher_disagreement_score":0.007041266,"about_ca_system_score_codex":0.0014933862,"about_ca_system_score_gemma":0.0011422009,"threshold_uncertainty_score":0.023555398},"labels":[],"label_agreement":null},{"id":"W1980155648","doi":"10.1016/j.tcs.2004.07.031","title":"Optimal graph exploration without good maps","year":2004,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":66,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Graph; Computer science; Mathematics; Theoretical computer science","score_opus":0.018372535556696407,"score_gpt":0.2655600713819139,"score_spread":0.2471875358252175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980155648","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27043986,0.002718221,0.67383534,0.0034280866,0.00026401674,0.00017772235,0.00068812806,0.0021640733,0.046284545],"genre_scores_gemma":[0.8183689,0.00064363825,0.167105,0.00035076315,0.00007684183,0.00017183356,0.00035962462,0.00038944161,0.012533957],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993705,0.0002989564,0.00002002923,0.000115475035,0.00010360221,0.000091367954],"domain_scores_gemma":[0.9962872,0.002833652,0.00011193226,0.00048076984,0.00012540196,0.00016102222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007855304,0.0008761737,0.0014357748,0.0011085522,0.0009116104,0.0013571377,0.001106535,0.0019234867,0.007158639],"category_scores_gemma":[0.008353266,0.0008537308,0.00092971924,0.0011877521,0.0013230634,0.0043126806,0.002896153,0.0017545994,0.00068403385],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001419179,0.0002370657,0.0012680008,0.000714373,0.00016074565,0.0002441759,0.00045563388,0.5891887,0.005097709,0.25709802,0.016396588,0.12771975],"study_design_scores_gemma":[0.00011075407,0.00010264835,0.00029308337,0.000043914442,0.000049059297,0.00010128551,0.00009332078,0.63634396,0.001638354,0.35817206,0.0030349323,0.000016655616],"about_ca_topic_score_codex":0.0017121377,"about_ca_topic_score_gemma":0.0023949607,"teacher_disagreement_score":0.007158639,"about_ca_system_score_codex":0.0007378873,"about_ca_system_score_gemma":0.000985596,"threshold_uncertainty_score":0.023948014},"labels":[],"label_agreement":null},{"id":"W1981392728","doi":"10.1007/s00446-014-0234-3","title":"Localization for a system of colliding robots","year":2014,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Position (finance); Conjecture; Ring (chemistry); Mobile robot; Energy (signal processing); Motion (physics); Trajectory; Momentum (technical analysis); Physics; Topology (electrical circuits); Computer science; Mathematics; Control theory (sociology); Combinatorics; Classical mechanics; Artificial intelligence; Quantum mechanics; Control (management)","score_opus":0.017592758448582733,"score_gpt":0.2551770093600642,"score_spread":0.23758425091148147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981392728","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056988213,0.00041840124,0.9397937,0.0007128589,0.000046273148,0.000032524607,0.00005756963,0.00017492223,0.0017755354],"genre_scores_gemma":[0.81648964,0.00057105,0.17292087,0.00011607244,0.00012388024,0.00019375661,0.00015441953,0.0000867393,0.009343608],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923337,0.00022982372,0.00004310068,0.00023065857,0.00014945919,0.00011354803],"domain_scores_gemma":[0.997619,0.0016182199,0.00029421868,0.00010616781,0.0002479851,0.000114493894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013359624,0.00084530225,0.0013378863,0.0011373769,0.001358751,0.0016657964,0.0016786396,0.0023950043,0.002527987],"category_scores_gemma":[0.0067961863,0.00072587194,0.00078388385,0.0017349487,0.0021285505,0.0021183516,0.0026400466,0.001024874,0.00037475204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017457212,0.00003493581,0.000791873,0.00011012163,0.000041234063,0.00017441504,0.00014522088,0.95360535,0.001314453,0.029820122,0.00062896515,0.013158823],"study_design_scores_gemma":[0.000025409377,0.000025315845,0.00011044248,0.0000043685177,0.000009961422,0.000029157676,0.000028491451,0.9808357,0.00019354591,0.018536689,0.00019335552,0.000007571619],"about_ca_topic_score_codex":0.0076442673,"about_ca_topic_score_gemma":0.004302157,"teacher_disagreement_score":0.0076442673,"about_ca_system_score_codex":0.0012822077,"about_ca_system_score_gemma":0.0010257902,"threshold_uncertainty_score":0.015199542},"labels":[],"label_agreement":null},{"id":"W1981643246","doi":"10.2200/s00278ed1v01y201004dct001","title":"The Mobile Agent Rendezvous Problem in the Ring","year":2010,"lang":"en","type":"article","venue":"Synthesis lectures on distributed computing theory","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Rendezvous; Computer science; Robotics; Artificial intelligence; Mobile agent; Ring (chemistry); Distributed computing; Mobile robot; Collective intelligence; Multi-agent system; Engineering; Robot; Aerospace engineering","score_opus":0.009257801723203448,"score_gpt":0.2502785384484939,"score_spread":0.24102073672529045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981643246","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23488674,0.0054184655,0.66778064,0.007250919,0.0006270272,0.00014750141,0.00036856844,0.00031981067,0.083200365],"genre_scores_gemma":[0.89752,0.0026048175,0.06637199,0.00020695003,0.0003850763,0.0001458556,0.00013753709,0.00010554552,0.0325222],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993703,0.0002340146,0.000019952471,0.00016730792,0.00010052227,0.00010803139],"domain_scores_gemma":[0.9987394,0.00082959357,0.00010977837,0.000108454304,0.00006150097,0.00015123056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011183743,0.0005095787,0.0014413594,0.00038712705,0.0014697214,0.0025872595,0.0012993327,0.0019439296,0.0058630146],"category_scores_gemma":[0.0033002603,0.0004461648,0.0006296779,0.0006565202,0.0019650438,0.0038574885,0.0016305426,0.0019419314,0.0006219563],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003284673,0.000042478554,0.0002072706,0.00014724988,0.00003531881,0.00015885927,0.00020294377,0.118504345,0.0022891916,0.85630196,0.005404657,0.016377304],"study_design_scores_gemma":[0.00011332036,0.00007286842,0.00019239784,0.000033378743,0.00002856345,0.00012248215,0.0002602645,0.3206053,0.0014688933,0.66605866,0.0110118985,0.000031880154],"about_ca_topic_score_codex":0.0015552294,"about_ca_topic_score_gemma":0.0010232189,"teacher_disagreement_score":0.0058630146,"about_ca_system_score_codex":0.0010714614,"about_ca_system_score_gemma":0.000834151,"threshold_uncertainty_score":0.019613743},"labels":[],"label_agreement":null},{"id":"W1981710280","doi":"10.1145/1077464.1077467","title":"A maiden analysis of longest wait first","year":2005,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Multicast; Scheduling (production processes); Computer science; Competitive analysis; Combinatorics; Mathematics; Distributed computing; Mathematical optimization","score_opus":0.025029759575546602,"score_gpt":0.2748734465406962,"score_spread":0.24984368696514958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981710280","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.045016456,0.006702941,0.85695356,0.0055057467,0.0005147225,0.0001944699,0.00056402665,0.001070456,0.08347771],"genre_scores_gemma":[0.6832012,0.007188313,0.22784585,0.0033737195,0.0020827565,0.0010266084,0.0010522138,0.0018236869,0.07240562],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977653,0.0005136454,0.00007324868,0.00035608624,0.00070675806,0.00058496016],"domain_scores_gemma":[0.98848337,0.008051382,0.00085556775,0.0006945694,0.0012089086,0.00070612016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046323426,0.0023722292,0.0019911474,0.0029227827,0.0023571365,0.003304322,0.0044508595,0.0020823912,0.024697045],"category_scores_gemma":[0.024715126,0.0010743974,0.0016812122,0.0025329406,0.0023435426,0.008018826,0.0023494374,0.004851244,0.0035020607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005041678,0.00016114708,0.0010472215,0.000480175,0.00013181448,0.0001490401,0.00034016013,0.19440739,0.004331013,0.73684305,0.018120596,0.043484163],"study_design_scores_gemma":[0.00006118338,0.00012859423,0.00025415092,0.00007838477,0.00007430747,0.00008648786,0.000047227928,0.6971189,0.0018699577,0.2895996,0.010645054,0.00003618895],"about_ca_topic_score_codex":0.004638243,"about_ca_topic_score_gemma":0.002854036,"teacher_disagreement_score":0.024697045,"about_ca_system_score_codex":0.0050152787,"about_ca_system_score_gemma":0.0028185023,"threshold_uncertainty_score":0.082619786},"labels":[],"label_agreement":null},{"id":"W1983335618","doi":"10.1016/s0890-5401(03)00081-6","title":"Searching and on-line recognition of star-shaped polygons","year":2003,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Polygon (computer graphics); Star (game theory); Competitive analysis; Combinatorics; Line (geometry); Rectilinear polygon; Visibility polygon; Polygon covering; Path (computing); Computer science; Upper and lower bounds; Mathematics; Artificial intelligence; Monotone polygon; Simple polygon; Geometry","score_opus":0.04476430482108747,"score_gpt":0.29182407910099006,"score_spread":0.2470597742799026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983335618","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1674301,0.00020197811,0.82180583,0.00014793559,0.00004578786,0.000100675905,0.0002652563,0.0012912633,0.008711088],"genre_scores_gemma":[0.6165899,0.00018710464,0.37810197,0.00004529915,0.000020497762,0.000049206756,0.00071192445,0.00025222998,0.004041809],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994586,0.00011416503,0.000039507766,0.00015347092,0.00015974545,0.00007437033],"domain_scores_gemma":[0.9990101,0.0003584547,0.00012298395,0.0002285603,0.0002058233,0.0000741026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004087365,0.00047640028,0.0010818826,0.0008636284,0.00048453745,0.0018854198,0.0013592377,0.0010600686,0.0036495794],"category_scores_gemma":[0.0028958363,0.00040431012,0.0006753873,0.0011957791,0.0007972733,0.0021033469,0.0012814258,0.0006624316,0.0009356893],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096301694,0.00024303318,0.005159124,0.00028269048,0.000064300606,0.0005909411,0.0006507833,0.37699586,0.032638613,0.05799201,0.0061876937,0.51823187],"study_design_scores_gemma":[0.000012369794,0.000048111146,0.00039446264,0.000011143144,0.000007542417,0.0001096147,0.00012506066,0.97322524,0.009069859,0.01512613,0.0018592004,0.000011272388],"about_ca_topic_score_codex":0.0025977027,"about_ca_topic_score_gemma":0.0023332303,"teacher_disagreement_score":0.0036495794,"about_ca_system_score_codex":0.00045167387,"about_ca_system_score_gemma":0.00054670253,"threshold_uncertainty_score":0.012209117},"labels":[],"label_agreement":null},{"id":"W1983693678","doi":"10.1016/j.tcs.2010.01.004","title":"Fast radio broadcasting with advice","year":2010,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Engineering and Physical Sciences Research Council; Agence Nationale de la Recherche","keywords":"Broadcasting (networking); Advice (programming); Computer science; Constant (computer programming); Radio broadcasting; Radio networks; Computer network; Broadcast communication network; Theoretical computer science; Telecommunications; Wireless network; Wireless","score_opus":0.006882577268605463,"score_gpt":0.23766120430507173,"score_spread":0.23077862703646626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983693678","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059586935,0.002003742,0.88616437,0.0022724965,0.00085867575,0.0002561554,0.00044395553,0.006277131,0.042136487],"genre_scores_gemma":[0.7335624,0.00076449005,0.23263536,0.00081289874,0.00076825183,0.0002791459,0.00042939783,0.0004945224,0.03025359],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99798703,0.00066251424,0.000071594404,0.00029551893,0.0006314711,0.00035185297],"domain_scores_gemma":[0.9895459,0.0071274405,0.00029328582,0.001840755,0.0009346818,0.00025796602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015920738,0.0009650909,0.0016699226,0.0015861893,0.001394549,0.001574658,0.0014442275,0.001954065,0.010555607],"category_scores_gemma":[0.017158462,0.00060861284,0.0006513722,0.001526987,0.0012743608,0.0017080276,0.0020688185,0.0017568258,0.0026409482],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004362962,0.000295591,0.0024614932,0.00073543197,0.00024723026,0.0005862908,0.0007962119,0.17069292,0.02975047,0.1602986,0.05279078,0.576982],"study_design_scores_gemma":[0.0007233426,0.0003256153,0.0007039821,0.00008306877,0.00018510534,0.00061637553,0.00015281148,0.8053223,0.010334671,0.16166191,0.019832512,0.00005830327],"about_ca_topic_score_codex":0.0036678135,"about_ca_topic_score_gemma":0.0053754277,"teacher_disagreement_score":0.010555607,"about_ca_system_score_codex":0.0009598859,"about_ca_system_score_gemma":0.001927139,"threshold_uncertainty_score":0.035311997},"labels":[],"label_agreement":null},{"id":"W1983997639","doi":"10.1145/2090236.2090246","title":"Paging for multi-core shared caches","year":2012,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paging; Computer science; Cache; CPU cache; Core (optical fiber); Multi-core processor; Metric (unit); Competitive analysis; Parallel computing; Cache algorithms; Computer network; Distributed computing; Upper and lower bounds; Telecommunications","score_opus":0.2318437048557492,"score_gpt":0.3587837408272864,"score_spread":0.12694003597153722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1983997639","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15220009,0.0014333982,0.8351448,0.0009176684,0.00012702934,0.00011918427,0.00016619086,0.00046023726,0.009431395],"genre_scores_gemma":[0.92922205,0.0003568297,0.06484887,0.00013468493,0.000053403637,0.000074439835,0.00011462447,0.000070330774,0.005124804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99881834,0.0003955373,0.000052095333,0.00020649997,0.00027344748,0.00025397193],"domain_scores_gemma":[0.99770796,0.001053996,0.0001873798,0.0005166206,0.00034936954,0.00018476069],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011614182,0.00044439902,0.0012334472,0.00036198704,0.00068138633,0.0017697471,0.0020842499,0.0013138953,0.0028262632],"category_scores_gemma":[0.0044097346,0.0004029369,0.00062252,0.0008566231,0.00072547054,0.0026095642,0.0012304696,0.0013783625,0.00031988966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033119458,0.00016141536,0.0011177625,0.00020489657,0.00006507939,0.0001919954,0.0001412737,0.7553679,0.0054747392,0.17801863,0.0052269306,0.0536982],"study_design_scores_gemma":[0.000011180629,0.000042006028,0.00009586186,0.000005519106,0.000006744824,0.000043185795,0.000018853258,0.96448773,0.00070270186,0.033726197,0.00085491984,0.0000050797275],"about_ca_topic_score_codex":0.0027049517,"about_ca_topic_score_gemma":0.0029044833,"teacher_disagreement_score":0.0028262632,"about_ca_system_score_codex":0.0017901575,"about_ca_system_score_gemma":0.001282907,"threshold_uncertainty_score":0.012988508},"labels":[],"label_agreement":null},{"id":"W1984231426","doi":"10.1145/1711475.1714372","title":"On Developing New Models, with Paging as a Case Study","year":2010,"lang":"en","type":"article","venue":"ACM SIGACT News","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Paging; Contrast (vision); Cache; Theoretical computer science; Computation; Data science; Artificial intelligence; Algorithm; Parallel computing","score_opus":0.054009181967706786,"score_gpt":0.30892744113052567,"score_spread":0.2549182591628189,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984231426","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004204426,0.0040964573,0.94212824,0.011095885,0.0006275953,0.00017424634,0.00030882587,0.00030271287,0.0370616],"genre_scores_gemma":[0.22925441,0.014440233,0.7144022,0.005886181,0.0044298586,0.0015900625,0.00077703805,0.0009421474,0.028277868],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98519796,0.007737561,0.00093871565,0.0019625423,0.0032024996,0.00096070266],"domain_scores_gemma":[0.96577215,0.023391485,0.0022554528,0.004339658,0.00327338,0.00096791075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013278741,0.0027460062,0.0018855571,0.0047689923,0.0023134428,0.011401235,0.008309741,0.0065662554,0.014642464],"category_scores_gemma":[0.04180233,0.0014986235,0.003397502,0.006324686,0.010932248,0.027408993,0.006358724,0.011639843,0.003790543],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014555149,0.000037658396,0.0002769918,0.00014245865,0.000014823156,0.000046110916,0.00017255459,0.013197985,0.000090821195,0.9743397,0.0037889783,0.007877285],"study_design_scores_gemma":[0.000012726394,0.000048230133,0.00014213922,0.00014809347,0.000023125363,0.000119563854,0.00017342005,0.08797617,0.00021775844,0.8849065,0.026199356,0.00003303243],"about_ca_topic_score_codex":0.0049282927,"about_ca_topic_score_gemma":0.004563726,"teacher_disagreement_score":0.014642464,"about_ca_system_score_codex":0.0066883136,"about_ca_system_score_gemma":0.0034144612,"threshold_uncertainty_score":0.07022554},"labels":[],"label_agreement":null},{"id":"W1984719907","doi":"10.1007/s00446-006-0154-y","title":"Searching for a black hole in arbitrary networks: optimal mobile agents protocols","year":2006,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":98,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Asynchronous communication; Node (physics); Ignorance; Computer science; Mathematical proof; Upper and lower bounds; Protocol (science); Topology (electrical circuits); Flexibility (engineering); Degree (music); Constructive; Mathematics; Computer network; Discrete mathematics; Combinatorics","score_opus":0.025111813245434718,"score_gpt":0.3120113948574338,"score_spread":0.2868995816119991,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1984719907","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06756887,0.0011153618,0.9222708,0.0021118987,0.00013149552,0.00010807226,0.000042415442,0.00019209969,0.006458954],"genre_scores_gemma":[0.75338537,0.0009599434,0.24101007,0.0002981804,0.00015339156,0.0002469492,0.000058231366,0.0001225397,0.0037653206],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981604,0.0010162502,0.00007370037,0.00026307398,0.00027761125,0.00020898496],"domain_scores_gemma":[0.9909146,0.0067196335,0.0007891433,0.00070019753,0.0004401555,0.00043628353],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049474365,0.0011448337,0.0022240586,0.0015600326,0.0017462457,0.0029303061,0.0033028538,0.003342548,0.0018306734],"category_scores_gemma":[0.01923596,0.0010408107,0.0008657154,0.0017054772,0.004449083,0.0067624133,0.004269706,0.0023518754,0.00025102997],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006295367,0.000117796066,0.0004105656,0.00014671005,0.00012378496,0.00008766325,0.00028655896,0.60973954,0.0012480909,0.36068106,0.0028433546,0.023685303],"study_design_scores_gemma":[0.0000843727,0.00003835392,0.000039717455,0.000016096534,0.000025454225,0.00001945145,0.000044058113,0.82317924,0.00037595624,0.17555529,0.0006113939,0.0000107348405],"about_ca_topic_score_codex":0.0013084225,"about_ca_topic_score_gemma":0.0013532632,"teacher_disagreement_score":0.0049474365,"about_ca_system_score_codex":0.0017152458,"about_ca_system_score_gemma":0.0017116765,"threshold_uncertainty_score":0.02616489},"labels":[],"label_agreement":null},{"id":"W1985522690","doi":"10.1016/j.dam.2008.11.011","title":"Edge searching weighted graphs","year":2009,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Combinatorics; Pathwidth; Graph; Enhanced Data Rates for GSM Evolution; Monotonic function; Edge cover; Discrete mathematics; Line graph; Computer science; Artificial intelligence","score_opus":0.017714882409356578,"score_gpt":0.2656131470015109,"score_spread":0.2478982645921543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985522690","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0824259,0.0008794393,0.86816895,0.0012159786,0.00016949727,0.00017274359,0.00076646724,0.00042599626,0.045775052],"genre_scores_gemma":[0.4822121,0.0016016056,0.43715003,0.0005002359,0.00015629377,0.0003225044,0.0017172233,0.0003957256,0.07594433],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999564,0.0001426367,0.00002168148,0.000121469246,0.00009556004,0.000054617856],"domain_scores_gemma":[0.99852353,0.0007544761,0.00012325954,0.0002344766,0.00020949407,0.00015475553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053470995,0.00063002907,0.00072493526,0.0011009135,0.0005895931,0.0013169309,0.0014809408,0.001210254,0.013412194],"category_scores_gemma":[0.0044407714,0.0004025875,0.0005883536,0.0017843498,0.00053485396,0.0027461383,0.0013386473,0.0017066436,0.0016070114],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003042771,0.00026130083,0.0009672397,0.00041051232,0.00009643223,0.00015452062,0.00013983305,0.10342709,0.0070012845,0.6009519,0.018281525,0.26800415],"study_design_scores_gemma":[0.000049409125,0.00011407766,0.00045365558,0.000055605808,0.000066662986,0.00020401752,0.000065646374,0.30250084,0.004359176,0.6740726,0.018040031,0.00001816669],"about_ca_topic_score_codex":0.00071228575,"about_ca_topic_score_gemma":0.0010254312,"teacher_disagreement_score":0.013412194,"about_ca_system_score_codex":0.000533933,"about_ca_system_score_gemma":0.0005439392,"threshold_uncertainty_score":0.04486829},"labels":[],"label_agreement":null},{"id":"W1985734068","doi":"10.1016/j.tcs.2014.02.026","title":"The Covering Canadian Traveller Problem","year":2014,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Travelling salesman problem; Shortest path problem; Routing (electronic design automation); Competitive analysis; Computer science; Mathematical optimization; A priori and a posteriori; Set (abstract data type); Path (computing); Variation (astronomy); Operations research; Mathematics; Upper and lower bounds; Theoretical computer science; Computer network","score_opus":0.006748960221634481,"score_gpt":0.21944515269249248,"score_spread":0.212696192470858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1985734068","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22209284,0.004720232,0.21807402,0.017486067,0.00079290726,0.0005723504,0.0106861135,0.00096790533,0.5246076],"genre_scores_gemma":[0.7864528,0.003470665,0.0551734,0.0010554257,0.00028421357,0.00030219255,0.005674022,0.0004125231,0.14717478],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989814,0.00027676165,0.000026378639,0.00019463869,0.00019624234,0.00032447686],"domain_scores_gemma":[0.9985298,0.00062236097,0.00008657572,0.0001592016,0.000243907,0.00035816876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008928372,0.0010730072,0.0015962473,0.0012851721,0.0034299889,0.003894301,0.002810904,0.0038304743,0.043243814],"category_scores_gemma":[0.0059073265,0.00056249887,0.0007967117,0.0041499212,0.0021331648,0.004502657,0.001851595,0.0025714124,0.002219794],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044816744,0.00013022666,0.0009283996,0.00031174946,0.00008160039,0.00025366852,0.00035099,0.089176066,0.00038268554,0.71634215,0.13359438,0.05799989],"study_design_scores_gemma":[0.00020350498,0.00008853331,0.0010934516,0.00014832919,0.00008012358,0.00033129353,0.0010905092,0.27355775,0.00064408954,0.60296404,0.11969545,0.00010287267],"about_ca_topic_score_codex":0.2961692,"about_ca_topic_score_gemma":0.24544813,"teacher_disagreement_score":0.70383084,"about_ca_system_score_codex":0.008870214,"about_ca_system_score_gemma":0.009082076,"threshold_uncertainty_score":0.58889055},"labels":[],"label_agreement":null},{"id":"W1986121630","doi":"10.1109/ssrr.2009.5424167","title":"Market-based dynamic task allocation in mobile surveillance systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Task (project management); Distributed computing; Mobile robot; Set (abstract data type); Tree (set theory); Mobile telephony; Volume (thermodynamics); Mobile computing; Real-time computing; Robot; Artificial intelligence; Computer network; Mobile radio; Engineering","score_opus":0.007869853526240122,"score_gpt":0.24824548131929575,"score_spread":0.24037562779305563,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1986121630","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10013831,0.0008335294,0.8895625,0.0005109654,0.00007174715,0.00014377983,0.00010665386,0.00031633422,0.008316158],"genre_scores_gemma":[0.95554376,0.0002682847,0.040608898,0.00007096028,0.00003895072,0.00012272969,0.000059795817,0.00004365062,0.0032429092],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991216,0.00035149022,0.000031521307,0.00014674723,0.00016788846,0.00018069679],"domain_scores_gemma":[0.9986382,0.00077449635,0.00019757389,0.0000758548,0.00018496365,0.00012884596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018232699,0.0005354423,0.001176946,0.0005417415,0.0005852732,0.0010966486,0.0014274082,0.00090647716,0.0035283673],"category_scores_gemma":[0.003220073,0.0003736595,0.00038179586,0.00086914294,0.00088166876,0.0018763989,0.0008543985,0.0006237012,0.00035502497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016291285,0.000077662655,0.00035070445,0.00007874886,0.000028209859,0.00009910619,0.000058040798,0.9370694,0.0018089969,0.029378025,0.0014051462,0.029482989],"study_design_scores_gemma":[0.00002276677,0.000042859963,0.00016138601,0.0000031575462,0.000004904571,0.000026095162,0.000017766239,0.98837507,0.00023235839,0.010428841,0.000677571,0.000007219869],"about_ca_topic_score_codex":0.0042437487,"about_ca_topic_score_gemma":0.0033267397,"teacher_disagreement_score":0.0042437487,"about_ca_system_score_codex":0.0012175471,"about_ca_system_score_gemma":0.001051755,"threshold_uncertainty_score":0.011803508},"labels":[],"label_agreement":null},{"id":"W1988381536","doi":"10.1007/s00453-013-9800-5","title":"Parameterized Analysis of Paging and List Update Algorithms","year":2013,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Parameterized complexity; Computer science; Paging; Locality; Algorithm; Cache; Theory of computation; Locality of reference; Online algorithm; Cache algorithms; Set (abstract data type); Memory hierarchy; CPU cache; Theoretical computer science; Parallel computing","score_opus":0.011120576140118882,"score_gpt":0.2412701161776356,"score_spread":0.23014954003751673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988381536","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08151815,0.0024252844,0.88591653,0.0033150609,0.00021599034,0.00020974608,0.00090983906,0.0013881621,0.02410121],"genre_scores_gemma":[0.81353325,0.0022809214,0.15871984,0.00064960454,0.0007538736,0.00051726523,0.001825966,0.0014982033,0.020221185],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99442494,0.0023613803,0.00022389714,0.00068632583,0.0012924164,0.0010109785],"domain_scores_gemma":[0.9602628,0.029759312,0.0022374594,0.0047546327,0.0019880421,0.0009977712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005574713,0.0018264124,0.002491791,0.0022133263,0.0016819759,0.0066159633,0.0057735336,0.0028835451,0.019086719],"category_scores_gemma":[0.052286357,0.0014247036,0.0021094359,0.004546235,0.0026203715,0.013013201,0.0032140054,0.004634555,0.0016852667],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00052306225,0.0003292169,0.00244101,0.0003042608,0.00013154643,0.00011167523,0.00031301938,0.44386855,0.0015998104,0.48427865,0.01457787,0.051521316],"study_design_scores_gemma":[0.000040680752,0.00003611223,0.00039188968,0.000026296095,0.0000519613,0.000040385425,0.000040618568,0.79813606,0.0005355113,0.19898728,0.0016953935,0.000017730172],"about_ca_topic_score_codex":0.0048154597,"about_ca_topic_score_gemma":0.0042350106,"teacher_disagreement_score":0.019086719,"about_ca_system_score_codex":0.0060185473,"about_ca_system_score_gemma":0.005012272,"threshold_uncertainty_score":0.063851416},"labels":[],"label_agreement":null},{"id":"W1988551609","doi":"10.1002/net.21453","title":"Deterministic rendezvous in networks: A comprehensive survey","year":2012,"lang":"en","type":"article","venue":"Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":112,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Computer science; Task (project management); Graph; Terrain; Undirected graph; Theoretical computer science; Mathematical optimization; Operations research; Mathematics; Geography; Engineering","score_opus":0.04834175643551917,"score_gpt":0.2885700570184015,"score_spread":0.24022830058288233,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988551609","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0152222635,0.6943859,0.24252656,0.0021215412,0.00045772543,0.00007253445,0.00037102113,0.00019022515,0.04465221],"genre_scores_gemma":[0.23106787,0.7000549,0.059445225,0.00048019466,0.0015415716,0.00016172395,0.00063389627,0.00012111559,0.006493522],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990289,0.00026144678,0.000071930845,0.00023590933,0.00030277466,0.00009900468],"domain_scores_gemma":[0.99751675,0.0019241548,0.00014409488,0.00013079225,0.00022687539,0.00005726191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014919555,0.0010657274,0.0015938568,0.0021323976,0.00060167507,0.0022043923,0.0016046483,0.0012111835,0.0025207049],"category_scores_gemma":[0.003499244,0.00080047286,0.0008850873,0.0043658586,0.0011746158,0.0035066314,0.0014031142,0.0011802927,0.0008368288],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011618388,0.00018490276,0.0032116594,0.006451476,0.00025648717,0.00021985173,0.00020256743,0.23242925,0.0009554238,0.2961106,0.01660085,0.44326082],"study_design_scores_gemma":[0.000043858105,0.00023686877,0.0030044594,0.0020733112,0.00019971542,0.0010141317,0.00034267316,0.26758084,0.0015147548,0.46204096,0.26185,0.000098418706],"about_ca_topic_score_codex":0.0025165922,"about_ca_topic_score_gemma":0.0017705811,"teacher_disagreement_score":0.0025207049,"about_ca_system_score_codex":0.0014429773,"about_ca_system_score_gemma":0.001146521,"threshold_uncertainty_score":0.010469615},"labels":[],"label_agreement":null},{"id":"W1988889787","doi":"10.1007/s00453-006-0074-2","title":"Deterministic Rendezvous in Graphs","year":2006,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":179,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Computer science; Theory of computation; Time complexity; Binary logarithm; Graph; Identifier; Upper and lower bounds; Node (physics); Combinatorics; Mathematics; Discrete mathematics; Algorithm; Theoretical computer science; Computer network","score_opus":0.00716953051749322,"score_gpt":0.2238464719368621,"score_spread":0.21667694141936888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1988889787","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42270574,0.002419023,0.52226746,0.004065999,0.00022631048,0.00023901783,0.00080962514,0.0012328314,0.046034],"genre_scores_gemma":[0.9064116,0.00091071473,0.071777865,0.00025379515,0.00008441443,0.00018620005,0.0004800956,0.00041226656,0.019483035],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983359,0.00056497625,0.000065183995,0.00045801827,0.00025505747,0.00032087014],"domain_scores_gemma":[0.9909333,0.006552436,0.00060419185,0.0010377073,0.00033773837,0.0005346468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014528213,0.000985904,0.001994446,0.0014264189,0.0027806023,0.0032829032,0.0030405226,0.0024342556,0.0090445215],"category_scores_gemma":[0.012732415,0.0012891914,0.0011195105,0.002264237,0.004251047,0.006404631,0.0036776895,0.0026540528,0.0010824389],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005716782,0.00010766837,0.0011533909,0.0003161156,0.00010439996,0.00022456906,0.0006130697,0.30576932,0.0019246505,0.64876115,0.0077695013,0.032684457],"study_design_scores_gemma":[0.00009859689,0.000034498917,0.0002158011,0.000034262317,0.000037117974,0.000093682305,0.00021603791,0.2950231,0.001242269,0.6996757,0.0033059886,0.00002299522],"about_ca_topic_score_codex":0.006154896,"about_ca_topic_score_gemma":0.007691697,"teacher_disagreement_score":0.0090445215,"about_ca_system_score_codex":0.0023291626,"about_ca_system_score_gemma":0.0015226969,"threshold_uncertainty_score":0.030256987},"labels":[],"label_agreement":null},{"id":"W1989886714","doi":"10.1016/j.dam.2007.08.045","title":"Digraph searching, directed vertex separation and directed pathwidth","year":2007,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Digraph; Vertex (graph theory); Mathematics; Directed graph; Directed acyclic graph; Combinatorics; Strongly connected component; Graph","score_opus":0.01467820838175314,"score_gpt":0.2815725775623087,"score_spread":0.26689436918055554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989886714","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058947958,0.0027849465,0.92362785,0.0012302534,0.000117680516,0.000111299465,0.00058355526,0.00053305115,0.012063437],"genre_scores_gemma":[0.39943814,0.0033611024,0.58083016,0.00042577815,0.00017695616,0.00019209362,0.0012511166,0.00026957103,0.014055077],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999198,0.00024943418,0.000038031645,0.00022337587,0.00018780146,0.000103325045],"domain_scores_gemma":[0.99507916,0.0037756225,0.0004221999,0.00029448062,0.00019324744,0.00023527937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010917339,0.00085250207,0.001413702,0.0019266071,0.0009719761,0.0021970982,0.0023715554,0.0016514637,0.004931045],"category_scores_gemma":[0.009258871,0.00079794327,0.00072894216,0.004526046,0.0012937117,0.00553163,0.0018272322,0.0022228146,0.0005426578],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054644234,0.0003581446,0.0023810433,0.0007761965,0.00012724432,0.00015369382,0.00021901137,0.34685096,0.0038545048,0.39289433,0.012726364,0.23911208],"study_design_scores_gemma":[0.00008479108,0.00008681309,0.00037001588,0.000064936714,0.000059873644,0.0002000926,0.000082095525,0.5504742,0.001834549,0.4411597,0.0055580093,0.000024913294],"about_ca_topic_score_codex":0.0039147492,"about_ca_topic_score_gemma":0.0056524635,"teacher_disagreement_score":0.004931045,"about_ca_system_score_codex":0.0015015897,"about_ca_system_score_gemma":0.0017553412,"threshold_uncertainty_score":0.016495943},"labels":[],"label_agreement":null},{"id":"W1989900196","doi":"10.1007/s10878-007-9121-1","title":"Standard directed search strategies and their applications","year":2007,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Digraph; Directed acyclic graph; Directed graph; Computer science; Theory of computation; Search problem; Upper and lower bounds; Combinatorics; Theoretical computer science; Mathematics; Discrete mathematics; Algorithm","score_opus":0.01290475218289373,"score_gpt":0.2732350615311445,"score_spread":0.2603303093482508,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989900196","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007973875,0.0047168066,0.96428585,0.0003849209,0.00020618387,0.00008277064,0.00008715882,0.00027846254,0.02198393],"genre_scores_gemma":[0.3081075,0.012050001,0.6367476,0.0006870007,0.0004576391,0.00069419487,0.000359936,0.00047102603,0.040425055],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99879444,0.0004770819,0.00007413375,0.00016228427,0.00041525243,0.000076726996],"domain_scores_gemma":[0.9964252,0.0024767548,0.00015585929,0.00034351673,0.00048331948,0.000115306684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024387306,0.0013001789,0.0012211069,0.0023707964,0.0007423289,0.0020300883,0.0026418653,0.0021108405,0.0048416564],"category_scores_gemma":[0.011556918,0.0005793919,0.000811265,0.0038285572,0.0016877353,0.0028204126,0.0023013053,0.0018671127,0.0015330826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008001367,0.000121979516,0.00029024458,0.00022425284,0.000057568126,0.000066306144,0.00012681105,0.067246616,0.00069589354,0.727343,0.007002237,0.19674501],"study_design_scores_gemma":[0.000031810225,0.00004908789,0.00007216258,0.000055680866,0.000027061456,0.00007821185,0.000030425927,0.29613602,0.0006360777,0.6931871,0.009677772,0.00001864453],"about_ca_topic_score_codex":0.0014550741,"about_ca_topic_score_gemma":0.0014107474,"teacher_disagreement_score":0.0048416564,"about_ca_system_score_codex":0.0011864242,"about_ca_system_score_gemma":0.0011368884,"threshold_uncertainty_score":0.016196966},"labels":[],"label_agreement":null},{"id":"W1991356098","doi":"10.1016/j.tcs.2013.04.015","title":"Fast–mixed searching and related problems on graphs","year":2013,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Mathematics; Mixed graph; Combinatorics; Search algorithm; Graph; Degree (music); Search problem; Planar graph; Computer science; Discrete mathematics; Algorithm; Line graph","score_opus":0.01041735476262332,"score_gpt":0.23739648023326881,"score_spread":0.2269791254706455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991356098","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12267096,0.004466676,0.8446998,0.004812536,0.00026258256,0.00019720107,0.00085408916,0.00058825826,0.021447867],"genre_scores_gemma":[0.5310046,0.0021818408,0.4293758,0.0010246093,0.0005416881,0.0004529687,0.0012681236,0.0007258244,0.033424597],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99770314,0.0012576331,0.00009091833,0.00042399604,0.00032031038,0.00020413828],"domain_scores_gemma":[0.98131025,0.014965718,0.0010744492,0.0013079556,0.0007317644,0.0006098933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034011914,0.0014983311,0.0025211496,0.0024617421,0.0019983249,0.0040245536,0.0038871637,0.0038044127,0.012342917],"category_scores_gemma":[0.021722605,0.0014840149,0.0015453236,0.0039778203,0.0030528377,0.011554125,0.0034269027,0.0037148776,0.0009120518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005900042,0.00024000158,0.00093016255,0.00077106134,0.0001340567,0.00013202253,0.00030981583,0.20642997,0.0014006273,0.704616,0.014265317,0.07018093],"study_design_scores_gemma":[0.000076260134,0.000057441495,0.00019031564,0.00004366311,0.000030253439,0.000105933585,0.00008797803,0.2831273,0.0006224465,0.71278256,0.0028541957,0.0000216331],"about_ca_topic_score_codex":0.0024184748,"about_ca_topic_score_gemma":0.0026838852,"teacher_disagreement_score":0.012342917,"about_ca_system_score_codex":0.0021909862,"about_ca_system_score_gemma":0.0013163496,"threshold_uncertainty_score":0.041291237},"labels":[],"label_agreement":null},{"id":"W1991761577","doi":"10.1177/1548512913509033","title":"Solving the Impediment Induced Variable Shape Covering Problem","year":2013,"lang":"en","type":"article","venue":"The Journal of Defense Modeling and Simulation Applications Methodology Technology","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Variable (mathematics); Circle packing; Constant (computer programming); Operations research; Mathematical optimization; Norm (philosophy); Mathematics; Geometry; Law","score_opus":0.08250096892388886,"score_gpt":0.33068337045444046,"score_spread":0.2481824015305516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1991761577","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10535493,0.00038222055,0.88354605,0.0005481951,0.00007649968,0.00008846521,0.0002343262,0.00021736314,0.009551988],"genre_scores_gemma":[0.7405345,0.0004583407,0.25087562,0.00017526498,0.00008373662,0.00019913286,0.0005239547,0.00013681347,0.0070125796],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933773,0.0002443622,0.000023447843,0.00013531382,0.00012313463,0.00013591623],"domain_scores_gemma":[0.99814975,0.0013844942,0.00015081918,0.00010297134,0.0001224222,0.00008953244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008507148,0.0007202942,0.0009856406,0.00045067287,0.00034482623,0.0009575266,0.0009864884,0.0014052894,0.0032736592],"category_scores_gemma":[0.0036076063,0.00052736857,0.00076014816,0.0006395924,0.00072578207,0.0010257751,0.0012204865,0.0009510484,0.00029313602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007141899,0.000028387494,0.0006189448,0.00007792953,0.000027983951,0.00012905007,0.000058608595,0.9638481,0.0009381928,0.018441897,0.0012126924,0.014546726],"study_design_scores_gemma":[0.000014064479,0.000034514265,0.00014022205,0.0000063588354,0.0000063643447,0.000038753395,0.000029638206,0.9824187,0.00034142297,0.016174993,0.00078961754,0.000005359121],"about_ca_topic_score_codex":0.004291642,"about_ca_topic_score_gemma":0.002500261,"teacher_disagreement_score":0.004291642,"about_ca_system_score_codex":0.0006631056,"about_ca_system_score_gemma":0.00087228947,"threshold_uncertainty_score":0.010951519},"labels":[],"label_agreement":null},{"id":"W1992712376","doi":"10.1007/s10951-009-0148-2","title":"Characterizing sets of jobs that admit optimal greedy-like algorithms","year":2009,"lang":"en","type":"article","venue":"Journal of Scheduling","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"","keywords":"Greedy algorithm; Computation; Algorithm; Set (abstract data type); Computer science; Mathematics; Combinatorics; Class (philosophy); Mathematical optimization; Discrete mathematics; Artificial intelligence","score_opus":0.0401982384900589,"score_gpt":0.29236549489283614,"score_spread":0.25216725640277726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1992712376","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6866948,0.0007830693,0.29407308,0.0017887553,0.00014881855,0.000408427,0.0010107214,0.00091377326,0.014178569],"genre_scores_gemma":[0.9256913,0.0003042826,0.070058584,0.00036146346,0.00015183612,0.0002549848,0.001006055,0.00025660876,0.0019149175],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9943786,0.001834916,0.00047866642,0.0009957008,0.0012479218,0.0010641658],"domain_scores_gemma":[0.9392808,0.04486195,0.004620148,0.0052511767,0.003033519,0.002952372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053805774,0.0014717004,0.0029119444,0.0024844431,0.0026117258,0.0065297955,0.0037963002,0.0034200605,0.003828499],"category_scores_gemma":[0.049622033,0.0024957897,0.002405298,0.0031597326,0.003494356,0.0056316857,0.003978198,0.0025774671,0.0005454588],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004394504,0.0020733068,0.016358646,0.0008806682,0.0006044968,0.0005226616,0.0013578276,0.4919845,0.01626636,0.40099832,0.012005972,0.05255277],"study_design_scores_gemma":[0.00020247701,0.0004904979,0.002050038,0.00007300751,0.000096861404,0.0003266129,0.00046042545,0.5890932,0.0029808553,0.40285188,0.0013219697,0.000052167514],"about_ca_topic_score_codex":0.00071263814,"about_ca_topic_score_gemma":0.0009476299,"teacher_disagreement_score":0.0065297955,"about_ca_system_score_codex":0.0020352858,"about_ca_system_score_gemma":0.002512068,"threshold_uncertainty_score":0.028455496},"labels":[],"label_agreement":null},{"id":"W1993821074","doi":"10.1142/s0129054107004826","title":"OPTIMAL CONSTRUCTION OF SENSE OF DIRECTION IN A TORUS BY A MOBILE AGENT","year":2007,"lang":"en","type":"article","venue":"International Journal of Foundations of Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Torus; Computer science; Enhanced Data Rates for GSM Evolution; Security token; Compass; Computation; Property (philosophy); Sense (electronics); Orientation (vector space); Task (project management); Mathematics; Algorithm; Artificial intelligence; Geometry; Computer network","score_opus":0.012770053744457445,"score_gpt":0.3117274546573193,"score_spread":0.2989574009128619,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993821074","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12807094,0.00011470108,0.86483234,0.0002846706,0.00008331935,0.00009011736,0.00006585573,0.0006269664,0.005831083],"genre_scores_gemma":[0.4988293,0.0002014233,0.49626082,0.000060795483,0.00002940183,0.00016175328,0.00017861479,0.0001445464,0.0041334406],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936634,0.0002206273,0.000039961244,0.00013695743,0.000093694995,0.00014253751],"domain_scores_gemma":[0.99855024,0.00044716327,0.0002234351,0.00039978774,0.0001729694,0.00020634574],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000954121,0.0005085529,0.0007542702,0.0004058221,0.0009374745,0.0012180436,0.000925466,0.00066781294,0.0018072132],"category_scores_gemma":[0.0032032733,0.00043546074,0.00053891685,0.0005874122,0.0014399044,0.0025296176,0.002420999,0.000906818,0.00056319364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001153622,0.00019036264,0.0030704138,0.000338579,0.00006204702,0.0006005696,0.001004238,0.33886346,0.03683522,0.43269813,0.0067715584,0.17841181],"study_design_scores_gemma":[0.00015441526,0.00044131113,0.0008018859,0.000049288,0.000059275473,0.0003322997,0.0009743104,0.73369056,0.021211792,0.21818875,0.023999592,0.0000964968],"about_ca_topic_score_codex":0.0010153706,"about_ca_topic_score_gemma":0.0013092029,"teacher_disagreement_score":0.0018072132,"about_ca_system_score_codex":0.0006877961,"about_ca_system_score_gemma":0.0010593069,"threshold_uncertainty_score":0.0060457587},"labels":[],"label_agreement":null},{"id":"W1993964758","doi":"10.1142/s0219265906001739","title":"EXPLORING PLANAR GRAPHS USING UNORIENTED MAPS","year":2006,"lang":"en","type":"article","venue":"Journal of Interconnection Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; University of Ottawa","funders":"","keywords":"Computer science; Overhead (engineering); Embedding; Planar graph; Node (physics); Graph; Traverse; Algorithm; Planar; Terrain; Planar straight-line graph; Book embedding; Theoretical computer science; Artificial intelligence; Line graph; Pathwidth","score_opus":0.06915790782859202,"score_gpt":0.2541455881890506,"score_spread":0.18498768036045857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993964758","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23666552,0.0006284348,0.747477,0.0006592897,0.000036856138,0.00009970109,0.00033397798,0.0020002364,0.01209903],"genre_scores_gemma":[0.6809962,0.0010668705,0.31311855,0.00010224404,0.000026546213,0.00011279369,0.0007189607,0.00018221166,0.0036757537],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997117,0.000090756315,0.00001148564,0.00006278962,0.00007597539,0.00004732004],"domain_scores_gemma":[0.9989588,0.0007131855,0.000105721876,0.000121619574,0.000057865098,0.00004269477],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023913426,0.00061936595,0.0004158062,0.00056630623,0.000424325,0.00067489315,0.0007402308,0.00045753503,0.0022951716],"category_scores_gemma":[0.0020404155,0.0003187532,0.00048638313,0.0010474505,0.0004801482,0.0020894015,0.0013748863,0.0005413551,0.00035147395],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022983277,0.0000443779,0.0009843879,0.00020998222,0.000034723325,0.00026214356,0.00014925809,0.87717557,0.007639628,0.02398805,0.002134834,0.08714726],"study_design_scores_gemma":[0.000027944572,0.000054836306,0.0004256713,0.000016725166,0.000013870833,0.00011982355,0.000091265676,0.94480944,0.0035026341,0.04794841,0.002976722,0.000012528781],"about_ca_topic_score_codex":0.002362136,"about_ca_topic_score_gemma":0.0031633917,"teacher_disagreement_score":0.002362136,"about_ca_system_score_codex":0.0005461841,"about_ca_system_score_gemma":0.0006019825,"threshold_uncertainty_score":0.0076780915},"labels":[],"label_agreement":null},{"id":"W1995813020","doi":"10.1177/0278364913504011","title":"Persistent monitoring in discrete environments: Minimizing the maximum weighted latency between observations","year":2013,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":125,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Vertex (graph theory); Neighbourhood (mathematics); Feedback vertex set; Approximation algorithm; Vertex cover; Latency (audio); Patrolling; Combinatorics; Time complexity; Algorithm; Graph; Mathematics; Computer science","score_opus":0.14401273056313005,"score_gpt":0.3575397659671938,"score_spread":0.21352703540406373,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1995813020","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12420081,0.0004194791,0.8734817,0.0003839732,0.000030864754,0.00006843649,0.00013443039,0.0005038009,0.00077644654],"genre_scores_gemma":[0.8621982,0.00026140272,0.13575462,0.00006577999,0.000036581787,0.00013969267,0.00026305098,0.00012473116,0.0011560025],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989511,0.0002672294,0.000060652794,0.0003253765,0.00020563121,0.00018999071],"domain_scores_gemma":[0.99603784,0.0026080476,0.0006049354,0.00031251475,0.00018476603,0.00025189936],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013650742,0.0012373822,0.0013618376,0.00075550715,0.00065280346,0.0012279664,0.0022435233,0.0012591651,0.00100921],"category_scores_gemma":[0.006761078,0.00072831794,0.0004623611,0.0013487622,0.00096364,0.0031299146,0.0019236093,0.0010243206,0.00017343927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022195074,0.000071812356,0.0016023268,0.00009360989,0.000047182366,0.000094957984,0.00012424876,0.9607267,0.002848961,0.0048546675,0.00042799878,0.028885609],"study_design_scores_gemma":[0.000024721045,0.00007993434,0.00033037364,0.0000071391537,0.000013737464,0.000029998855,0.000050710263,0.9866246,0.0011356866,0.0114350505,0.00026065085,0.0000074466893],"about_ca_topic_score_codex":0.0045329113,"about_ca_topic_score_gemma":0.0038556785,"teacher_disagreement_score":0.0045329113,"about_ca_system_score_codex":0.0010074582,"about_ca_system_score_gemma":0.0013270059,"threshold_uncertainty_score":0.009013057},"labels":[],"label_agreement":null},{"id":"W1996317753","doi":"10.1007/s00224-005-1252-0","title":"Efficient Exploration of Faulty Trees","year":2006,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Overhead (engineering); Node (physics); Competitive analysis; Tree (set theory); Computation; Algorithm; Situated; Enhanced Data Rates for GSM Evolution; Fault tree analysis; Mathematics; Artificial intelligence; Combinatorics; Engineering; Upper and lower bounds","score_opus":0.028762374305972335,"score_gpt":0.2608479320143923,"score_spread":0.23208555770842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1996317753","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39095372,0.0012914744,0.59237885,0.0012933776,0.00013350937,0.000068042,0.0003526485,0.001807951,0.011720439],"genre_scores_gemma":[0.9078127,0.0001849895,0.08847482,0.000102004655,0.00002717815,0.000050836712,0.00028788217,0.00020715807,0.0028524662],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99934644,0.00021325018,0.000027597505,0.000076076874,0.00020683902,0.00012973043],"domain_scores_gemma":[0.99548954,0.002919775,0.00023716275,0.0008290133,0.00039709522,0.00012744409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007858359,0.0004044651,0.00097207236,0.00068943866,0.00068097573,0.00087184366,0.0012281535,0.001092551,0.0029444543],"category_scores_gemma":[0.0075077587,0.00041669863,0.000504074,0.00083799136,0.0010326555,0.0021239219,0.0021665744,0.0009726065,0.0003904581],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010316952,0.00010991579,0.0038222903,0.00031910554,0.0000796805,0.00053115597,0.00048759655,0.72790354,0.013694857,0.082182996,0.008569195,0.1612679],"study_design_scores_gemma":[0.00002221315,0.00003875106,0.0001657653,0.000011129068,0.000011425062,0.000076184406,0.000049419075,0.9331792,0.001860812,0.063516065,0.0010638554,0.0000052700207],"about_ca_topic_score_codex":0.0011850066,"about_ca_topic_score_gemma":0.0020571945,"teacher_disagreement_score":0.0029444543,"about_ca_system_score_codex":0.0005773335,"about_ca_system_score_gemma":0.0007583466,"threshold_uncertainty_score":0.009850144},"labels":[],"label_agreement":null},{"id":"W1998843748","doi":"10.1016/s0304-3975(98)00116-9","title":"Competitive analysis of randomized paging algorithms","year":2000,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":132,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Paging; Competitive analysis; Computer science; Online algorithm; Cache; Algorithm; Randomized algorithm; CPU cache; Demand paging; Page fault; Cache algorithms; Deterministic algorithm; Virtual memory; Memory management; Parallel computing; Upper and lower bounds; Mathematics; Operating system","score_opus":0.008541897466011434,"score_gpt":0.26329504070959364,"score_spread":0.2547531432435822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998843748","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2553874,0.007309391,0.61261785,0.00976996,0.0007297846,0.0008840784,0.0018252247,0.0022295956,0.10924674],"genre_scores_gemma":[0.9041083,0.0023802363,0.069457375,0.0011529538,0.0013179571,0.00071475666,0.0012982116,0.0008247545,0.018745486],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9885252,0.005698818,0.00032210557,0.000980611,0.0025096256,0.0019636569],"domain_scores_gemma":[0.9249324,0.06067259,0.0027469087,0.0052654385,0.0037085745,0.0026739691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008456368,0.0024069736,0.0047649904,0.003563574,0.0027339375,0.0074238456,0.009463843,0.0044947406,0.022261057],"category_scores_gemma":[0.066458076,0.0017081586,0.0020904327,0.0061168154,0.0041917195,0.010814791,0.0041071414,0.0051012025,0.0022776967],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024075462,0.0011231715,0.0022363777,0.0006929151,0.0001835694,0.00013595277,0.00035543257,0.3282477,0.0022181766,0.57334495,0.03212961,0.056924574],"study_design_scores_gemma":[0.00023101088,0.00018021195,0.00044807,0.000038162678,0.00006339152,0.00007469674,0.000070504204,0.81814414,0.00044762282,0.17795132,0.0023179373,0.000032826203],"about_ca_topic_score_codex":0.0067073,"about_ca_topic_score_gemma":0.004054929,"teacher_disagreement_score":0.022261057,"about_ca_system_score_codex":0.006764665,"about_ca_system_score_gemma":0.0062129637,"threshold_uncertainty_score":0.07447064},"labels":[],"label_agreement":null},{"id":"W1999004550","doi":"10.1016/j.disopt.2014.01.001","title":"The quadratic balanced optimization problem","year":2014,"lang":"en","type":"article","venue":"Discrete Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Mathematical optimization; Quadratically constrained quadratic program; Quadratic programming; Quadratic equation; Sequential quadratic programming; Geometry","score_opus":0.007785666697622099,"score_gpt":0.23544298419849105,"score_spread":0.22765731750086896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999004550","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011042398,0.0012741331,0.9476455,0.0013640504,0.00018154152,0.000051108662,0.00031251053,0.00009447991,0.038034365],"genre_scores_gemma":[0.56637853,0.0034354948,0.33811644,0.00096921343,0.0006282884,0.0005248565,0.0016167613,0.00055606867,0.08777437],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991315,0.00031164233,0.000028221839,0.00020102001,0.00023251711,0.00009516028],"domain_scores_gemma":[0.99909496,0.0005499792,0.00007816121,0.000062146115,0.00013305499,0.000081749924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015654356,0.00093850266,0.0011958936,0.0006308742,0.0004848147,0.0020783956,0.0009833425,0.0016288131,0.014235674],"category_scores_gemma":[0.006393753,0.00051396503,0.00041224007,0.00113584,0.0011094486,0.0024084614,0.0018479729,0.001604908,0.0016811129],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025064536,0.0001100938,0.0004769554,0.00037238427,0.000056709818,0.000077774814,0.000066791574,0.2383388,0.0030938413,0.61593056,0.01910693,0.12211851],"study_design_scores_gemma":[0.000069908856,0.00008140751,0.00032074994,0.000044827295,0.000018138486,0.00009955695,0.000038927174,0.6126769,0.0009814152,0.36934876,0.016302135,0.000017240025],"about_ca_topic_score_codex":0.0013195556,"about_ca_topic_score_gemma":0.0010251,"teacher_disagreement_score":0.014235674,"about_ca_system_score_codex":0.0009837816,"about_ca_system_score_gemma":0.0009773946,"threshold_uncertainty_score":0.047623098},"labels":[],"label_agreement":null},{"id":"W1999760725","doi":"10.1007/s00453-004-1121-2","title":"Approximating the Degree-Bounded Minimum Diameter Spanning Tree Problem","year":2004,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Minimum spanning tree; Combinatorics; Spanning tree; Mathematics; Degree (music); k-minimum spanning tree; Bounded function; Gomory–Hu tree; Theory of computation; Steiner tree problem; Approximation algorithm; Shortest-path tree; Discrete mathematics; Graph; Node (physics); Kruskal's algorithm; Undirected graph; Connected dominating set; Algorithm; K-ary tree; Tree structure; Binary tree","score_opus":0.04624586313923365,"score_gpt":0.256247606757736,"score_spread":0.21000174361850235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999760725","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18240565,0.0024550515,0.7973991,0.0027554547,0.0002330878,0.000089799185,0.00075014506,0.0005850928,0.013326764],"genre_scores_gemma":[0.7183557,0.0014309402,0.27287456,0.00028818086,0.00020519605,0.00013775988,0.001136156,0.0002756689,0.0052958825],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991314,0.00032826737,0.000032826036,0.00018348658,0.00020574739,0.00011833786],"domain_scores_gemma":[0.9959413,0.0029461,0.000274065,0.00031483435,0.00030991758,0.00021391398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013872234,0.0009217414,0.0014340312,0.00094920356,0.00064310216,0.0016052847,0.0020768563,0.0019889798,0.0033436536],"category_scores_gemma":[0.0128577305,0.0005401938,0.0006619586,0.0016648014,0.00081028073,0.003059224,0.0016793613,0.0014949818,0.0006331037],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005126552,0.00015472471,0.002078874,0.0003820682,0.000068166606,0.00011404529,0.000164951,0.83497983,0.0034575346,0.062970564,0.010603343,0.08451325],"study_design_scores_gemma":[0.00003637481,0.000034883036,0.00024169586,0.000017479093,0.00001760629,0.00005831223,0.000036437377,0.9512646,0.0005843345,0.04658049,0.0011235379,0.0000042685474],"about_ca_topic_score_codex":0.0022708576,"about_ca_topic_score_gemma":0.0032159172,"teacher_disagreement_score":0.0033436536,"about_ca_system_score_codex":0.0013025637,"about_ca_system_score_gemma":0.0009975362,"threshold_uncertainty_score":0.011185586},"labels":[],"label_agreement":null},{"id":"W1999969615","doi":"10.5555/1283383.1283410","title":"Improved bounds for the online steiner tree problem in graphs of bounded edge-asymmetry","year":2007,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Combinatorics; Competitive analysis; Steiner tree problem; Upper and lower bounds; Mathematics; Bounded function; Binary logarithm; Online algorithm; Log-log plot; Discrete mathematics; Asymmetry; Algorithm","score_opus":0.022410622383360786,"score_gpt":0.28838452357988265,"score_spread":0.26597390119652187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1999969615","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10928284,0.008721793,0.81306374,0.0052883956,0.0005313186,0.00032577408,0.0008431363,0.001753666,0.060189337],"genre_scores_gemma":[0.68529785,0.0060283286,0.29223305,0.001387808,0.0011724296,0.000612922,0.0013716455,0.0012483139,0.010647601],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9944161,0.001556581,0.00021305362,0.0007708009,0.0017949274,0.0012486178],"domain_scores_gemma":[0.97788805,0.01700995,0.001107387,0.0021383665,0.0011611327,0.0006951734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042233034,0.002465953,0.0021917734,0.0018478041,0.0019484125,0.004340455,0.005665622,0.0024513332,0.011562405],"category_scores_gemma":[0.02178982,0.00094159803,0.0020056074,0.002964892,0.002187731,0.011316613,0.0039104917,0.0048707165,0.002043352],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019111335,0.0006469682,0.0029052177,0.0010218727,0.00023498322,0.00038988274,0.00050001574,0.5126849,0.018635977,0.3257678,0.01707774,0.118223555],"study_design_scores_gemma":[0.00010958378,0.0001859518,0.0006134815,0.0000717798,0.0000912862,0.00025057653,0.00010960061,0.8605524,0.003937277,0.12630284,0.0077337036,0.000041494062],"about_ca_topic_score_codex":0.0041118367,"about_ca_topic_score_gemma":0.005151863,"teacher_disagreement_score":0.011562405,"about_ca_system_score_codex":0.0041169985,"about_ca_system_score_gemma":0.0029866262,"threshold_uncertainty_score":0.038680077},"labels":[],"label_agreement":null},{"id":"W2001755298","doi":"10.5555/1283383.1283408","title":"On the separation and equivalence of paging strategies","year":2007,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paging; Computer science; Partition (number theory); Equivalence (formal languages); Measure (data warehouse); Algorithm; Mathematics; Data mining; Computer network; Discrete mathematics","score_opus":0.031981909787465616,"score_gpt":0.32379853491843646,"score_spread":0.29181662513097084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2001755298","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17689282,0.00070353114,0.7894645,0.0011812217,0.000057903824,0.00023980929,0.00027198115,0.000742071,0.030446202],"genre_scores_gemma":[0.8800589,0.0005141294,0.11377723,0.000424879,0.00012501478,0.000295422,0.00035130026,0.0003527499,0.0041003865],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9883503,0.004369212,0.0010235531,0.0020107145,0.0024771867,0.0017690761],"domain_scores_gemma":[0.9508064,0.034428023,0.003639212,0.006975755,0.0024322479,0.0017184356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064632813,0.0010188159,0.0018205937,0.0016169323,0.0013102556,0.0051984666,0.0027576736,0.0022787482,0.0051915497],"category_scores_gemma":[0.05563993,0.0008254396,0.0012398799,0.0015454207,0.004529098,0.010103713,0.0049151983,0.0044267196,0.0010549658],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053882063,0.00033205815,0.002741984,0.00018919092,0.000048646296,0.00010833282,0.0010385128,0.053357817,0.003887979,0.84040135,0.0020725834,0.09528285],"study_design_scores_gemma":[0.00008764586,0.0004842619,0.0017561709,0.000075622636,0.000034489396,0.00029056933,0.00024240727,0.29734424,0.0034296324,0.69279134,0.0034105598,0.00005311885],"about_ca_topic_score_codex":0.0012874888,"about_ca_topic_score_gemma":0.0004958161,"teacher_disagreement_score":0.0064632813,"about_ca_system_score_codex":0.0022755435,"about_ca_system_score_gemma":0.0019619379,"threshold_uncertainty_score":0.034181476},"labels":[],"label_agreement":null},{"id":"W2002043779","doi":"10.1007/s446-002-8031-5","title":"The optimal location of replicas in a network using a READ-ONE-WRITE-ALL policy","year":2002,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Fields Institute for Research in Mathematical Sciences; Carleton University; University of Toronto","funders":"","keywords":"Computer science; Consistency (knowledge bases); Mathematical optimization; Dynamic programming; Function (biology); Path (computing); Linear programming; Zero (linguistics); Optimization problem; Algorithm; Mathematics; Computer network","score_opus":0.059305550587239415,"score_gpt":0.3061084122070256,"score_spread":0.2468028616197862,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002043779","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31515604,0.0018999486,0.66949797,0.0035842578,0.00029262633,0.00041381925,0.00051597535,0.0011276588,0.0075116903],"genre_scores_gemma":[0.86840516,0.0004542724,0.12680474,0.00015566281,0.00009730137,0.00015002573,0.00014857118,0.00015311404,0.003631143],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982547,0.0008120571,0.0001264027,0.0003308504,0.00019490447,0.0002811074],"domain_scores_gemma":[0.9907444,0.006297998,0.00074947265,0.00091821706,0.00071308005,0.00057675765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00355649,0.0011686094,0.0029651583,0.0012251723,0.0015056016,0.0026009814,0.0026075668,0.0032055688,0.0037112033],"category_scores_gemma":[0.017164582,0.0011900477,0.0006323179,0.001815147,0.0019604296,0.005682991,0.0018398198,0.001119719,0.00067795435],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001953335,0.000234244,0.0017232787,0.00036872562,0.00009132398,0.00019968614,0.00024278671,0.90551805,0.006151845,0.028969286,0.004886084,0.049661286],"study_design_scores_gemma":[0.0001549518,0.00010554537,0.00023615117,0.000015949578,0.00003778905,0.00005622921,0.00014619339,0.9763001,0.0023004464,0.020230345,0.0003957146,0.000020564723],"about_ca_topic_score_codex":0.0033554125,"about_ca_topic_score_gemma":0.004644971,"teacher_disagreement_score":0.0037112033,"about_ca_system_score_codex":0.0018568629,"about_ca_system_score_gemma":0.0027221774,"threshold_uncertainty_score":0.018808722},"labels":[],"label_agreement":null},{"id":"W2002942860","doi":"10.5555/545381.545459","title":"Tree exploration with little memory","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; Carleton University","funders":"","keywords":"Node (physics); Binary logarithm; Degree (music); Bounded function; Tree (set theory); Computer science; Task (project management); Upper and lower bounds; Time complexity; Combinatorics; Mathematics; Discrete mathematics; Algorithm; Theoretical computer science","score_opus":0.050559385432962685,"score_gpt":0.226879259790743,"score_spread":0.17631987435778032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002942860","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13131969,0.001534878,0.84396017,0.0009373775,0.00007491003,0.000097235774,0.00036279185,0.0049073095,0.016805612],"genre_scores_gemma":[0.6101838,0.0007075136,0.37581745,0.00031928316,0.000042515374,0.00031135677,0.00071448367,0.00038670786,0.011516998],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996859,0.00006544842,0.0000237738,0.00007958196,0.000055611283,0.00008977059],"domain_scores_gemma":[0.99894184,0.0005337318,0.000090821195,0.0002791879,0.00007993378,0.000074468466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030205684,0.0005610649,0.0008695224,0.00043598286,0.00070572627,0.000956534,0.0013845697,0.000931151,0.0070565417],"category_scores_gemma":[0.0021917182,0.0003694473,0.0005551208,0.000714401,0.0007148192,0.0030543169,0.0021827132,0.0007716914,0.0016417314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002825014,0.00021378724,0.0023306466,0.0009176132,0.00012583878,0.0006083329,0.000850187,0.35925636,0.060016993,0.09096088,0.020314435,0.46157995],"study_design_scores_gemma":[0.00020495709,0.0003089213,0.0005691635,0.0000693024,0.000060213613,0.00034356635,0.00014929356,0.8336221,0.017860223,0.13484325,0.011925703,0.00004341224],"about_ca_topic_score_codex":0.0011718922,"about_ca_topic_score_gemma":0.00193799,"teacher_disagreement_score":0.0070565417,"about_ca_system_score_codex":0.00043883323,"about_ca_system_score_gemma":0.0006698163,"threshold_uncertainty_score":0.02360648},"labels":[],"label_agreement":null},{"id":"W2004438803","doi":"10.1093/comjnl/bxl067","title":"A Novel Framework for Self-Organizing Lists in Environments with Locality of Reference: Lists-on-Lists","year":2006,"lang":"en","type":"article","venue":"The Computer Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Locality; Computer science; Library science; World Wide Web; Information retrieval; Linguistics","score_opus":0.026993477283438618,"score_gpt":0.26322578882454256,"score_spread":0.23623231154110394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004438803","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010976206,0.00047464212,0.9859358,0.00035523958,0.000052571344,0.00007208548,0.000069339396,0.00034933424,0.0017148408],"genre_scores_gemma":[0.37290832,0.0009922893,0.61649185,0.00038341153,0.00029839508,0.0005247346,0.0003806272,0.0002655533,0.00775479],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985122,0.00052174286,0.000079705096,0.00033858937,0.00033920654,0.0002084506],"domain_scores_gemma":[0.9959055,0.00213205,0.0005589376,0.0006160699,0.00048168367,0.00030570236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017242949,0.0007572987,0.0012624634,0.0014360449,0.0015751873,0.0029719044,0.0042926203,0.0025787852,0.0042362334],"category_scores_gemma":[0.0070317173,0.0007629734,0.0011944734,0.0017204186,0.0024181125,0.0055724136,0.0031501795,0.0019027357,0.0009521935],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001175571,0.00012219086,0.0012537079,0.00025148253,0.00005896728,0.00019328359,0.00040623316,0.7031073,0.003975146,0.23474409,0.0028413625,0.052928653],"study_design_scores_gemma":[0.000018399936,0.00008838189,0.00013439907,0.000018852275,0.000015796917,0.00007559696,0.000070271984,0.901274,0.0010220194,0.09309327,0.004163233,0.00002571932],"about_ca_topic_score_codex":0.003742694,"about_ca_topic_score_gemma":0.0036006833,"teacher_disagreement_score":0.0042926203,"about_ca_system_score_codex":0.0019806072,"about_ca_system_score_gemma":0.0016109837,"threshold_uncertainty_score":0.014370322},"labels":[],"label_agreement":null},{"id":"W2006093991","doi":"10.5555/982792.982915","title":"A maiden analysis of Longest Wait First","year":2004,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Multicast; Computer science; Scheduling (production processes); Competitive analysis; Computer network; Mathematical optimization; Mathematics","score_opus":0.013779340519190672,"score_gpt":0.25979166195592013,"score_spread":0.24601232143672946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2006093991","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03588038,0.0062423204,0.882159,0.004838656,0.00045317694,0.00015746304,0.00045667286,0.0010405644,0.06877173],"genre_scores_gemma":[0.7036538,0.007639189,0.21462488,0.003232166,0.0020803227,0.00088239805,0.00086694985,0.0017928398,0.06522737],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978702,0.00050316623,0.000070759575,0.00033776797,0.00066163205,0.0005564552],"domain_scores_gemma":[0.98806226,0.008476972,0.00088824384,0.0007422068,0.0011436035,0.0006867218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004620641,0.0022279348,0.0018936141,0.0028937059,0.0021653776,0.0032948942,0.0042386297,0.0020373603,0.023468345],"category_scores_gemma":[0.02385545,0.0010676123,0.0016543501,0.0024344178,0.002364498,0.007910718,0.0022446455,0.004856122,0.0033043644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041853153,0.00014310918,0.0009004573,0.00041649188,0.00011449083,0.00012794917,0.00028521073,0.16820648,0.0038690385,0.76813495,0.01595339,0.041429963],"study_design_scores_gemma":[0.000052710482,0.00010745157,0.00024030065,0.00007519995,0.0000679511,0.00007760251,0.000038914637,0.6661388,0.0018643906,0.32178667,0.009516742,0.000033168144],"about_ca_topic_score_codex":0.004024385,"about_ca_topic_score_gemma":0.0024679888,"teacher_disagreement_score":0.023468345,"about_ca_system_score_codex":0.0048542353,"about_ca_system_score_gemma":0.002564531,"threshold_uncertainty_score":0.07850945},"labels":[],"label_agreement":null},{"id":"W2007652042","doi":"10.1109/crv.2014.31","title":"Asymmetric Rendezvous Search at Sea","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Drifter; Rendezvous; Position (finance); Marine engineering; Trajectory; Spiral (railway); Computer science; Underwater; Geodesy; Geology; Simulation; Aerospace engineering; Lagrangian; Engineering; Oceanography; Physics","score_opus":0.023458078164191876,"score_gpt":0.2612381506962305,"score_spread":0.23778007253203864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2007652042","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6521107,0.0008069615,0.3280748,0.00038653077,0.000039323153,0.000045048375,0.00012090446,0.0002937999,0.01812186],"genre_scores_gemma":[0.98653215,0.0000923206,0.011378219,0.000028242923,0.0000052399787,0.00002535828,0.000051332627,0.000024890775,0.0018622802],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996793,0.00007602649,0.000014789714,0.0000713062,0.00008275878,0.00007591389],"domain_scores_gemma":[0.9986344,0.00083403685,0.00019025391,0.0001305347,0.00011744656,0.000093233175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047198217,0.000497565,0.00083553564,0.00049744983,0.0006403188,0.0006071106,0.0008215072,0.00081768964,0.00213073],"category_scores_gemma":[0.003764221,0.00026790932,0.00035821783,0.00038337108,0.0010197175,0.0013834606,0.0011835272,0.00058418757,0.0003725704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003047553,0.00003132615,0.0015849319,0.00006896563,0.0000387529,0.00025586822,0.00016334245,0.94796664,0.0053586983,0.024094857,0.00066275167,0.019469202],"study_design_scores_gemma":[0.000044556407,0.000088114066,0.0005004113,0.000011200298,0.000009755947,0.00013694452,0.00009399456,0.97434014,0.0021197107,0.02182688,0.00081507425,0.000013164745],"about_ca_topic_score_codex":0.0031665224,"about_ca_topic_score_gemma":0.001954287,"teacher_disagreement_score":0.0031665224,"about_ca_system_score_codex":0.00053355703,"about_ca_system_score_gemma":0.0004932083,"threshold_uncertainty_score":0.0071279407},"labels":[],"label_agreement":null},{"id":"W2008126942","doi":"10.1007/s00453-001-0039-1","title":"On-Line Competitive Algorithms for Call Admission in Optical Networks","year":2001,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Theory of computation; Computer science; Logarithm; Network topology; Competitive analysis; Telecommunications network; Line (geometry); Algorithm; Computer network; Mathematics; Upper and lower bounds","score_opus":0.03568695878688269,"score_gpt":0.311284834257148,"score_spread":0.27559787547026526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008126942","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05593266,0.0014052982,0.9168251,0.002393844,0.00039430702,0.00038053197,0.00024198006,0.0008405756,0.021585755],"genre_scores_gemma":[0.7629399,0.0011539492,0.21418956,0.000855012,0.0008819048,0.000639444,0.00045181715,0.00046264328,0.018425751],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99517727,0.0024461297,0.00012188606,0.00034126267,0.0010012224,0.00091217045],"domain_scores_gemma":[0.978152,0.017710065,0.0008738824,0.0009167918,0.0012838123,0.0010634788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006013452,0.0020061114,0.003477254,0.0018332467,0.0023693058,0.005152312,0.0062734177,0.0047633443,0.0135598015],"category_scores_gemma":[0.031224532,0.001192543,0.0010929883,0.0033414965,0.0031243495,0.005968346,0.0036890882,0.004492057,0.0014238248],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008608418,0.00064579793,0.00065405696,0.00022010172,0.00007713847,0.00006165066,0.00023526141,0.79994684,0.0007547184,0.09200454,0.01502264,0.08951648],"study_design_scores_gemma":[0.00008281872,0.000054391126,0.000062763116,0.00000847698,0.000010679272,0.000012401164,0.000027226975,0.9600446,0.00016146371,0.038900573,0.00062615896,0.0000084653075],"about_ca_topic_score_codex":0.0075132293,"about_ca_topic_score_gemma":0.006214103,"teacher_disagreement_score":0.0135598015,"about_ca_system_score_codex":0.003949205,"about_ca_system_score_gemma":0.0038277458,"threshold_uncertainty_score":0.045361996},"labels":[],"label_agreement":null},{"id":"W2008228566","doi":"10.1016/j.ins.2013.01.017","title":"Using Voronoi diagrams to solve a hybrid facility location problem with attentive facilities","year":2013,"lang":"en","type":"article","venue":"Information Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Voronoi diagram; Computer science; Set (abstract data type); Mathematical optimization; Facility location problem; Function (biology); Space (punctuation); Class (philosophy); Mathematics; Artificial intelligence","score_opus":0.04730909891146549,"score_gpt":0.2722949613739627,"score_spread":0.22498586246249722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008228566","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031332746,0.00020468958,0.9657426,0.00010685594,0.000041661344,0.00006710748,0.000047682133,0.00010165904,0.0023550675],"genre_scores_gemma":[0.4956119,0.00019520994,0.5002289,0.000071060036,0.00004789938,0.00023494325,0.00012255671,0.00006827791,0.0034192242],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992987,0.00030456122,0.000026563604,0.00010379531,0.0001553111,0.00011103121],"domain_scores_gemma":[0.99718827,0.0022688655,0.00014115572,0.00009160028,0.00018841514,0.000121732584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013078345,0.0009895576,0.0015711586,0.0013322243,0.00075423456,0.0015699151,0.0022604181,0.0021635413,0.0026932328],"category_scores_gemma":[0.005824983,0.0011381063,0.0012190847,0.0015161047,0.0009408641,0.0019261295,0.0021152424,0.0012007939,0.00027250202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009085392,0.00005390355,0.0002663849,0.0000730598,0.000036223795,0.000061621045,0.000040850162,0.9702354,0.00066500163,0.01576383,0.0004460848,0.0122667765],"study_design_scores_gemma":[0.000024448043,0.00002554231,0.000032339965,0.0000047460594,0.0000089209125,0.000013619122,0.0000132954665,0.9932528,0.00019497675,0.0061490634,0.00027462767,0.0000056997756],"about_ca_topic_score_codex":0.009010954,"about_ca_topic_score_gemma":0.008283474,"teacher_disagreement_score":0.009010954,"about_ca_system_score_codex":0.0010905878,"about_ca_system_score_gemma":0.00145982,"threshold_uncertainty_score":0.017916977},"labels":[],"label_agreement":null},{"id":"W2008628501","doi":"10.1109/acc.2013.6579839","title":"Distributed dominating sets on grids","year":2013,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Dominating set; Bounded function; Grid; Distributed algorithm; Computer science; Mathematics; Set (abstract data type); Combinatorics; Discrete mathematics; Distributed computing; Graph","score_opus":0.016087884653133336,"score_gpt":0.2553096493095414,"score_spread":0.2392217646564081,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008628501","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008343426,0.00073336484,0.9839602,0.00033549574,0.00017915304,0.00016324071,0.00009583867,0.00041514894,0.0057742335],"genre_scores_gemma":[0.32412034,0.0013653153,0.66352373,0.0003492373,0.00018427715,0.0005246174,0.0004898805,0.00016760727,0.009275006],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980703,0.0007606488,0.00012191662,0.00033488218,0.00054673536,0.00016557558],"domain_scores_gemma":[0.99823254,0.0008804948,0.00010159539,0.00035812976,0.00029272324,0.0001344913],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001497508,0.0008414204,0.0014418152,0.0007125479,0.0011597465,0.0015082879,0.0019692406,0.0007710162,0.0021207228],"category_scores_gemma":[0.003922518,0.00047190321,0.00076300395,0.0013081988,0.0008679628,0.0018601808,0.0023019724,0.001094508,0.0007481442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021992617,0.00008749802,0.00054267136,0.0003497128,0.000096771706,0.0001809933,0.0002807407,0.6099523,0.005377647,0.20703939,0.011201218,0.16467115],"study_design_scores_gemma":[0.000099997524,0.00012432176,0.00015998406,0.00003888028,0.000027361692,0.00013599286,0.00009785376,0.8228916,0.0035981175,0.13995008,0.032850303,0.00002552595],"about_ca_topic_score_codex":0.0015156008,"about_ca_topic_score_gemma":0.001734595,"teacher_disagreement_score":0.0021207228,"about_ca_system_score_codex":0.0012287181,"about_ca_system_score_gemma":0.0011895462,"threshold_uncertainty_score":0.008915007},"labels":[],"label_agreement":null},{"id":"W2008689719","doi":"10.1145/2612669.2612686","title":"On the online fault-tolerant server consolidation problem","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Server; Computer science; Competitive analysis; Round-robin DNS; Cloud computing; Load balancing (electrical power); Upper and lower bounds; Distributed computing; Online algorithm; Heuristics; Fault tolerance; Consolidation (business); Computer network; Algorithm; Operating system; The Internet; Mathematics","score_opus":0.02469024284429975,"score_gpt":0.2587300152619463,"score_spread":0.23403977241764654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2008689719","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10935929,0.0015425544,0.86655205,0.002194083,0.00015799914,0.00037825326,0.00033200815,0.000544573,0.01893915],"genre_scores_gemma":[0.73553073,0.001336847,0.2512337,0.000768407,0.00028078345,0.00045258043,0.0006217091,0.0002715792,0.009503643],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99808514,0.0007181793,0.00006999552,0.00031068627,0.0003282159,0.00048779842],"domain_scores_gemma":[0.99465996,0.0040202937,0.00035389242,0.00026306455,0.00033891897,0.00036385603],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019645856,0.001531033,0.0019805462,0.000801995,0.0012187933,0.0021531119,0.0023727166,0.002334453,0.0065355827],"category_scores_gemma":[0.0071351505,0.0004420381,0.00077580306,0.0019709724,0.0014311294,0.0037599907,0.0014225872,0.0018298458,0.0008705594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006935506,0.00060553796,0.0013037372,0.00038769716,0.000093727336,0.00026975086,0.00019568036,0.7715186,0.0028573247,0.1195048,0.009756554,0.09281308],"study_design_scores_gemma":[0.000084167514,0.00015769088,0.0003036784,0.000024341523,0.000025072615,0.00017631965,0.000101736005,0.9432665,0.0011906022,0.052032463,0.0026206828,0.000016691547],"about_ca_topic_score_codex":0.004784904,"about_ca_topic_score_gemma":0.0033317984,"teacher_disagreement_score":0.0065355827,"about_ca_system_score_codex":0.002074779,"about_ca_system_score_gemma":0.002090375,"threshold_uncertainty_score":0.021863699},"labels":[],"label_agreement":null},{"id":"W2009831508","doi":"10.1016/j.tcs.2013.03.016","title":"Complexity of Canadian traveler problem variants","year":2013,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Israel Science Foundation","keywords":"PSPACE; Combinatorics; Mathematics; Time complexity; Disjoint sets; Vertex (graph theory); Graph; Discrete mathematics; Path (computing); Travelling salesman problem; Computational complexity theory; Computer science; Algorithm","score_opus":0.03185590816938742,"score_gpt":0.24652722804301677,"score_spread":0.21467131987362936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009831508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6163009,0.0029390613,0.12968165,0.007598728,0.0005001548,0.000523728,0.006892658,0.0005964079,0.23496674],"genre_scores_gemma":[0.90822977,0.0010989526,0.040836092,0.00044163706,0.00020427431,0.00023186106,0.0050344416,0.00036540514,0.04355757],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971156,0.000695882,0.00010209706,0.00046401826,0.0008312533,0.0007911394],"domain_scores_gemma":[0.99384034,0.0039781877,0.00029597414,0.0005446208,0.0007497568,0.0005911927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018934484,0.0012188625,0.0017529908,0.0019847467,0.0030146497,0.0063514975,0.003783354,0.0025664372,0.02134353],"category_scores_gemma":[0.014645684,0.00070195226,0.001748315,0.003647964,0.0024647554,0.0048752166,0.0021436643,0.003797532,0.00091784063],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009026198,0.00033238542,0.0030909025,0.00026300168,0.00010146419,0.00024101067,0.00054113095,0.20986886,0.00082553824,0.6964036,0.047480255,0.03994911],"study_design_scores_gemma":[0.000249317,0.00009039744,0.0022370766,0.00006650974,0.00009410503,0.00022694403,0.000623275,0.45906088,0.00068609376,0.5190466,0.01753201,0.00008675705],"about_ca_topic_score_codex":0.2072077,"about_ca_topic_score_gemma":0.19406295,"teacher_disagreement_score":0.2072077,"about_ca_system_score_codex":0.012238029,"about_ca_system_score_gemma":0.010143134,"threshold_uncertainty_score":0.41200322},"labels":[],"label_agreement":null},{"id":"W2009988763","doi":"10.1109/comsnets.2013.6465538","title":"Multi-queued network processors for packets with heterogeneous processing requirements","year":2013,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Network packet; Queueing theory; Scheduling (production processes); Network processor; Distributed computing; Queue; Packet processing; Throughput; Priority queue; Computer network; Packet switching; Mathematical optimization","score_opus":0.045761079527912855,"score_gpt":0.28999556623787315,"score_spread":0.24423448670996029,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2009988763","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16303338,0.0010362124,0.82962614,0.0007450026,0.000104964296,0.00013820396,0.00006065634,0.00034240304,0.0049130376],"genre_scores_gemma":[0.85543346,0.00039948564,0.14141382,0.0001323908,0.00005295523,0.00009837398,0.000040075574,0.00003262085,0.00239685],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954116,0.00017463553,0.000019004376,0.00008272526,0.00009841205,0.000084109764],"domain_scores_gemma":[0.9991912,0.00042487614,0.00011425374,0.00010270307,0.00011241547,0.00005457302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010798553,0.00057495246,0.0004768794,0.00030122054,0.0007062652,0.0010100448,0.0017812091,0.0006967185,0.0018946426],"category_scores_gemma":[0.0020239209,0.00025032373,0.00027201453,0.00050634093,0.00053335924,0.001516062,0.0007345977,0.0008928482,0.00021902316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022755945,0.00012950932,0.0008349714,0.00015306276,0.000028198698,0.00021000698,0.00006886274,0.9254839,0.012898277,0.027929977,0.0012702444,0.03076551],"study_design_scores_gemma":[0.000017784163,0.0000620749,0.00010179937,0.0000054513625,0.000009807214,0.000025226349,0.000012377279,0.99295276,0.0017253744,0.0041880724,0.00089543307,0.000003831787],"about_ca_topic_score_codex":0.0019671333,"about_ca_topic_score_gemma":0.0038237441,"teacher_disagreement_score":0.0019671333,"about_ca_system_score_codex":0.001415719,"about_ca_system_score_gemma":0.0011196779,"threshold_uncertainty_score":0.010271788},"labels":[],"label_agreement":null},{"id":"W2010017329","doi":"10.1016/j.tcs.2005.01.001","title":"Gathering of asynchronous robots with limited visibility","year":2005,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":396,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Visibility; Asynchronous communication; Robot; Computer science; Orientation (vector space); Mobile robot; Convergence (economics); Computation; Protocol (science); Point (geometry); Artificial intelligence; Distributed computing; Computer vision; Theoretical computer science; Algorithm; Mathematics; Telecommunications; Geography; Geometry","score_opus":0.01010129519343213,"score_gpt":0.24813068238141042,"score_spread":0.23802938718797828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010017329","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41336673,0.00038825773,0.5761545,0.00044563046,0.000093911345,0.00009278255,0.00012524684,0.00027519415,0.009057682],"genre_scores_gemma":[0.9575259,0.00023103664,0.03553186,0.000046470403,0.00007049714,0.00009972924,0.00012190866,0.00006429185,0.0063083195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994592,0.00014293616,0.000028873854,0.00013220971,0.00011641868,0.00012045916],"domain_scores_gemma":[0.99365956,0.003969991,0.0008669955,0.00043220652,0.00039695916,0.0006743584],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010417352,0.00094783574,0.0014558004,0.0013336565,0.0015240757,0.0016067482,0.0019993105,0.0015280626,0.0033241825],"category_scores_gemma":[0.008131398,0.0009887179,0.00087479356,0.0010193528,0.001377421,0.0027491644,0.003015001,0.0010430317,0.00041623233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014088457,0.00021194556,0.0024074102,0.000364104,0.0001172489,0.00071841985,0.0005417521,0.83880055,0.012477862,0.110369325,0.0019883045,0.030594153],"study_design_scores_gemma":[0.0000849385,0.00012727562,0.0003204925,0.000010715969,0.000024694078,0.00005283003,0.000072068775,0.95481735,0.00097413134,0.042982668,0.00051862525,0.000014170518],"about_ca_topic_score_codex":0.0018704319,"about_ca_topic_score_gemma":0.0017057193,"teacher_disagreement_score":0.0033241825,"about_ca_system_score_codex":0.0007348095,"about_ca_system_score_gemma":0.00067228585,"threshold_uncertainty_score":0.011120498},"labels":[],"label_agreement":null},{"id":"W2015639925","doi":"10.5555/1283383.1283392","title":"Improved bounds for the symmetric rendezvous value on the line","year":2007,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Rendezvous; Conjecture; Mathematics; Semidefinite programming; Value (mathematics); Markov decision process; Line (geometry); Mathematical optimization; Quadratic equation; Markov chain; Applied mathematics; Combinatorics; Markov process; Discrete mathematics; Physics; Statistics; Geometry","score_opus":0.023880501906073954,"score_gpt":0.2873125432453776,"score_spread":0.26343204133930365,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015639925","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18289144,0.0029113118,0.76258236,0.001735202,0.00018683345,0.00018659094,0.0005336397,0.0008906664,0.04808197],"genre_scores_gemma":[0.88290447,0.0010796051,0.109363236,0.00032527954,0.0001396428,0.00021705724,0.0004967197,0.0003983216,0.005075601],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9955004,0.0013995265,0.00013810348,0.00084849313,0.0010283764,0.0010850815],"domain_scores_gemma":[0.96867174,0.022854066,0.0020380663,0.0024982917,0.002740191,0.0011977232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005171525,0.0016611101,0.0020663983,0.0024438668,0.0016036937,0.0034075803,0.0037629977,0.0018734712,0.011500232],"category_scores_gemma":[0.030782748,0.00065320544,0.0014614015,0.0019221215,0.003957401,0.007083123,0.0038328953,0.0044306153,0.0016288846],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012690787,0.00025118413,0.0029184006,0.00045719693,0.00014989145,0.00024082672,0.0004583569,0.5189872,0.014947541,0.4059801,0.006263506,0.048076708],"study_design_scores_gemma":[0.000053902233,0.00016359313,0.00050125347,0.00008974102,0.000033873057,0.0001069049,0.00020961787,0.8050183,0.007188387,0.1844786,0.0020942085,0.00006155358],"about_ca_topic_score_codex":0.0022410706,"about_ca_topic_score_gemma":0.002144959,"teacher_disagreement_score":0.011500232,"about_ca_system_score_codex":0.0032507123,"about_ca_system_score_gemma":0.0018161356,"threshold_uncertainty_score":0.038472116},"labels":[],"label_agreement":null},{"id":"W2017441966","doi":"10.1007/s00453-014-9884-6","title":"A Comparison of Performance Measures for Online Algorithms","year":2014,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of California, Irvine; University of Waterloo; Danmarks Frie Forskningsfond; National Science Foundation","keywords":"Bijection; Competitive analysis; Context (archaeology); Computer science; Theory of computation; Algorithm; Adaptability; Order (exchange); Greedy algorithm; Simple (philosophy); Online algorithm; Mathematics; Combinatorics; Upper and lower bounds","score_opus":0.05276604616838215,"score_gpt":0.3370390444198044,"score_spread":0.28427299825142227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017441966","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28842,0.044165738,0.6191957,0.0030117168,0.0019145972,0.0006253207,0.0029955653,0.005602303,0.034069087],"genre_scores_gemma":[0.80909985,0.004603745,0.17734447,0.0002749267,0.0007231954,0.0004424987,0.0031273444,0.001009448,0.003374453],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9727066,0.012854495,0.0017873559,0.002409409,0.008682529,0.0015596391],"domain_scores_gemma":[0.79779804,0.16020952,0.006853814,0.018511795,0.0139546385,0.00267211],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.023244468,0.002070673,0.0030488523,0.0072355443,0.0011104415,0.005037354,0.0029366687,0.00356266,0.004360444],"category_scores_gemma":[0.11271043,0.0004899026,0.001478221,0.007209655,0.0017959757,0.007677331,0.0027095259,0.002238344,0.0011106965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0062045036,0.0016589551,0.013976306,0.0022146818,0.0008881051,0.00009277003,0.00036389023,0.2765093,0.0044157975,0.08647524,0.021258406,0.5859421],"study_design_scores_gemma":[0.00045575792,0.004415944,0.014689194,0.0004374538,0.00047981663,0.00052878377,0.00049508305,0.8859353,0.010536443,0.07223571,0.009599834,0.00019074122],"about_ca_topic_score_codex":0.0017220279,"about_ca_topic_score_gemma":0.001197157,"teacher_disagreement_score":0.023244468,"about_ca_system_score_codex":0.0038039158,"about_ca_system_score_gemma":0.0025632884,"threshold_uncertainty_score":0.12292999},"labels":[],"label_agreement":null},{"id":"W2018043895","doi":"10.5555/2133036.2133045","title":"Online scalable scheduling for the lk-norms of flow time without conservation of work","year":2011,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Scalability; Scheduling (production processes); Cloud computing; Competitive analysis; Distributed computing; Flow shop scheduling; Job shop scheduling; Parallel computing; Mathematical optimization; Computer network; Mathematics; Upper and lower bounds; Operating system","score_opus":0.034947947273841026,"score_gpt":0.26552950854941215,"score_spread":0.2305815612755711,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018043895","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047571998,0.00055383326,0.9407053,0.00087353383,0.00011521825,0.00023639493,0.0002967574,0.0011515295,0.008495455],"genre_scores_gemma":[0.5349597,0.00048386847,0.4555273,0.0003904913,0.00031090045,0.00065539934,0.0006044948,0.0007301226,0.0063377586],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9973309,0.00071791786,0.00012060546,0.0005661499,0.00072772696,0.0005368036],"domain_scores_gemma":[0.98829997,0.007438705,0.0011694536,0.0013259104,0.0010051546,0.0007608398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00358156,0.0016812434,0.0020356742,0.0009036186,0.0010753385,0.0027482037,0.0036438429,0.00152704,0.0043291254],"category_scores_gemma":[0.016774822,0.00066512264,0.00094282796,0.0016903437,0.0016965849,0.0054081515,0.002403859,0.0027464684,0.0009447379],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010171079,0.00037630624,0.0010883394,0.0005414791,0.00008299662,0.0001666554,0.00037226971,0.6952349,0.010208682,0.19368896,0.010841425,0.0863809],"study_design_scores_gemma":[0.000046511068,0.00006184822,0.00010373763,0.000010796768,0.0000065157406,0.000032472344,0.000020461248,0.9513484,0.0010790488,0.046426363,0.0008522132,0.000011496804],"about_ca_topic_score_codex":0.0030270133,"about_ca_topic_score_gemma":0.0032318425,"teacher_disagreement_score":0.0043291254,"about_ca_system_score_codex":0.0038137801,"about_ca_system_score_gemma":0.0038149413,"threshold_uncertainty_score":0.02767098},"labels":[],"label_agreement":null},{"id":"W2019146736","doi":"10.2139/ssrn.1001726","title":"General Theory of Cost Minimization Strategies of Continuous Audit of Databases","year":2007,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Audit; Minification; Computer science; Independence (probability theory); Process (computing); Database; General theory; Domain (mathematical analysis); Work (physics); Accounting; Algorithm; Data mining; Mathematics; Mathematical economics; Economics; Engineering","score_opus":0.018495714936868,"score_gpt":0.2813549039057231,"score_spread":0.2628591889688551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019146736","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024407484,0.0022919306,0.9475157,0.002102869,0.00011405808,0.00016944532,0.0003572096,0.00017717882,0.022864083],"genre_scores_gemma":[0.7667634,0.0056822062,0.19586019,0.0006357815,0.00048790502,0.0006065394,0.0004999297,0.00021491366,0.02924917],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967691,0.0015129026,0.00018939069,0.0003985882,0.0007031797,0.00042684327],"domain_scores_gemma":[0.98934376,0.008087261,0.0006176744,0.00075566897,0.00086850807,0.0003272139],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047690645,0.0016793604,0.0024741339,0.0019190247,0.0008406959,0.005865358,0.0038056113,0.0031456726,0.008947819],"category_scores_gemma":[0.023515867,0.0012907,0.0015765866,0.003784039,0.0023596347,0.0064951763,0.0021484147,0.0029594924,0.00074461097],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006133492,0.000048702525,0.000301038,0.00022133796,0.00005768618,0.00006770762,0.00012233065,0.13039474,0.0005480315,0.8428633,0.0031114893,0.02220222],"study_design_scores_gemma":[0.00002908211,0.000038783935,0.00021213804,0.000060209728,0.00003517728,0.00006903632,0.00005498421,0.38645908,0.00029126063,0.6106769,0.0020512084,0.000022220504],"about_ca_topic_score_codex":0.0035915081,"about_ca_topic_score_gemma":0.002048661,"teacher_disagreement_score":0.008947819,"about_ca_system_score_codex":0.004495178,"about_ca_system_score_gemma":0.003254882,"threshold_uncertainty_score":0.032614946},"labels":[],"label_agreement":null},{"id":"W2019783787","doi":"10.1016/s0167-8191(03)00022-x","title":"The maximum flow problem: a real-time approach","year":2003,"lang":"en","type":"article","venue":"Parallel Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Flow (mathematics); Computer science; Mechanics; Physics","score_opus":0.019048448547801702,"score_gpt":0.24641333936502036,"score_spread":0.22736489081721867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2019783787","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023098185,0.0008359822,0.9917856,0.00057727017,0.00016028012,0.000044366046,0.000053963387,0.0001916161,0.004041168],"genre_scores_gemma":[0.17729072,0.0024147457,0.8082588,0.00025466806,0.0008759289,0.0002948091,0.00022353095,0.00048309864,0.009903747],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845755,0.0006465754,0.00005510525,0.00029862634,0.0003952231,0.000146935],"domain_scores_gemma":[0.99680614,0.0023739627,0.00022856165,0.00018056693,0.00027978088,0.00013106455],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035254816,0.0021789873,0.0021900816,0.0015119778,0.0008750883,0.0033849236,0.004040203,0.0028697485,0.0085184965],"category_scores_gemma":[0.009711384,0.001196929,0.0012798157,0.0022416764,0.0019682634,0.0060015074,0.0016947291,0.0036024477,0.00095251016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002570028,0.0001328595,0.0002444786,0.00051769055,0.00007459326,0.00014182448,0.00012399632,0.6497263,0.0015126646,0.2302904,0.009206596,0.10777164],"study_design_scores_gemma":[0.00003211255,0.000024382809,0.000042409152,0.000021199328,0.000018398177,0.000045613597,0.000021899234,0.92707986,0.0004019049,0.06870968,0.0035914655,0.000011022732],"about_ca_topic_score_codex":0.002253678,"about_ca_topic_score_gemma":0.0022231995,"teacher_disagreement_score":0.0085184965,"about_ca_system_score_codex":0.0013172445,"about_ca_system_score_gemma":0.0013088225,"threshold_uncertainty_score":0.02849716},"labels":[],"label_agreement":null},{"id":"W2020291377","doi":"10.5555/545381.545437","title":"Broadcast scheduling: when fairness is fine","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Scheduling (production processes); Latency (audio); Online algorithm; Competitive analysis; Server; Computer network; Approximation algorithm; Distributed computing; Parallel computing; Operating system; Algorithm; Upper and lower bounds; Mathematical optimization","score_opus":0.05081797835851215,"score_gpt":0.25180055192917605,"score_spread":0.2009825735706639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020291377","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15253246,0.0017554006,0.8241195,0.0022328568,0.00044672363,0.00016184419,0.00021704496,0.00073687226,0.017797304],"genre_scores_gemma":[0.9518555,0.00038963254,0.042467684,0.00029460186,0.0002828793,0.00008586872,0.00006797661,0.0001471717,0.0044086166],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99679416,0.0010093459,0.00009487829,0.0005618491,0.0006234795,0.0009163401],"domain_scores_gemma":[0.98511106,0.010304658,0.0010389088,0.0014250084,0.0012350692,0.0008852607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059985295,0.0008118037,0.0019753634,0.00064672023,0.0020878382,0.002798813,0.0025914859,0.0017370955,0.004462811],"category_scores_gemma":[0.026279742,0.00050873857,0.00045709868,0.0010483678,0.0015184091,0.0050967922,0.0019115609,0.0021016272,0.00057477114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025502148,0.00058490154,0.006175436,0.00047163572,0.00017206212,0.0005513786,0.00090115593,0.5361545,0.013667476,0.30227026,0.013474223,0.12302674],"study_design_scores_gemma":[0.00015227044,0.00015658588,0.0005823753,0.000027349994,0.000042198168,0.00016725263,0.00019018582,0.83716303,0.003199837,0.15478024,0.0035151762,0.000023596469],"about_ca_topic_score_codex":0.004164585,"about_ca_topic_score_gemma":0.0031069962,"teacher_disagreement_score":0.0059985295,"about_ca_system_score_codex":0.0023372408,"about_ca_system_score_gemma":0.0026598298,"threshold_uncertainty_score":0.031723678},"labels":[],"label_agreement":null},{"id":"W2020796742","doi":"10.1007/s00453-011-9611-5","title":"Computing Without Communicating: Ring Exploration by Asynchronous Oblivious Robots","year":2012,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; École de Technologie Supérieure; Université du Québec en Outaouais; University of Ottawa","funders":"","keywords":"Asynchronous communication; Robot; Ring (chemistry); Theory of computation; Computer science; Prime (order theory); Combinatorics; Theoretical computer science; Discrete mathematics; Algorithm; Mathematics; Topology (electrical circuits); Artificial intelligence; Computer network","score_opus":0.03405175304668747,"score_gpt":0.2886569309033074,"score_spread":0.25460517785661996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2020796742","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25938442,0.0011038892,0.7113301,0.0015902781,0.00020851534,0.00009090425,0.00013280309,0.0005812576,0.025577785],"genre_scores_gemma":[0.9544291,0.00030266412,0.04024196,0.00008131758,0.0000616235,0.000079032325,0.00003487673,0.00007588601,0.0046934797],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924004,0.000336149,0.000027791108,0.00013832869,0.000111370086,0.00014637897],"domain_scores_gemma":[0.9969073,0.0019532703,0.00022253499,0.0005279889,0.00014918494,0.0002397482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014184552,0.00041616586,0.00091417105,0.00041639604,0.0010059088,0.0015670588,0.001727605,0.0010006317,0.0035704072],"category_scores_gemma":[0.0065944996,0.0003893117,0.00051166717,0.00061583065,0.0019853625,0.0040845824,0.0023615372,0.0012356366,0.00040858748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010784528,0.00013741294,0.00068589865,0.00021152318,0.000069418806,0.00016581346,0.0003786285,0.50034654,0.005024066,0.4539081,0.0036092931,0.034384787],"study_design_scores_gemma":[0.00006894711,0.00007631001,0.00011352746,0.000011034906,0.000020573121,0.00003983118,0.000072882074,0.7697736,0.0014070183,0.22695404,0.0014451158,0.000017170203],"about_ca_topic_score_codex":0.00075059215,"about_ca_topic_score_gemma":0.0007386045,"teacher_disagreement_score":0.0035704072,"about_ca_system_score_codex":0.00053792354,"about_ca_system_score_gemma":0.00073004473,"threshold_uncertainty_score":0.011944175},"labels":[],"label_agreement":null},{"id":"W2022437016","doi":"10.1142/s1793830911001346","title":"TIME OPTIMAL ALGORITHMS FOR BLACK HOLE SEARCH IN RINGS","year":2011,"lang":"en","type":"article","venue":"Discrete Mathematics Algorithms and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Asynchronous communication; Focus (optics); Computer science; Black hole (networking); Algorithm; Ring (chemistry); Upper and lower bounds; Task (project management); Mathematics; Computer network; Engineering; Routing (electronic design automation); Physics","score_opus":0.045002723913948876,"score_gpt":0.2952494002916094,"score_spread":0.2502466763776605,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022437016","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043495607,0.00075669243,0.9462867,0.00046014617,0.00007247753,0.00022364887,0.00011829811,0.0013571245,0.0072293743],"genre_scores_gemma":[0.39456272,0.0005749652,0.59863585,0.00020534125,0.00010022757,0.00054533157,0.00031986166,0.00034901118,0.0047066775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975804,0.000759244,0.00015607361,0.000492674,0.00045269457,0.0005588388],"domain_scores_gemma":[0.99383074,0.004290299,0.0006943106,0.00062632933,0.0003080378,0.000250389],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028939105,0.001344119,0.0014431078,0.0011896855,0.0011753254,0.0019540212,0.0026001958,0.0018696693,0.005224044],"category_scores_gemma":[0.011353426,0.00069860177,0.0010315512,0.0013282436,0.0015185797,0.0042385673,0.0026193412,0.0013715827,0.0012007802],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008437643,0.0003238825,0.001376987,0.00038275713,0.000110120985,0.0001124022,0.00048476065,0.75026566,0.0045939703,0.10914975,0.0072746216,0.12508132],"study_design_scores_gemma":[0.00018282652,0.000118326716,0.00017409015,0.000022441438,0.000025830554,0.000062281346,0.00007830487,0.9319283,0.0015730585,0.064173155,0.0016414924,0.000019948335],"about_ca_topic_score_codex":0.002562818,"about_ca_topic_score_gemma":0.0029164806,"teacher_disagreement_score":0.005224044,"about_ca_system_score_codex":0.0018124526,"about_ca_system_score_gemma":0.0026789429,"threshold_uncertainty_score":0.017476201},"labels":[],"label_agreement":null},{"id":"W2025264288","doi":"10.1016/j.dam.2007.11.001","title":"Impact of memory size on graph exploration capability","year":2008,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Automaton; Theoretical computer science; Graph; Finite-state machine; Algorithm","score_opus":0.039807105362277787,"score_gpt":0.2876512014303654,"score_spread":0.2478440960680876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2025264288","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9803642,0.0014966761,0.006094485,0.0013298789,0.00014223786,0.000026559632,0.00065042754,0.0016642166,0.008231229],"genre_scores_gemma":[0.99309266,0.00035882354,0.0045011886,0.00009787147,0.00003166552,0.000028256123,0.0002885964,0.00029431007,0.0013067812],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99823797,0.00050021446,0.0001371134,0.00031029942,0.00024823318,0.0005662364],"domain_scores_gemma":[0.92471147,0.06373443,0.0016032413,0.0052215806,0.0029177307,0.0018116212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028549712,0.00073284307,0.00078400935,0.0014026125,0.00069922925,0.002054284,0.0019316457,0.0016805521,0.009656348],"category_scores_gemma":[0.05131395,0.00054429495,0.000458352,0.0019176333,0.00087808643,0.0066682966,0.0016015552,0.0009609569,0.0010556068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.023737187,0.0019830638,0.03723919,0.0016613499,0.0004379573,0.0014949533,0.0012674044,0.4984001,0.08355729,0.015114557,0.020245675,0.31486118],"study_design_scores_gemma":[0.001550898,0.0042285076,0.0142695205,0.00031570272,0.000850748,0.0014231134,0.0019268114,0.8149797,0.12648313,0.028356722,0.0054349587,0.00018015772],"about_ca_topic_score_codex":0.0019876852,"about_ca_topic_score_gemma":0.002759691,"teacher_disagreement_score":0.009656348,"about_ca_system_score_codex":0.0004998113,"about_ca_system_score_gemma":0.0017371054,"threshold_uncertainty_score":0.03230369},"labels":[],"label_agreement":null},{"id":"W2026266551","doi":"10.1016/j.ipl.2011.12.001","title":"Optimal strategies for the list update problem under the MRM alternative cost model","year":2011,"lang":"en","type":"article","venue":"Information Processing Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Combinatorics; Paging; Mathematics; Algorithm; Discrete mathematics","score_opus":0.05248951916879621,"score_gpt":0.2750355865265959,"score_spread":0.22254606735779967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026266551","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.063073166,0.0016617266,0.91492045,0.002551363,0.00013549154,0.00025900314,0.000505153,0.0003649001,0.016528709],"genre_scores_gemma":[0.68875694,0.0012538141,0.2843759,0.0005928006,0.00024247733,0.00057119475,0.0005916341,0.00027602343,0.023339195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987993,0.0006207789,0.00005627318,0.00014138619,0.0001997043,0.00018252188],"domain_scores_gemma":[0.9959979,0.0030120288,0.00031776505,0.00019743656,0.0003202619,0.00015469627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022712066,0.0009441395,0.001826575,0.0013420896,0.00048506106,0.002117484,0.0025516625,0.002599354,0.009780407],"category_scores_gemma":[0.009082046,0.0007317359,0.0006356952,0.0017606339,0.00092218677,0.0032879736,0.001267283,0.0016862346,0.00130784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000630354,0.00027128024,0.0006474192,0.00044415746,0.00010545511,0.00017050061,0.00019935629,0.6783806,0.0012182252,0.1838318,0.008508481,0.1255923],"study_design_scores_gemma":[0.000085193155,0.00008570867,0.0001898178,0.000032901036,0.000028325512,0.000044556375,0.000043882625,0.9352125,0.00031819634,0.06253155,0.0014021832,0.000025143307],"about_ca_topic_score_codex":0.0041652,"about_ca_topic_score_gemma":0.0047957953,"teacher_disagreement_score":0.009780407,"about_ca_system_score_codex":0.0016234647,"about_ca_system_score_gemma":0.001854305,"threshold_uncertainty_score":0.032718718},"labels":[],"label_agreement":null},{"id":"W2027982484","doi":"10.1145/1122480.1122499","title":"2005","year":2006,"lang":"en","type":"article","venue":"ACM SIGACT News","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Computer science; Column (typography); Information retrieval; Library science; Telecommunications; Geography; Archaeology","score_opus":0.018760005216208242,"score_gpt":0.25688321969390127,"score_spread":0.23812321447769302,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2027982484","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0010295594,0.0058962544,0.004917401,0.011389464,0.01553428,0.00012508748,0.018357186,0.0027725245,0.9399783],"genre_scores_gemma":[0.002706037,0.0031010592,0.0015150256,0.0023931041,0.0010956649,0.000051934676,0.010976814,0.0004403704,0.97772],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99946755,0.000040122788,0.00003848934,0.00016106597,0.00023071724,0.00006210937],"domain_scores_gemma":[0.9987877,0.000109023495,0.00005190138,0.00024654492,0.00058673177,0.00021812653],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005720941,0.0010140409,0.0008051298,0.0014187214,0.0011777113,0.0055608097,0.001404732,0.0019188748,0.66083103],"category_scores_gemma":[0.0021926549,0.00040657137,0.0005570854,0.0018487435,0.0004482126,0.002821656,0.001299047,0.0016031563,0.65957934],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000029920699,0.000018430372,0.0001410544,0.00006776784,0.000003707598,0.000029680778,0.000016648613,0.00006680245,0.00018104147,0.004899545,0.9269802,0.06756522],"study_design_scores_gemma":[0.000003752485,0.00000692552,0.00018789491,0.000047741356,0.0000017374389,0.000037047106,0.000017855557,0.00007972604,0.00009545472,0.0011447883,0.99837375,0.000003284094],"about_ca_topic_score_codex":0.0052503273,"about_ca_topic_score_gemma":0.009047839,"teacher_disagreement_score":0.33916897,"about_ca_system_score_codex":0.0019755522,"about_ca_system_score_gemma":0.001586428,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2030705938","doi":"10.1007/s10707-008-0053-4","title":"A meeting scheduling problem respecting time and space","year":2008,"lang":"en","type":"article","venue":"GeoInformatica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Voronoi diagram; Schedule; Scheduling (production processes); Graph; Spacetime; Computer science; Interval (graph theory); Mathematics; Combinatorics; Operations research; Theoretical computer science; Mathematical optimization","score_opus":0.015988497943991063,"score_gpt":0.22784294180583203,"score_spread":0.21185444386184096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030705938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1240583,0.0010319273,0.8474803,0.0022383933,0.00042085565,0.0004319237,0.001754339,0.00073243235,0.021851568],"genre_scores_gemma":[0.59895724,0.001064538,0.37925127,0.00030620824,0.0005429806,0.00037763562,0.0013986723,0.00047736062,0.017624125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99841785,0.0005319232,0.00010208923,0.0003818108,0.0003031293,0.000263173],"domain_scores_gemma":[0.9963207,0.0021764662,0.00044741118,0.00024163774,0.00025769693,0.0005560804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021012162,0.0017419544,0.0028492943,0.001568247,0.0013215955,0.003314043,0.0025546812,0.0030776495,0.008887831],"category_scores_gemma":[0.008183578,0.0010157364,0.0017647772,0.0038233667,0.0011022699,0.0034303863,0.0017624679,0.0022827084,0.001008959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009175359,0.0003326646,0.00087150355,0.0006319846,0.00021814139,0.00038940198,0.0002731007,0.8169982,0.008838595,0.08442182,0.009123751,0.07698338],"study_design_scores_gemma":[0.00021912673,0.00042521505,0.00045357394,0.000033633638,0.00009777334,0.0002448009,0.00019110477,0.9257164,0.002088881,0.063254,0.007237924,0.000037546055],"about_ca_topic_score_codex":0.0049464176,"about_ca_topic_score_gemma":0.0025095362,"teacher_disagreement_score":0.008887831,"about_ca_system_score_codex":0.0019511916,"about_ca_system_score_gemma":0.0022990503,"threshold_uncertainty_score":0.029732764},"labels":[],"label_agreement":null},{"id":"W2031025945","doi":"10.1007/s00224-007-9065-y","title":"Fault-Tolerant Sequential Scan","year":2007,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais; University of Ottawa","funders":"","keywords":"Computer science; Algorithm; Point (geometry); Line (geometry); Adversary; Construct (python library); Head (geology); Matching (statistics); Fault (geology); Order (exchange); Mathematics","score_opus":0.0263441281532681,"score_gpt":0.2829132204927016,"score_spread":0.25656909233943354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031025945","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10677041,0.0018630859,0.8705024,0.0012111948,0.00029984204,0.00017143569,0.00050542183,0.003509849,0.015166251],"genre_scores_gemma":[0.8749121,0.00052044936,0.11618522,0.00026177548,0.000121752484,0.00011808174,0.00040426242,0.0001979748,0.007278369],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998968,0.00020860722,0.00007402319,0.00021592298,0.0003896631,0.00014373864],"domain_scores_gemma":[0.99670285,0.0015320365,0.0002646065,0.0009089268,0.0004955083,0.000096175914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007737867,0.000565966,0.0012241628,0.0010203122,0.0006829307,0.0012357379,0.0015904943,0.0008914856,0.005107268],"category_scores_gemma":[0.0050210785,0.0004196957,0.00041778845,0.0018382401,0.000980365,0.0021868495,0.0012411263,0.0007884826,0.0005770463],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028277312,0.0002102983,0.0031248534,0.00057418767,0.0001617099,0.0005065256,0.00022592365,0.4498382,0.022035426,0.1327499,0.019134676,0.36861044],"study_design_scores_gemma":[0.00009986347,0.00019721105,0.00037534133,0.000020990254,0.000057448855,0.00035494604,0.000058844147,0.88100904,0.009644481,0.10396,0.004200764,0.000020993497],"about_ca_topic_score_codex":0.00158288,"about_ca_topic_score_gemma":0.0025474182,"teacher_disagreement_score":0.005107268,"about_ca_system_score_codex":0.0008269914,"about_ca_system_score_gemma":0.0014641121,"threshold_uncertainty_score":0.017085493},"labels":[],"label_agreement":null},{"id":"W2031037037","doi":"10.1007/s12369-011-0102-2","title":"Regression Analysis of Multi-Rendezvous Recharging Route in Multi-Robot Environment","year":2011,"lang":"en","type":"article","venue":"International Journal of Social Robotics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Robot; Tree traversal; Robotics; Rendezvous; Computer science; Process (computing); Ordinary least squares; Mobile robot; Energy (signal processing); Real-time computing; Artificial intelligence; Simulation; Engineering; Machine learning; Algorithm; Mathematics; Statistics","score_opus":0.11217025211119643,"score_gpt":0.3399269234462845,"score_spread":0.2277566713350881,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031037037","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6004134,0.0006465996,0.3948677,0.00030734987,0.00008102005,0.000034167413,0.000358089,0.0006397293,0.0026520141],"genre_scores_gemma":[0.9880475,0.00012853144,0.009474739,0.000011144159,0.000011796401,0.000017544213,0.00019227828,0.00004970958,0.002066784],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99970645,0.00006401354,0.000009464391,0.000103520084,0.00006122275,0.000055324243],"domain_scores_gemma":[0.99910897,0.00042618377,0.00014143325,0.000051146755,0.00024008047,0.00003221546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051352265,0.0005524797,0.0005930962,0.00069857383,0.00031057524,0.00053712405,0.00075967563,0.00057007466,0.0012993037],"category_scores_gemma":[0.0022816143,0.00026709927,0.0005762228,0.00088513206,0.0003145255,0.0005711137,0.00036741473,0.00060096465,0.00032147483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008135409,0.000032250497,0.005798959,0.000053567906,0.000052361305,0.000099203804,0.000055427743,0.9735299,0.0030004373,0.0015895399,0.00054111937,0.015165992],"study_design_scores_gemma":[0.0000011012717,0.000009122148,0.0015919659,0.000001332131,0.000004623977,0.000011719527,0.000012130908,0.9977107,0.00037000288,0.00020332164,0.00008010944,0.000003816057],"about_ca_topic_score_codex":0.0212434,"about_ca_topic_score_gemma":0.010098868,"teacher_disagreement_score":0.0212434,"about_ca_system_score_codex":0.00053195463,"about_ca_system_score_gemma":0.0005163894,"threshold_uncertainty_score":0.042239487},"labels":[],"label_agreement":null},{"id":"W2031698396","doi":"10.1002/net.20095","title":"Black hole search in common interconnection networks","year":2005,"lang":"en","type":"article","venue":"Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science; Hypercube; Star (game theory); Interconnection; Polygon mesh; Black hole (networking); Topology (electrical circuits); TRACE (psycholinguistics); Chordal graph; Network topology; Torus; Host (biology); Routing (electronic design automation); Theoretical computer science; Combinatorics; Computer network; Mathematics; Parallel computing; Routing protocol; Graph","score_opus":0.0211345147778055,"score_gpt":0.2741044860498077,"score_spread":0.2529699712720022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031698396","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53012645,0.0011177306,0.45365658,0.000964358,0.00005268287,0.00011821449,0.00012552057,0.00018082806,0.013657578],"genre_scores_gemma":[0.95231116,0.00023988083,0.04442328,0.000058297435,0.00001599124,0.00007156477,0.000073416595,0.000020100515,0.002786343],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928004,0.00031517667,0.0000241769,0.00013064564,0.000099781515,0.00015020464],"domain_scores_gemma":[0.99705386,0.002101907,0.00034274327,0.00016323189,0.0001805622,0.00015767249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012428801,0.0004841785,0.0008999187,0.0009971928,0.00079651014,0.0008835547,0.0009802273,0.001082177,0.0019137429],"category_scores_gemma":[0.005031762,0.00030838922,0.00035779635,0.0010436161,0.0015077788,0.0016031219,0.0014783865,0.0004591061,0.00013635634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022277376,0.000057380734,0.0011081923,0.00008328886,0.000057985795,0.00021495736,0.00016444693,0.85614306,0.0008142608,0.11436667,0.0017453999,0.025021618],"study_design_scores_gemma":[0.000049917744,0.000047820093,0.00020923222,0.00001193708,0.000012574423,0.000059521473,0.00006832987,0.8699843,0.000504603,0.1277795,0.0012645641,0.00000771015],"about_ca_topic_score_codex":0.003546559,"about_ca_topic_score_gemma":0.0026791578,"teacher_disagreement_score":0.003546559,"about_ca_system_score_codex":0.0010091177,"about_ca_system_score_gemma":0.000531062,"threshold_uncertainty_score":0.0073217154},"labels":[],"label_agreement":null},{"id":"W2032767523","doi":"10.7771/1932-6246.1090","title":"Human Performance on the Traveling Salesman and Related Problems: A Review","year":2011,"lang":"en","type":"review","venue":"The Journal of Problem Solving","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":93,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Travelling salesman problem; Computer science; Operations research; Mathematics; Algorithm","score_opus":0.09076530393819074,"score_gpt":0.3128578328087348,"score_spread":0.22209252887054406,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032767523","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00032635144,0.99765754,0.0003165829,0.00030852694,0.0000855793,0.0000046446394,0.00001498972,0.0000066502266,0.0012791655],"genre_scores_gemma":[0.0013222175,0.99776924,0.0003892237,0.00009046887,0.00012939554,0.00000665337,0.000023188903,0.000001984819,0.00026771342],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995172,0.00009520673,0.00007503856,0.00010297945,0.00017515673,0.000034387507],"domain_scores_gemma":[0.9979589,0.0013635425,0.0001488272,0.00003742895,0.00041970055,0.00007163295],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011612291,0.0011208946,0.0017312057,0.0026778178,0.00034378294,0.0012858969,0.0011484502,0.0016694751,0.0027138214],"category_scores_gemma":[0.002950748,0.00041589836,0.00043672597,0.0040563466,0.0010101652,0.0023641898,0.0006441492,0.0011439392,0.0020031435],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005012159,0.000089215246,0.0005777993,0.012082726,0.00008198555,0.000092164686,0.00011902203,0.0006400216,0.00048822418,0.0039361417,0.018457837,0.96338475],"study_design_scores_gemma":[0.000029614594,0.00042099235,0.0071539492,0.012621559,0.00023890188,0.0022456415,0.00046291036,0.000475973,0.001081517,0.0125276325,0.9626385,0.0001028463],"about_ca_topic_score_codex":0.0025590179,"about_ca_topic_score_gemma":0.0028439239,"teacher_disagreement_score":0.0027138214,"about_ca_system_score_codex":0.0008409278,"about_ca_system_score_gemma":0.0014519728,"threshold_uncertainty_score":0.0090786815},"labels":[],"label_agreement":null},{"id":"W2032839108","doi":"10.1109/iros.2012.6386049","title":"Multi-robot exploration and rendezvous on graphs","year":2012,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Rendezvous; Robot; Task (project management); Computer science; Set (abstract data type); Ranking (information retrieval); Artificial intelligence; Distributed computing; Engineering","score_opus":0.09137424760496787,"score_gpt":0.30284271101499727,"score_spread":0.2114684634100294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032839108","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48961616,0.00084626395,0.4980527,0.0006079918,0.00004408148,0.00018513037,0.00037205723,0.00059850526,0.009677073],"genre_scores_gemma":[0.9073214,0.0003436603,0.0878512,0.000058718426,0.000016354794,0.00013582523,0.00025127074,0.00011334951,0.003908316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991504,0.00038273883,0.000026213109,0.00016959751,0.00012374611,0.00014736195],"domain_scores_gemma":[0.99621946,0.002702931,0.00044053915,0.00024241314,0.00013376428,0.00026096028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000895954,0.001256341,0.0011496148,0.0010595678,0.0010557893,0.0008342254,0.0013429277,0.0011042688,0.0025935462],"category_scores_gemma":[0.0040453793,0.00041901352,0.0008520075,0.0012325135,0.0011891027,0.00183622,0.0013212514,0.00065293757,0.00030582905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013347293,0.000034736375,0.00047384412,0.00006867486,0.00003053034,0.00014990788,0.000066810804,0.98191226,0.0014817242,0.0077739153,0.00034136532,0.0075327107],"study_design_scores_gemma":[0.000032554228,0.00007609355,0.0003779585,0.000008768623,0.00001259192,0.00007494363,0.000071112845,0.97634727,0.0011068701,0.021135725,0.00074567035,0.000010400512],"about_ca_topic_score_codex":0.0042062025,"about_ca_topic_score_gemma":0.0047659692,"teacher_disagreement_score":0.0042062025,"about_ca_system_score_codex":0.0011788483,"about_ca_system_score_gemma":0.00064615806,"threshold_uncertainty_score":0.0086762905},"labels":[],"label_agreement":null},{"id":"W2032986039","doi":"10.1145/2632149","title":"Placing Sensors for Area Coverage in a Complex Environment by a Team of Robots","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Sensor Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Huawei Technologies (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Robot; Real-time computing; Mobile robot; Vertex (graph theory); Path (computing); Algorithm; Wireless sensor network; Computer vision; Artificial intelligence; Computer network; Theoretical computer science","score_opus":0.025516847205928898,"score_gpt":0.24283882030925394,"score_spread":0.21732197310332504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032986039","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17765465,0.00017448561,0.81917626,0.00017745356,0.000034466524,0.00009485433,0.00004197939,0.00083217496,0.0018136513],"genre_scores_gemma":[0.7541503,0.00014400505,0.24392013,0.000048621197,0.000019211186,0.00013068927,0.00007951523,0.00006978142,0.0014376985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995123,0.00011473591,0.000022874945,0.00012017308,0.00014219282,0.00008774384],"domain_scores_gemma":[0.9990062,0.0004209576,0.00013508071,0.00022962842,0.00010248887,0.00010564011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071244634,0.0007647608,0.0006805806,0.00045114267,0.00064677506,0.0005852493,0.0013417867,0.00086327095,0.0015507784],"category_scores_gemma":[0.0020857987,0.00046942488,0.0005486515,0.0005192514,0.000741726,0.0009157111,0.0017139056,0.0006334278,0.0003951574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025835462,0.00013097134,0.0036308835,0.00015093898,0.00006769246,0.0003554264,0.0004793804,0.86751914,0.029596083,0.0043899603,0.001484184,0.09193699],"study_design_scores_gemma":[0.000036720816,0.00016009835,0.0006598936,0.0000079883075,0.00001602605,0.00009830244,0.00013616972,0.99049264,0.0054490888,0.0017576818,0.0011764992,0.00000884845],"about_ca_topic_score_codex":0.0037457105,"about_ca_topic_score_gemma":0.0038318648,"teacher_disagreement_score":0.0037457105,"about_ca_system_score_codex":0.00055574445,"about_ca_system_score_gemma":0.00076024595,"threshold_uncertainty_score":0.007447779},"labels":[],"label_agreement":null},{"id":"W2033427227","doi":"10.1145/1711475.1711499","title":"Introduction to the SIGACT news online algorithms column","year":2010,"lang":"en","type":"article","venue":"ACM SIGACT News","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paging; Column (typography); Computer science; Competitive analysis; Quarter (Canadian coin); Online algorithm; Algorithm; Operations research; Information retrieval; Telecommunications; History; Mathematics; Upper and lower bounds","score_opus":0.02205290292875095,"score_gpt":0.2866052760490196,"score_spread":0.26455237312026864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033427227","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013702803,0.02460225,0.017836694,0.17217447,0.38395151,0.00040923778,0.013460283,0.0049359575,0.38125932],"genre_scores_gemma":[0.006366319,0.01435988,0.011304907,0.036777414,0.15551794,0.0003030987,0.00847276,0.0032565582,0.7636412],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978254,0.00034558534,0.0001364892,0.00029155565,0.0011957989,0.00020527946],"domain_scores_gemma":[0.9882059,0.0031123608,0.00065757416,0.001109575,0.0047539687,0.002160599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027429108,0.0016916639,0.0016424677,0.0026182751,0.0025270972,0.011537609,0.002099844,0.0029575443,0.24526884],"category_scores_gemma":[0.010821603,0.0007071074,0.0011791127,0.0036208683,0.0011338228,0.0064990674,0.0015163284,0.0059955367,0.19608623],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014623231,0.000016496484,0.000029791787,0.00002183898,0.0000028440659,0.0000061134983,0.000001908083,0.000052221083,0.000029446022,0.00088456133,0.988381,0.010559225],"study_design_scores_gemma":[0.000016191687,0.000025050664,0.0002510892,0.000071193506,0.000007136913,0.00004229685,0.00002458557,0.000563334,0.00013132296,0.0019252758,0.9969292,0.000013322374],"about_ca_topic_score_codex":0.005010864,"about_ca_topic_score_gemma":0.014002028,"teacher_disagreement_score":0.24526884,"about_ca_system_score_codex":0.0026604913,"about_ca_system_score_gemma":0.0027302539,"threshold_uncertainty_score":0.820506},"labels":[],"label_agreement":null},{"id":"W2033561606","doi":"10.1145/2601071","title":"Faster Algorithms for Semi-Matching Problems","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Algorithm; Combinatorics; Bipartite graph; Binary logarithm; Matching (statistics); Mathematics; Simple (philosophy); Running time; Time complexity; Scheduling (production processes); Upper and lower bounds; Computer science; Discrete mathematics; Graph; Mathematical optimization","score_opus":0.036387628298889294,"score_gpt":0.28501888826687455,"score_spread":0.24863125996798524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033561606","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013654431,0.0012555879,0.9710916,0.00085603364,0.00020679881,0.00025819792,0.00035675842,0.004624142,0.007696423],"genre_scores_gemma":[0.11103306,0.0009783983,0.8779424,0.00053689315,0.00030361552,0.0005661649,0.0017832259,0.001143751,0.005712593],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961194,0.0008734002,0.0002643878,0.0009184372,0.0012457019,0.0005788424],"domain_scores_gemma":[0.99320203,0.0033090408,0.00044764104,0.0019692602,0.00079637795,0.00027570763],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027595481,0.0025681537,0.0025840104,0.0026365886,0.0013932256,0.0028284367,0.0045970217,0.0028252339,0.021287467],"category_scores_gemma":[0.011900497,0.00126612,0.0028914544,0.00457029,0.0011148767,0.011085796,0.004650252,0.0033610798,0.006209476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001162111,0.0008988485,0.0013299763,0.0016350923,0.0002732373,0.00021754169,0.0005075381,0.16407338,0.014091061,0.128946,0.031258866,0.6556064],"study_design_scores_gemma":[0.00040035177,0.0002006124,0.00040858434,0.00008215508,0.00007934552,0.00032330686,0.00014917534,0.6477161,0.005648249,0.32488784,0.020057676,0.000046598718],"about_ca_topic_score_codex":0.001758084,"about_ca_topic_score_gemma":0.0028091124,"teacher_disagreement_score":0.021287467,"about_ca_system_score_codex":0.0018369105,"about_ca_system_score_gemma":0.0019969265,"threshold_uncertainty_score":0.07121366},"labels":[],"label_agreement":null},{"id":"W2033661244","doi":"10.1145/1435375.1435378","title":"Competitive buffer management for shared-memory switches","year":2008,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Competitive analysis; Computer science; Network packet; Queue; Buffer (optical fiber); Preemption; Constraint (computer-aided design); Partition (number theory); Upper and lower bounds; Online algorithm; Computer network; Operating system; Algorithm; Mathematics; Telecommunications","score_opus":0.03958810005221866,"score_gpt":0.2723584283068775,"score_spread":0.23277032825465885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2033661244","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42621228,0.0020615864,0.55339813,0.0013246931,0.00020175004,0.00019450948,0.00015891883,0.00039810513,0.016050022],"genre_scores_gemma":[0.97657335,0.00027682385,0.021597052,0.00010748371,0.00006705229,0.000055147713,0.000044139084,0.000022694434,0.0012562543],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982565,0.00052358594,0.00005281372,0.00022530578,0.00045392686,0.00048789845],"domain_scores_gemma":[0.9953843,0.0028811516,0.00046141414,0.00023523907,0.0005267342,0.0005111643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022363756,0.0009498781,0.0011660546,0.0005744362,0.0012416489,0.0027182978,0.0025578435,0.0014215958,0.0026370524],"category_scores_gemma":[0.008652984,0.0003608994,0.00043261662,0.00093258754,0.0010500201,0.0030191578,0.001482131,0.0010643192,0.00020292135],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00068536977,0.00038302253,0.0015526525,0.00020809851,0.00009141079,0.0002495737,0.00018379944,0.7520374,0.008198553,0.20073693,0.0031840529,0.032489218],"study_design_scores_gemma":[0.00004006009,0.00007732138,0.00013002564,0.0000046270043,0.000012585084,0.000041952364,0.000028503877,0.97164404,0.0011074557,0.02632779,0.00057798275,0.000007633879],"about_ca_topic_score_codex":0.003943108,"about_ca_topic_score_gemma":0.0028472142,"teacher_disagreement_score":0.003943108,"about_ca_system_score_codex":0.0026094276,"about_ca_system_score_gemma":0.0020156337,"threshold_uncertainty_score":0.01893282},"labels":[],"label_agreement":null},{"id":"W2036433802","doi":"10.1016/j.dam.2009.03.003","title":"Counting feasible solutions of the traveling salesman problem with pickups and deliveries is <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" altimg=\"si3.gif\" display=\"inline\" overflow=\"scroll\"><mml:mi>#</mml:mi><mml:mi>P</mml:mi></mml:math>-complete","year":2009,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; HEC Montréal","funders":"","keywords":"Travelling salesman problem; Mathematics; Combinatorics; Algorithm; Mathematical optimization; Discrete mathematics","score_opus":0.02324561272859016,"score_gpt":0.2381692861386059,"score_spread":0.21492367341001575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2036433802","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11092302,0.0015081236,0.7842514,0.0058529694,0.0002886124,0.000992765,0.01699941,0.0015540285,0.077629685],"genre_scores_gemma":[0.33302072,0.0022334985,0.59515595,0.0005337304,0.000348412,0.0016911079,0.021191275,0.0011099343,0.04471541],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99582905,0.0013563649,0.00036465217,0.0010177657,0.0008766826,0.00055550446],"domain_scores_gemma":[0.9835127,0.0124499975,0.0015513211,0.0009364336,0.0009789781,0.0005704837],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042874245,0.0030054187,0.0032092184,0.00331695,0.0018868642,0.00870277,0.004534999,0.0033529482,0.028756006],"category_scores_gemma":[0.02449289,0.0020303067,0.0031681694,0.0076473937,0.0016941767,0.009874096,0.002182351,0.0036337555,0.0036982638],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007822092,0.0005829721,0.004123009,0.002063245,0.00044077222,0.00040132154,0.00048287906,0.25337163,0.0022473861,0.5295867,0.04819286,0.15772505],"study_design_scores_gemma":[0.00019360553,0.00015890086,0.0010420034,0.00019138206,0.00014654263,0.00022101274,0.00018816537,0.31325176,0.00237159,0.670446,0.011712007,0.00007703314],"about_ca_topic_score_codex":0.0051366007,"about_ca_topic_score_gemma":0.00786577,"teacher_disagreement_score":0.028756006,"about_ca_system_score_codex":0.0032769488,"about_ca_system_score_gemma":0.0046015345,"threshold_uncertainty_score":0.09619838},"labels":[],"label_agreement":null},{"id":"W2038319432","doi":"10.1016/j.ic.2008.07.005","title":"Tree exploration with advice","year":2008,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Advice (programming); Tree (set theory); Forestry; Computer science; Data science; Geography; Mathematics; Combinatorics","score_opus":0.024859649797871156,"score_gpt":0.24018585644940837,"score_spread":0.21532620665153723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038319432","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05566914,0.001292468,0.8632355,0.0017768956,0.00039170033,0.00025711887,0.00096065394,0.012996445,0.063420214],"genre_scores_gemma":[0.39223894,0.00052153843,0.5683169,0.00062572135,0.00014233938,0.00022141011,0.0011529551,0.0022699798,0.03451031],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99914885,0.00025963437,0.000041074996,0.00014035871,0.00029437133,0.000115800736],"domain_scores_gemma":[0.9974043,0.0014473023,0.00006138584,0.00068171055,0.00029687327,0.000108445754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008287797,0.0006257748,0.000892346,0.0010484284,0.00071938115,0.0011634812,0.0010414296,0.0011703332,0.017968144],"category_scores_gemma":[0.008084506,0.00041492085,0.00089491653,0.0010185286,0.00083554356,0.0020364579,0.0022231382,0.0019991724,0.0037364175],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007990856,0.00024011718,0.0023049137,0.0005621138,0.00008597897,0.00034400856,0.0006897127,0.04065366,0.010990792,0.1484241,0.054109644,0.74079585],"study_design_scores_gemma":[0.00014211681,0.00015447378,0.00059648906,0.00017555864,0.000116266034,0.0003620338,0.00016340241,0.46194458,0.011855964,0.45874825,0.065704115,0.000036701447],"about_ca_topic_score_codex":0.001420307,"about_ca_topic_score_gemma":0.0036922689,"teacher_disagreement_score":0.017968144,"about_ca_system_score_codex":0.0004994836,"about_ca_system_score_gemma":0.0009252006,"threshold_uncertainty_score":0.060109437},"labels":[],"label_agreement":null},{"id":"W2038655901","doi":"10.1016/j.dam.2011.10.027","title":"Strong and weak edges of a graph and linkages with the vertex cover problem","year":2011,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Edge cover; Vertex cover; Mathematics; Combinatorics; Vertex (graph theory); Neighbourhood (mathematics); Feedback vertex set; Time complexity; Graph; Discrete mathematics","score_opus":0.023108284779005294,"score_gpt":0.22237611605044405,"score_spread":0.19926783127143877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2038655901","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.42081857,0.003263538,0.48825747,0.0057631494,0.00027810983,0.00014525895,0.0009107897,0.00017109356,0.08039203],"genre_scores_gemma":[0.8381218,0.0030454167,0.12401743,0.00048668403,0.00071532256,0.0002706367,0.0008859237,0.00017246805,0.03228431],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99900144,0.0005033443,0.000036647954,0.00017471444,0.00018979637,0.00009399634],"domain_scores_gemma":[0.9929174,0.005218903,0.0008161982,0.00027342397,0.00024742653,0.0005265938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016912775,0.00077934196,0.00079897244,0.0020842003,0.0018114074,0.0027602792,0.0016874976,0.003469055,0.011475189],"category_scores_gemma":[0.011046674,0.0006955688,0.00085692643,0.0035107075,0.0020230755,0.007320297,0.0025905506,0.0024424966,0.0007040191],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011860237,0.00007662381,0.0014749927,0.00011304627,0.000032967877,0.00020164922,0.00026188514,0.033621598,0.000538386,0.940035,0.003031613,0.020493658],"study_design_scores_gemma":[0.000017458577,0.000023363495,0.00035168318,0.000025637668,0.000017734628,0.000105800325,0.0001338396,0.03913535,0.00017257032,0.95623773,0.003768788,0.000009967102],"about_ca_topic_score_codex":0.00086184946,"about_ca_topic_score_gemma":0.0007283127,"teacher_disagreement_score":0.011475189,"about_ca_system_score_codex":0.00071679265,"about_ca_system_score_gemma":0.0005275234,"threshold_uncertainty_score":0.038388312},"labels":[],"label_agreement":null},{"id":"W2039936247","doi":"10.1016/j.tcs.2005.07.014","title":"Graph exploration by a finite automaton","year":2005,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":176,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Traverse; Combinatorics; Planar graph; Mathematics; Graph; Discrete mathematics; Butterfly graph; Robot; Regular graph; Upper and lower bounds; Voltage graph; Computer science; Line graph; Artificial intelligence","score_opus":0.013465128249734063,"score_gpt":0.2579631548572839,"score_spread":0.24449802660754982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2039936247","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34897596,0.0004381552,0.6217843,0.0014607932,0.00015156137,0.00011267392,0.00035582142,0.0018459483,0.024874857],"genre_scores_gemma":[0.89816654,0.00015197787,0.09494936,0.00011264992,0.000023402912,0.00013730345,0.0001485573,0.00016377248,0.00614637],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995484,0.00016416471,0.000025148283,0.00012828395,0.000076105316,0.000057822937],"domain_scores_gemma":[0.9963966,0.0028083592,0.00011028745,0.00037876278,0.00015889073,0.00014704089],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004871408,0.00036412582,0.0007016008,0.0007656249,0.0011145873,0.0013885967,0.0011616362,0.0013751666,0.006801763],"category_scores_gemma":[0.0044520022,0.00040949427,0.001352633,0.00075144815,0.0017457281,0.0023047677,0.001599216,0.0012751179,0.00042516337],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048770188,0.00015310028,0.0022150462,0.00026924134,0.00011086787,0.00044066453,0.0006469222,0.31590888,0.010792391,0.61635345,0.0029360119,0.049685758],"study_design_scores_gemma":[0.0000488735,0.000054876375,0.00017495362,0.000020809184,0.000029110424,0.000075259966,0.000058527006,0.65498036,0.001765682,0.34119138,0.0015831789,0.000017000037],"about_ca_topic_score_codex":0.0027396532,"about_ca_topic_score_gemma":0.0032430692,"teacher_disagreement_score":0.006801763,"about_ca_system_score_codex":0.0009321412,"about_ca_system_score_gemma":0.00087705575,"threshold_uncertainty_score":0.022754133},"labels":[],"label_agreement":null},{"id":"W2041241584","doi":"10.1016/j.tcs.2014.07.013","title":"Exploring an unknown dangerous graph with a constant number of tokens","year":2014,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Vedecká Grantová Agentúra MŠVVaŠ SR a SAV","keywords":"Asynchronous communication; Security token; Computer science; Constant (computer programming); Graph; Node (physics); Protocol (science); Theoretical computer science; Simple (philosophy); Computer network","score_opus":0.040970488097334945,"score_gpt":0.2704389198655607,"score_spread":0.22946843176822573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041241584","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53136665,0.00022630843,0.4490897,0.0024673988,0.00016657267,0.00015988675,0.00066791684,0.0011404452,0.014715095],"genre_scores_gemma":[0.7503092,0.0001261324,0.2419592,0.0002231008,0.000041064563,0.00008052305,0.0004864811,0.00033850444,0.0064358274],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952567,0.00013223111,0.000016262617,0.00013991477,0.00009501171,0.00009100835],"domain_scores_gemma":[0.9970644,0.0021180734,0.00015489233,0.00026782812,0.00014421095,0.0002506777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00062293396,0.0007101849,0.00079811213,0.00095050404,0.0013705291,0.0010029494,0.0023093962,0.0023085834,0.006167311],"category_scores_gemma":[0.0063657328,0.0006745122,0.0011440864,0.0006932271,0.0017153028,0.003765362,0.0021728592,0.0020351384,0.0006202405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013086604,0.00034165985,0.004431866,0.000433823,0.00012211301,0.0019492912,0.00045728864,0.8182605,0.009764086,0.11948626,0.0050317366,0.03841266],"study_design_scores_gemma":[0.00006156717,0.00007444599,0.00021195861,0.000018542618,0.000032872013,0.00017057703,0.00013833208,0.9030943,0.0022290454,0.09256366,0.0013897093,0.0000149487],"about_ca_topic_score_codex":0.0037321192,"about_ca_topic_score_gemma":0.0056064064,"teacher_disagreement_score":0.006167311,"about_ca_system_score_codex":0.0009353582,"about_ca_system_score_gemma":0.0012723331,"threshold_uncertainty_score":0.02063173},"labels":[],"label_agreement":null},{"id":"W2041785607","doi":"10.1109/ccece.2006.277605","title":"Localization of a Team of Heterogeneous Robots for a Distributed Sensing Task","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Robot; Odometry; Computer science; Sonar; Task (project management); Context (archaeology); Mobile robot; Artificial intelligence; Computer vision; Collision avoidance; Process (computing); Position (finance); Human–computer interaction; Engineering; Collision","score_opus":0.013320595480649183,"score_gpt":0.24530126153545928,"score_spread":0.2319806660548101,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041785607","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019079044,0.000058077596,0.97975177,0.00010118485,0.000013915857,0.000044230746,0.000008555758,0.00010511912,0.0008381938],"genre_scores_gemma":[0.51531494,0.00015527583,0.48019645,0.00007746053,0.00005361805,0.00030682446,0.00006688599,0.000037642676,0.0037908799],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993705,0.0001880676,0.000029325583,0.00019260428,0.00014824659,0.00007127568],"domain_scores_gemma":[0.999453,0.00021739268,0.00009870517,0.000097581644,0.000062465944,0.00007098748],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010517221,0.0005788311,0.0008351419,0.0004377446,0.0008562119,0.00079835556,0.0012834284,0.0009986336,0.001999746],"category_scores_gemma":[0.0017302914,0.00034692354,0.0007005629,0.00045188575,0.00071633206,0.0011468453,0.0018070679,0.00069284276,0.000518931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035462584,0.00019131083,0.0018603024,0.00027036603,0.00016514232,0.0007935182,0.00085445715,0.77247137,0.03740976,0.035171658,0.001530027,0.14892745],"study_design_scores_gemma":[0.00006254887,0.00026624431,0.00037453804,0.000014846318,0.000041657666,0.0001132403,0.00026460103,0.97868335,0.0043714754,0.0125270495,0.003263791,0.000016704857],"about_ca_topic_score_codex":0.0015416743,"about_ca_topic_score_gemma":0.0014666085,"teacher_disagreement_score":0.001999746,"about_ca_system_score_codex":0.00054612913,"about_ca_system_score_gemma":0.00079365534,"threshold_uncertainty_score":0.006689787},"labels":[],"label_agreement":null},{"id":"W2042651328","doi":"10.1109/ieem.2012.6837983","title":"Virtual depot approximation for the transshipment problem","year":2012,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Transshipment (information security); Depot; Mathematical optimization; Computer science; On demand; Operations research; Mathematics","score_opus":0.03850969404749474,"score_gpt":0.2714792940498256,"score_spread":0.23296960000233088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042651328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027004426,0.0007224561,0.9657318,0.00034841584,0.00009992172,0.000040400297,0.00016425956,0.0003065926,0.005581678],"genre_scores_gemma":[0.68344414,0.0011635274,0.30811623,0.00021856195,0.00009882318,0.00017523886,0.0005355573,0.00022426262,0.006023707],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99945766,0.00020273872,0.000017350583,0.000071046125,0.0001401165,0.00011107746],"domain_scores_gemma":[0.9986951,0.0007844496,0.00011570245,0.00011626745,0.00014291012,0.00014560611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088060164,0.0010938618,0.0013018729,0.00054546277,0.0005306944,0.0012087311,0.0018372751,0.0012051464,0.0049980474],"category_scores_gemma":[0.0034036087,0.00047473024,0.00077153585,0.0010923987,0.000807397,0.0015780035,0.0014114045,0.001904643,0.0006111775],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008638487,0.000032522574,0.00027593193,0.00004291404,0.000013253071,0.000043451084,0.000016357526,0.97956663,0.0003026632,0.011205826,0.0012056862,0.007208419],"study_design_scores_gemma":[0.0000058565347,0.000010094635,0.000025927802,0.0000034009356,0.0000024392561,0.000011905623,0.000004670671,0.9957968,0.000078348436,0.0036714277,0.00038746785,0.0000017365741],"about_ca_topic_score_codex":0.0073616947,"about_ca_topic_score_gemma":0.005794145,"teacher_disagreement_score":0.0073616947,"about_ca_system_score_codex":0.0011952741,"about_ca_system_score_gemma":0.0013390554,"threshold_uncertainty_score":0.016720176},"labels":[],"label_agreement":null},{"id":"W2042736474","doi":"10.1007/s11036-006-4470-z","title":"Competitive Algorithms for Maintaining a Mobile Center","year":2006,"lang":"en","type":"article","venue":"Mobile Networks and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"","keywords":"Center (category theory); Euclidean geometry; Computer science; Euclidean distance; Set (abstract data type); Bounded function; Algorithm; Plane (geometry); Facility location problem; Mathematical optimization; Mathematics; Mathematical analysis; Geometry; Artificial intelligence","score_opus":0.010216024901648746,"score_gpt":0.2623748918661403,"score_spread":0.2521588669644916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042736474","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027083656,0.0007322161,0.9572258,0.00083777955,0.00017441396,0.00018595507,0.00016028249,0.0006183376,0.012981472],"genre_scores_gemma":[0.57831687,0.00083438243,0.40105245,0.00045512477,0.00047049765,0.0005498721,0.0004639951,0.0003871866,0.017469585],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843436,0.00046651543,0.000057035355,0.00029140853,0.00044896966,0.00030171702],"domain_scores_gemma":[0.9941871,0.003375458,0.00044801386,0.0006418574,0.0008094353,0.000538117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024905019,0.0013608912,0.002711975,0.0017247243,0.0022389723,0.0029540127,0.006088434,0.0042489525,0.007921901],"category_scores_gemma":[0.012245998,0.00079283485,0.0009474123,0.0031025596,0.0024090952,0.00428944,0.0029643124,0.0026260142,0.0016883268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058956235,0.00030122942,0.0007063934,0.00022786646,0.00010280987,0.00010663501,0.00025465328,0.4838362,0.0019467782,0.3853295,0.019437982,0.10716029],"study_design_scores_gemma":[0.00012092296,0.000098246695,0.00009343035,0.000012694142,0.00003017564,0.00007013518,0.000048496186,0.89960605,0.0005765654,0.09604993,0.0032753318,0.000018086668],"about_ca_topic_score_codex":0.0046190596,"about_ca_topic_score_gemma":0.0036976896,"teacher_disagreement_score":0.007921901,"about_ca_system_score_codex":0.0022777803,"about_ca_system_score_gemma":0.0023459217,"threshold_uncertainty_score":0.026501417},"labels":[],"label_agreement":null},{"id":"W2043815754","doi":"10.1007/s10878-013-9634-8","title":"An optimal randomized online algorithm for the $$k$$ k -Canadian Traveller Problem on node-disjoint paths","year":2013,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Competitive analysis; Randomized algorithm; Theory of computation; Disjoint sets; Online algorithm; Shortest path problem; Computer science; Node (physics); Graph; Combinatorics; Path (computing); Algorithm; Upper and lower bounds; Enhanced Data Rates for GSM Evolution; Mathematics; Discrete mathematics; Artificial intelligence; Computer network","score_opus":0.014345798641235114,"score_gpt":0.2585192954949509,"score_spread":0.24417349685371578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043815754","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2195997,0.0017076491,0.66456056,0.007444151,0.0009075918,0.0038110996,0.0095393555,0.009468022,0.082961835],"genre_scores_gemma":[0.42812216,0.0005730549,0.53318435,0.0009258587,0.0002003498,0.0012659503,0.008317052,0.0010117119,0.026399577],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99773836,0.000441802,0.00008501046,0.0007772253,0.0003089671,0.0006485788],"domain_scores_gemma":[0.99558926,0.00251052,0.00026733725,0.00056886475,0.0003860119,0.0006780699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016116174,0.0030437834,0.004240959,0.0022414322,0.003483916,0.0040921816,0.008950352,0.0049842647,0.034197338],"category_scores_gemma":[0.0070639923,0.0015817975,0.0019635016,0.0037737836,0.0021894493,0.0062942547,0.0043836664,0.0038437853,0.004010078],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00246409,0.001652251,0.002139628,0.0010648351,0.00025588062,0.00036906594,0.0004647148,0.6432492,0.003365465,0.06828017,0.09744879,0.17924589],"study_design_scores_gemma":[0.00071456307,0.00019551365,0.0004937129,0.00005570056,0.00008055361,0.00013354367,0.0003332098,0.94320726,0.0009839021,0.048230562,0.0055055073,0.000065925386],"about_ca_topic_score_codex":0.07809363,"about_ca_topic_score_gemma":0.11369433,"teacher_disagreement_score":0.07809363,"about_ca_system_score_codex":0.007102969,"about_ca_system_score_gemma":0.015570918,"threshold_uncertainty_score":0.1552782},"labels":[],"label_agreement":null},{"id":"W2043888881","doi":"10.1109/icma.2012.6283527","title":"New path planning scheme for complete coverage of mapped areas by single and multiple robots","year":2012,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Terrain; Robot; Motion planning; Scheme (mathematics); Path (computing); Computer science; Energy consumption; Energy (signal processing); Mobile robot; Function (biology); Real-time computing; Power consumption; Work (physics); Power (physics); Simulation; Artificial intelligence; Engineering; Electrical engineering; Mathematics; Computer network; Geography","score_opus":0.05646474044229159,"score_gpt":0.2722371969291634,"score_spread":0.21577245648687182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2043888881","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004395,0.000046101395,0.99445504,0.000023489676,0.000012229093,0.000032791166,0.00003314377,0.00028424693,0.00071800756],"genre_scores_gemma":[0.11840023,0.000077511395,0.87853545,0.000022531365,0.000014134341,0.0002391685,0.00014801204,0.000073721254,0.0024892637],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996805,0.00005655098,0.000021175174,0.00006892024,0.00014330537,0.000029445058],"domain_scores_gemma":[0.999684,0.00012089578,0.000033796474,0.00007128533,0.00006552136,0.000024472663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047403073,0.0004543833,0.0004914634,0.0005315834,0.00046765688,0.00040287466,0.0011616517,0.00046383197,0.002317135],"category_scores_gemma":[0.000978214,0.0002820271,0.00037759938,0.0005516149,0.0004635248,0.0008125071,0.0011586805,0.0006652561,0.0003584539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014998748,0.000070584494,0.0003943623,0.00021041895,0.000058824848,0.000122746,0.0003431778,0.50605655,0.03104998,0.0417258,0.004379132,0.41543847],"study_design_scores_gemma":[0.000033519304,0.00008260242,0.00014100422,0.000008593343,0.000011071449,0.000077625096,0.000018015811,0.983809,0.0037631243,0.0062528076,0.0057869316,0.000015669211],"about_ca_topic_score_codex":0.0028047,"about_ca_topic_score_gemma":0.0044693113,"teacher_disagreement_score":0.0028047,"about_ca_system_score_codex":0.00054802146,"about_ca_system_score_gemma":0.00086449215,"threshold_uncertainty_score":0.007751584},"labels":[],"label_agreement":null},{"id":"W2044712489","doi":"10.1016/s0304-3975(01)00303-6","title":"Searching games with errors—fifty years of coping with liars","year":2002,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":211,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Interactivity; Theoretical computer science; Computation; Algorithm; Multimedia","score_opus":0.016146130903592883,"score_gpt":0.24518310904156276,"score_spread":0.2290369781379699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044712489","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34587938,0.11030291,0.23233195,0.15357903,0.0023934303,0.00017790619,0.00015723555,0.00050190865,0.15467629],"genre_scores_gemma":[0.91609615,0.024841834,0.03500925,0.0051967856,0.0012784755,0.00017178225,0.00009622345,0.00013308185,0.017176343],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997265,0.0015944577,0.00012226659,0.00025659346,0.00040482162,0.0003569208],"domain_scores_gemma":[0.98497635,0.010441615,0.001079693,0.001185783,0.0011497218,0.0011668354],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0057937307,0.00073892623,0.00087434775,0.0010660655,0.0017764898,0.0046480717,0.0023917241,0.0035853584,0.003234327],"category_scores_gemma":[0.027244246,0.00043012513,0.00061146816,0.0009897499,0.008140598,0.009659651,0.0033094378,0.0033900284,0.0004574127],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036974854,0.0004352718,0.007635623,0.0004996833,0.00020815045,0.00034861197,0.010615131,0.032416448,0.0006416409,0.70943344,0.022066541,0.21532969],"study_design_scores_gemma":[0.0000884793,0.0002080276,0.0021616903,0.00067342864,0.00006077614,0.00025417464,0.0076408507,0.052968156,0.0005727761,0.82894677,0.10632898,0.000095897754],"about_ca_topic_score_codex":0.002717821,"about_ca_topic_score_gemma":0.0038020771,"teacher_disagreement_score":0.0057937307,"about_ca_system_score_codex":0.0019618967,"about_ca_system_score_gemma":0.0016038181,"threshold_uncertainty_score":0.030640543},"labels":[],"label_agreement":null},{"id":"W2044973122","doi":"10.1016/j.ic.2013.02.001","title":"Worst-case optimal exploration of terrains with obstacles","year":2013,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Terrain; Point (geometry); Artificial intelligence; Convex hull; Computer vision; Computer science; Robot; Mobile robot; Trajectory; Regular polygon; Algorithm; Mathematics; Geography; Geometry; Cartography","score_opus":0.02538619896032181,"score_gpt":0.2494876185426832,"score_spread":0.22410141958236138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2044973122","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28079155,0.0035555707,0.6863426,0.001963725,0.00015669431,0.00008787591,0.000661454,0.00042973465,0.026010854],"genre_scores_gemma":[0.93083346,0.00060042593,0.06355604,0.00011673461,0.00007511952,0.00006453292,0.00035269026,0.00017069289,0.00423032],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849796,0.00059619645,0.00007047743,0.00018400353,0.00030334445,0.00034803865],"domain_scores_gemma":[0.99387395,0.0050124275,0.00029738445,0.0003157485,0.00025063066,0.00024996325],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020037692,0.0010034284,0.0013738864,0.0009867037,0.00091024506,0.0022150192,0.0015335914,0.002225366,0.0028623776],"category_scores_gemma":[0.013387754,0.0009095164,0.0008357104,0.0012933434,0.0017291773,0.0028060835,0.0020935305,0.0011263421,0.00028208678],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036906128,0.000044534507,0.00061107485,0.000103816164,0.000048202535,0.00012062471,0.00005096896,0.9760276,0.00066149264,0.012296771,0.001350603,0.008315207],"study_design_scores_gemma":[0.000017964738,0.000035327146,0.00015518544,0.000012728353,0.000016703858,0.00006215411,0.00003934505,0.97046846,0.00047006874,0.028375937,0.00033888876,0.0000071981617],"about_ca_topic_score_codex":0.0039232783,"about_ca_topic_score_gemma":0.004797625,"teacher_disagreement_score":0.0039232783,"about_ca_system_score_codex":0.0010479685,"about_ca_system_score_gemma":0.0012254588,"threshold_uncertainty_score":0.01059711},"labels":[],"label_agreement":null},{"id":"W2046312856","doi":"10.1109/secon.2010.5508232","title":"Back-Tracking Based Sensor Deployment by a Robot Team","year":2010,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Computer science; Mobile robot; Vertex (graph theory); Grid; Real-time computing; Software deployment; Path (computing); Occupancy grid mapping; Computer vision; Artificial intelligence; Algorithm; Computer network; Mathematics; Theoretical computer science","score_opus":0.01930627975446081,"score_gpt":0.264669835391092,"score_spread":0.2453635556366312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2046312856","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05061096,0.00015006897,0.9467785,0.00011319874,0.000050257462,0.00006345732,0.00002161029,0.00063471164,0.0015773395],"genre_scores_gemma":[0.6520252,0.00015385298,0.344012,0.00010468734,0.00003345992,0.0001921025,0.000102620994,0.000059824168,0.0033162055],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939346,0.00016197484,0.000026602454,0.00013486168,0.00017659468,0.00010656774],"domain_scores_gemma":[0.99911064,0.0002729532,0.00015078796,0.00022191742,0.0001313594,0.00011229894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006603971,0.00072210556,0.0009259793,0.0005085604,0.00061800005,0.0006794802,0.0014600264,0.0007609128,0.0012352713],"category_scores_gemma":[0.0014524811,0.00050872884,0.00054251635,0.0005280255,0.0006641352,0.001101107,0.0015094308,0.00059955503,0.0006058753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004165532,0.00017960173,0.0017503374,0.00012484685,0.000063952,0.00029628072,0.00029812756,0.807882,0.018282825,0.011536809,0.0022612244,0.15690741],"study_design_scores_gemma":[0.000042904972,0.00015689663,0.0001176226,0.000005006577,0.000010539454,0.000058843587,0.000028369735,0.9939792,0.00299318,0.0014800743,0.0011188878,0.000008375248],"about_ca_topic_score_codex":0.0032896616,"about_ca_topic_score_gemma":0.0022371588,"teacher_disagreement_score":0.0032896616,"about_ca_system_score_codex":0.0005897147,"about_ca_system_score_gemma":0.0009646538,"threshold_uncertainty_score":0.0065410137},"labels":[],"label_agreement":null},{"id":"W2049954052","doi":"10.1007/s00224-005-1223-5","title":"Rendezvous and Election of Mobile Agents: Impact of Sense of Direction","year":2005,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Rendezvous; Leader election; Correctness; Computer science; Constructive proof; Node (physics); Context (archaeology); Asynchronous communication; Enhanced Data Rates for GSM Evolution; Topology (electrical circuits); Protocol (science); Theoretical computer science; Computer network; Distributed computing; Algorithm; Mathematics; Discrete mathematics; Combinatorics; Artificial intelligence","score_opus":0.015085414672775604,"score_gpt":0.2905820463513931,"score_spread":0.2754966316786175,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2049954052","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9226852,0.0014674045,0.049881667,0.0017726411,0.0002327059,0.000034055254,0.00011381563,0.00014882954,0.023663558],"genre_scores_gemma":[0.9972926,0.00022781968,0.0014108772,0.000023184039,0.00001881826,0.000006390531,0.000028141005,0.00001888143,0.0009733557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99912757,0.0003362665,0.000026718291,0.00017057173,0.00013471038,0.00020419044],"domain_scores_gemma":[0.9881109,0.00781979,0.0012491449,0.0009775521,0.00084160274,0.0010009431],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016226232,0.00044738498,0.00080933975,0.00084839883,0.0011220094,0.002897526,0.00086627394,0.0011898007,0.0049691955],"category_scores_gemma":[0.027027879,0.00046012097,0.00046860587,0.0008057077,0.0016335844,0.0038219846,0.0017347803,0.0010939544,0.00054887746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042257365,0.00046082502,0.025568457,0.00036366342,0.0003092044,0.00045409007,0.0011066516,0.60176826,0.018326981,0.26325622,0.004661586,0.07949835],"study_design_scores_gemma":[0.0003196949,0.00055170676,0.01003099,0.00003511126,0.00014414424,0.00040539177,0.0015076633,0.82748574,0.0042269416,0.15163837,0.0035869328,0.000067300156],"about_ca_topic_score_codex":0.0033885788,"about_ca_topic_score_gemma":0.0039281202,"teacher_disagreement_score":0.0049691955,"about_ca_system_score_codex":0.0007353461,"about_ca_system_score_gemma":0.0013884943,"threshold_uncertainty_score":0.016623676},"labels":[],"label_agreement":null},{"id":"W2050063944","doi":"10.1016/j.tcs.2005.12.016","title":"Asynchronous deterministic rendezvous in graphs","year":2006,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":162,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; Carleton University","funders":"","keywords":"Rendezvous; Asynchronous communication; Computer science; Graph; Upper and lower bounds; Mathematics; Node (physics); Topology (electrical circuits); Combinatorics; Algorithm; Discrete mathematics","score_opus":0.007596805078787223,"score_gpt":0.24335416124682405,"score_spread":0.23575735616803684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050063944","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41306934,0.0009755725,0.5517805,0.0016395727,0.00020174263,0.00013769924,0.00041766497,0.0012384756,0.030539423],"genre_scores_gemma":[0.95915836,0.00032832328,0.02908006,0.00012169565,0.000056036963,0.00009243631,0.00015875435,0.00019661288,0.010807668],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990409,0.0003107656,0.000042229047,0.00024464677,0.00016700303,0.00019437166],"domain_scores_gemma":[0.9920123,0.0054862727,0.0006036684,0.0008919088,0.00042226366,0.00058351265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010333266,0.0006181714,0.0012198926,0.0011827287,0.0016803528,0.0019091953,0.0019269246,0.0012884886,0.006782087],"category_scores_gemma":[0.008050895,0.00071151473,0.0005908607,0.0012915228,0.0020782899,0.0035127618,0.0023475229,0.0015923324,0.0007692908],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000657915,0.00009299114,0.0008483667,0.00021151296,0.0000518865,0.00026387282,0.0005464999,0.25104704,0.0055519766,0.7132396,0.0040868395,0.023401516],"study_design_scores_gemma":[0.00010109068,0.00004347918,0.00022349652,0.000018876006,0.000030177987,0.00007955058,0.000168951,0.45258635,0.0021925815,0.5420845,0.0024470144,0.000023845061],"about_ca_topic_score_codex":0.0038493648,"about_ca_topic_score_gemma":0.004861058,"teacher_disagreement_score":0.006782087,"about_ca_system_score_codex":0.0013625388,"about_ca_system_score_gemma":0.00086350495,"threshold_uncertainty_score":0.02268833},"labels":[],"label_agreement":null},{"id":"W2050134964","doi":"10.1109/vtcfall.2014.6966166","title":"Rollout Algorithm for Target Search in a Wireless Sensor Network","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Flooding (psychology); Wireless sensor network; Computer network; Node (physics); Heuristic; Mathematical optimization; Real-time computing; Mathematics; Artificial intelligence; Engineering","score_opus":0.018456732994868347,"score_gpt":0.2673638859269356,"score_spread":0.24890715293206725,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050134964","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037456833,0.00045612967,0.9552423,0.00034139343,0.00006423022,0.00014577514,0.00015073166,0.0013437769,0.00479888],"genre_scores_gemma":[0.8802085,0.00021798312,0.11460546,0.00016965134,0.00002554787,0.00029480265,0.00027304882,0.00012394568,0.0040811156],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995059,0.00018038899,0.000022871265,0.000088465786,0.00010830323,0.00009412385],"domain_scores_gemma":[0.9989286,0.0006713265,0.000120865734,0.000079933394,0.00010707171,0.00009224746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012803052,0.0010866693,0.0012848618,0.0008068056,0.00072022213,0.00087807217,0.0014605714,0.00096368603,0.0029636798],"category_scores_gemma":[0.0030064604,0.00040557882,0.00051749585,0.0006376402,0.0010028764,0.0013974127,0.0011748088,0.0011356875,0.00036246065],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018510509,0.00004329108,0.00043046763,0.00004549704,0.000020157715,0.00007239079,0.00007603149,0.9636871,0.00072006823,0.008752639,0.0011908829,0.02477635],"study_design_scores_gemma":[0.000015479753,0.000033432632,0.0000380675,0.000004003318,0.0000035817404,0.000008479972,0.000007812936,0.9969146,0.00016510823,0.0026000587,0.00020645242,0.0000028523461],"about_ca_topic_score_codex":0.008330033,"about_ca_topic_score_gemma":0.0069176513,"teacher_disagreement_score":0.008330033,"about_ca_system_score_codex":0.0012295288,"about_ca_system_score_gemma":0.0016146618,"threshold_uncertainty_score":0.016563118},"labels":[],"label_agreement":null},{"id":"W2051092461","doi":"10.1016/j.tcs.2003.08.001","title":"On-line parallel heuristics, processor scheduling and robot searching under the competitive framework","year":2003,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Heuristics; Computer science; Scheduling (production processes); Point (geometry); Robot; Heuristic; Path (computing); Line (geometry); Motion planning; Mathematical optimization; Mathematics; Artificial intelligence; Upper and lower bounds; Programming language","score_opus":0.0251432603993933,"score_gpt":0.3021206933952823,"score_spread":0.276977432995889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051092461","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047171425,0.0030729033,0.9099028,0.0017141134,0.00024328995,0.00012729726,0.00009742959,0.0003544178,0.037316285],"genre_scores_gemma":[0.7903608,0.0032299191,0.18994154,0.00048280502,0.00058104977,0.00024300888,0.00018289106,0.00034472582,0.014633239],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99731416,0.0014697103,0.000049671642,0.00016957344,0.00061484583,0.00038198318],"domain_scores_gemma":[0.995307,0.003322935,0.00038373758,0.00031912723,0.00044452996,0.00022261191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030647728,0.0011804259,0.0019979912,0.0009498251,0.0012481427,0.0027389666,0.0031290208,0.002616592,0.0053220456],"category_scores_gemma":[0.010327222,0.00072496355,0.0007076926,0.0027158416,0.002111443,0.0034848182,0.001415976,0.0019425082,0.00061159383],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045902425,0.00015928184,0.00031059285,0.00024388453,0.00007497969,0.00007070348,0.00009470298,0.68853164,0.00096804573,0.2664135,0.0053009964,0.03737271],"study_design_scores_gemma":[0.00007584538,0.00009146675,0.000118539494,0.000011970135,0.000016782744,0.000036250138,0.000027801632,0.81722915,0.0002521495,0.18044013,0.0016890999,0.000010799667],"about_ca_topic_score_codex":0.009629213,"about_ca_topic_score_gemma":0.0075085554,"teacher_disagreement_score":0.009629213,"about_ca_system_score_codex":0.002439624,"about_ca_system_score_gemma":0.0033558367,"threshold_uncertainty_score":0.019146323},"labels":[],"label_agreement":null},{"id":"W2052232389","doi":"10.1109/cec.2013.6557978","title":"Binary decision automata modelling stress in the workplace","year":2013,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Automaton; Covert; Representation (politics); Binary decision diagram; Productivity; String (physics); Machine learning; Artificial intelligence; Risk analysis (engineering); Theoretical computer science; Mathematics; Business","score_opus":0.029615587916060955,"score_gpt":0.2654160449431236,"score_spread":0.23580045702706265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2052232389","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21564996,0.00052049797,0.7576561,0.0011574681,0.00025109976,0.0001478086,0.00069554074,0.00050242513,0.023419116],"genre_scores_gemma":[0.9351343,0.0003106682,0.05248337,0.00011840609,0.000047212558,0.00025706808,0.000283082,0.00003964152,0.01132619],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999086,0.00030333214,0.00007512323,0.00022685036,0.00014502341,0.00016356801],"domain_scores_gemma":[0.9966871,0.0021661469,0.00040064374,0.00018388714,0.0003168467,0.00024534905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009851106,0.00086040044,0.00096625893,0.0006196886,0.0005793264,0.0017556229,0.0014647928,0.0014899777,0.0056444583],"category_scores_gemma":[0.0044589466,0.00044557633,0.000886804,0.0005825376,0.0013175035,0.001431717,0.0014411083,0.0015559358,0.00070898805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010433137,0.000079324964,0.0020584497,0.000071069146,0.000034349658,0.00019963871,0.00021618477,0.9202367,0.0011060656,0.06421771,0.0005614025,0.011114823],"study_design_scores_gemma":[0.000015643604,0.00003570579,0.00022580037,0.00000892775,0.000008345173,0.000015881471,0.000034863235,0.97617245,0.00017798021,0.022639178,0.00065469294,0.000010474731],"about_ca_topic_score_codex":0.010075257,"about_ca_topic_score_gemma":0.0060492703,"teacher_disagreement_score":0.010075257,"about_ca_system_score_codex":0.001377957,"about_ca_system_score_gemma":0.0010639613,"threshold_uncertainty_score":0.02003324},"labels":[],"label_agreement":null},{"id":"W2053218689","doi":"10.1016/j.ic.2012.08.004","title":"Connected graph searching","year":2012,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":44,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Agence Nationale de la Recherche","keywords":"Combinatorics; Computer science; Graph; Vertex (graph theory); Conjecture; Theoretical computer science; Connected component; Mathematics; Discrete mathematics","score_opus":0.019700056029231056,"score_gpt":0.2710275313583589,"score_spread":0.2513274753291278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053218689","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030215332,0.0021304227,0.89595884,0.0015093675,0.00034210726,0.0003188191,0.0008186461,0.001632529,0.06707399],"genre_scores_gemma":[0.325173,0.0015136586,0.6265388,0.00077964703,0.0002172262,0.0003967709,0.0022284398,0.0009110205,0.042241473],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991862,0.00022946883,0.000030403377,0.0002791705,0.00021357111,0.00006113426],"domain_scores_gemma":[0.9984988,0.00070322526,0.00009418661,0.00042483342,0.00018463719,0.0000943973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063506624,0.0009125485,0.0013653049,0.0034086558,0.0014099537,0.0020878084,0.0023186412,0.0023192456,0.025620557],"category_scores_gemma":[0.005683406,0.0006036631,0.0012451267,0.003642443,0.0014170544,0.0040961127,0.002615552,0.0015473976,0.00373222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026057663,0.00022224688,0.0009411795,0.0006010411,0.00015083507,0.00018427515,0.0002016555,0.1113419,0.0036747742,0.4982992,0.032476757,0.35164553],"study_design_scores_gemma":[0.000070745264,0.00006539911,0.0003513628,0.00009174145,0.00007318425,0.00018145399,0.00009009778,0.4317009,0.0029346193,0.54353416,0.02088127,0.000025195552],"about_ca_topic_score_codex":0.0024360188,"about_ca_topic_score_gemma":0.003418689,"teacher_disagreement_score":0.025620557,"about_ca_system_score_codex":0.0011830785,"about_ca_system_score_gemma":0.0012996137,"threshold_uncertainty_score":0.085709274},"labels":[],"label_agreement":null},{"id":"W2053680637","doi":"10.1007/s11590-015-0874-7","title":"An information theoretic based integer linear programming approach for the discrete search path planning problem","year":2015,"lang":"en","type":"article","venue":"Optimization Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal; Defence Research and Development Canada","funders":"","keywords":"Mathematical optimization; Computer science; Motion planning; Heuristics; Integer programming; Heuristic; Entropy (arrow of time); Mathematics; Artificial intelligence","score_opus":0.03145900289209521,"score_gpt":0.2827877760298572,"score_spread":0.25132877313776203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053680637","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015684438,0.00023936332,0.9936993,0.00033247715,0.000048961214,0.000030329415,0.000069572525,0.000052036103,0.0039594565],"genre_scores_gemma":[0.3064874,0.0016043585,0.67877233,0.0004666519,0.00037105416,0.000543939,0.0003959343,0.00020992589,0.011148378],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986557,0.000499388,0.00005440501,0.0001851543,0.00049908925,0.00010627186],"domain_scores_gemma":[0.99719125,0.002234171,0.00016203939,0.00010222377,0.00023016916,0.000080151774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020376686,0.0012357474,0.0018452782,0.0017073471,0.0006165169,0.0023392932,0.0024484734,0.0017821853,0.0057256734],"category_scores_gemma":[0.0059846286,0.0010920458,0.0013051791,0.0024204003,0.0015112141,0.0032187812,0.0017261673,0.003343811,0.00065925356],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031445907,0.000054902135,0.00008196973,0.00010667497,0.000027425043,0.000037365236,0.00004139364,0.8450701,0.0003491688,0.13440242,0.0015545002,0.01824254],"study_design_scores_gemma":[0.0000069159373,0.000015763517,0.000018180988,0.000011676395,0.000005972689,0.000008042422,0.000005002218,0.96344525,0.00007646332,0.03588248,0.0005182461,0.000005954013],"about_ca_topic_score_codex":0.0046929233,"about_ca_topic_score_gemma":0.0046820203,"teacher_disagreement_score":0.0057256734,"about_ca_system_score_codex":0.0024723078,"about_ca_system_score_gemma":0.0023658324,"threshold_uncertainty_score":0.01915431},"labels":[],"label_agreement":null},{"id":"W2053806044","doi":"10.1016/s0304-3975(99)00186-3","title":"Scheduling in the dark","year":2000,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":104,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Parallelizable manifold; Computer science; Scheduling (production processes); Multiprocessing; Parallel computing; Multiprocessor scheduling; Partition (number theory); Upper and lower bounds; Distributed computing; Job shop scheduling; Algorithm; Mathematical optimization; Flow shop scheduling; Mathematics; Operating system","score_opus":0.013007104593241791,"score_gpt":0.2663847769236825,"score_spread":0.25337767233044073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053806044","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06504212,0.013286858,0.17582761,0.10997823,0.008519281,0.00013784207,0.0010474912,0.0020824908,0.62407804],"genre_scores_gemma":[0.7453877,0.006523222,0.037070338,0.010352028,0.0031303407,0.00012240131,0.00062293326,0.0013088871,0.1954821],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99877566,0.00040205955,0.000029083518,0.00028260463,0.00022134237,0.00028930858],"domain_scores_gemma":[0.9960194,0.0010205337,0.00022755619,0.0011783262,0.00049548136,0.0010586367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021575275,0.0005005825,0.0008530652,0.00081700267,0.0028715422,0.005543649,0.0015467022,0.0017626683,0.042352144],"category_scores_gemma":[0.008047921,0.00057244947,0.00032630356,0.001704247,0.0034144758,0.007480376,0.0022377912,0.004814642,0.007430482],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035964444,0.00009250343,0.00032727892,0.000113661874,0.000021858072,0.00005526299,0.00036844503,0.0075270245,0.0014559733,0.8687327,0.070153825,0.050791886],"study_design_scores_gemma":[0.000059004262,0.000042639316,0.00022605447,0.000060131588,0.000009144482,0.000037702055,0.0005415659,0.015028075,0.00063924404,0.78599584,0.19733669,0.000023957573],"about_ca_topic_score_codex":0.008506688,"about_ca_topic_score_gemma":0.009450621,"teacher_disagreement_score":0.042352144,"about_ca_system_score_codex":0.0037038778,"about_ca_system_score_gemma":0.005115736,"threshold_uncertainty_score":0.14168203},"labels":[],"label_agreement":null},{"id":"W2055943982","doi":"10.1002/net.10094","title":"Locating information with uncertainty in fully interconnected networks: The case of nondistributed memory","year":2003,"lang":"en","type":"article","venue":"Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Node (physics); Clique; Computer network; Advice (programming); Bounded function; Theoretical computer science; Pointer (user interface); Mathematics; Artificial intelligence","score_opus":0.007708517376898164,"score_gpt":0.21699970336270394,"score_spread":0.20929118598580576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055943982","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55060554,0.0011597356,0.43982944,0.0022412306,0.000044409702,0.00012897346,0.00032416894,0.00040048786,0.005266024],"genre_scores_gemma":[0.9704663,0.00029623538,0.026454734,0.0001125537,0.000041563497,0.00009658579,0.000089652756,0.000038041926,0.0024043766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976852,0.000695714,0.0001344805,0.00060280616,0.00040044094,0.00048127025],"domain_scores_gemma":[0.96985686,0.022801364,0.0027174128,0.0025682107,0.001197447,0.0008587306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003077954,0.0007400629,0.0018526281,0.0013156121,0.0016328216,0.0024704237,0.0037537122,0.002874304,0.0030650117],"category_scores_gemma":[0.025471244,0.0010301886,0.0008049265,0.002089291,0.0033028806,0.007487927,0.0032082666,0.0014858596,0.00031027518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047891654,0.00007021008,0.0019761214,0.00013179478,0.00006840215,0.0004284097,0.0004271666,0.91816694,0.0010044856,0.059316423,0.0008898265,0.017041286],"study_design_scores_gemma":[0.000042621392,0.00004959828,0.0002924556,0.000015381764,0.000024480492,0.00009403917,0.000109436616,0.92997503,0.0006559954,0.06826943,0.0004516513,0.000019846208],"about_ca_topic_score_codex":0.008850705,"about_ca_topic_score_gemma":0.004927009,"teacher_disagreement_score":0.008850705,"about_ca_system_score_codex":0.0020467765,"about_ca_system_score_gemma":0.0010627223,"threshold_uncertainty_score":0.017598331},"labels":[],"label_agreement":null},{"id":"W2055960596","doi":"10.1006/jagm.1999.1068","title":"Distributed Online Frequency Assignment in Cellular Networks","year":2000,"lang":"en","type":"article","venue":"Journal of Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":63,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Carleton University; Dalhousie University","funders":"","keywords":"Frequency assignment; Vertex (graph theory); Competitive analysis; Computer science; Online algorithm; Graph; Lattice (music); Theoretical computer science; Combinatorics; Mathematics; Algorithm; Upper and lower bounds; Telecommunications","score_opus":0.014104128320367778,"score_gpt":0.24859558391952347,"score_spread":0.23449145559915568,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055960596","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12814842,0.000555366,0.8632496,0.00075358857,0.00016626909,0.000087440356,0.00012973264,0.0003780615,0.0065315566],"genre_scores_gemma":[0.94208306,0.0002555984,0.052368484,0.000078198595,0.000102417114,0.000101357226,0.00008405037,0.000036832593,0.004889954],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989287,0.00044424078,0.00004081443,0.0001784494,0.00019242203,0.0002153112],"domain_scores_gemma":[0.995561,0.0031764505,0.00030343392,0.0003991513,0.00037476522,0.00018511998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014331165,0.0005816042,0.0015107688,0.0008194478,0.001104068,0.0015763965,0.0018859548,0.0012426191,0.0033182749],"category_scores_gemma":[0.007267551,0.00049912045,0.00035211467,0.0018460414,0.0010240371,0.0019654068,0.001549939,0.00075892237,0.00036601286],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003919071,0.00015746172,0.0007909665,0.0000659645,0.00003247021,0.00005251911,0.0000778911,0.9031736,0.0010378379,0.02447171,0.002393741,0.06735388],"study_design_scores_gemma":[0.000046600006,0.000031244497,0.00010986238,0.0000030871138,0.00000965621,0.000022213042,0.000026638447,0.97290844,0.0002375192,0.026120268,0.0004801395,0.000004332926],"about_ca_topic_score_codex":0.0054599713,"about_ca_topic_score_gemma":0.0052517173,"teacher_disagreement_score":0.0054599713,"about_ca_system_score_codex":0.0012624941,"about_ca_system_score_gemma":0.0010992634,"threshold_uncertainty_score":0.011100769},"labels":[],"label_agreement":null},{"id":"W2056251021","doi":"10.1057/palgrave.jors.2601926","title":"Maximizing the value of an Earth observation satellite orbit","year":2005,"lang":"en","type":"article","venue":"Journal of the Operational Research Society","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":149,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Satellite; Computer science; Operations research; Earth observation satellite; Orbit (dynamics); Profit (economics); Earth observation; Tabu search; Remote sensing; Geodesy; Aerospace engineering; Geology; Algorithm; Mathematics; Economics; Engineering","score_opus":0.09892549807221367,"score_gpt":0.36858711387949034,"score_spread":0.26966161580727666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056251021","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8442707,0.0011099468,0.12894672,0.0010634526,0.0000689155,0.00014609433,0.00067910796,0.00035683796,0.023358142],"genre_scores_gemma":[0.9741407,0.00018884278,0.022596847,0.000035934332,0.00002023096,0.000032023447,0.00021246263,0.000039214585,0.0027337505],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972826,0.00010713678,0.000010718558,0.000043783148,0.000040446743,0.00006969808],"domain_scores_gemma":[0.9989961,0.00066690263,0.00010327786,0.000053754324,0.000081659935,0.00009827335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006428751,0.0005080008,0.0007009325,0.00075421087,0.00037128525,0.0010034221,0.0006008175,0.0007219025,0.0050015487],"category_scores_gemma":[0.0026199678,0.00020560474,0.0002463949,0.0008489742,0.00035748794,0.0011998238,0.00066172396,0.00031011458,0.0003351804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000935501,0.00023193088,0.0038476714,0.00017876261,0.00008893546,0.00018402266,0.00008861856,0.9135075,0.004846556,0.014439712,0.0056609535,0.05598983],"study_design_scores_gemma":[0.00006711267,0.00017609487,0.0013941508,0.000024722896,0.000036958198,0.00007203833,0.00008519632,0.98362064,0.0028547714,0.010230411,0.0014260312,0.000011805938],"about_ca_topic_score_codex":0.0024025273,"about_ca_topic_score_gemma":0.0016788514,"teacher_disagreement_score":0.0050015487,"about_ca_system_score_codex":0.0006961646,"about_ca_system_score_gemma":0.0006873053,"threshold_uncertainty_score":0.016731858},"labels":[],"label_agreement":null},{"id":"W2057121017","doi":"10.1007/s00446-013-0201-4","title":"Time versus space trade-offs for rendezvous in trees","year":2013,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Rendezvous; Node (physics); Logarithm; Tree (set theory); Constant (computer programming); Computer science; Binary logarithm; Task (project management); Combinatorics; Line (geometry); Mathematics; Discrete mathematics; Algorithm; Physics; Geometry","score_opus":0.02343529895674592,"score_gpt":0.26424040785154046,"score_spread":0.24080510889479453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057121017","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.71963626,0.002947289,0.2552141,0.0015238292,0.00011875457,0.00011715722,0.00034094206,0.0007998146,0.019301772],"genre_scores_gemma":[0.9783417,0.00031794087,0.018583791,0.000042429972,0.000032110212,0.00003708609,0.000060772276,0.00017687875,0.0024073594],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850935,0.0005189377,0.00006538162,0.00018852553,0.00026516576,0.00045262554],"domain_scores_gemma":[0.98075897,0.016017718,0.0005801263,0.0011473265,0.000664905,0.00083093473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028574727,0.00063864095,0.0016684406,0.0012989474,0.001605822,0.0021471474,0.0016015291,0.001587469,0.008881876],"category_scores_gemma":[0.021567909,0.000490721,0.0005616136,0.0016551589,0.0019282722,0.004234365,0.0019461587,0.0012027032,0.0007010217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021074186,0.00021482418,0.0017847817,0.00024840745,0.00007322232,0.00011443683,0.0005799299,0.7993042,0.010066903,0.105314724,0.0034962876,0.076694824],"study_design_scores_gemma":[0.00010741483,0.00026189064,0.0006395272,0.000027528644,0.00005116947,0.000088140485,0.00037953316,0.88094956,0.003448522,0.112934224,0.0010846361,0.000027851842],"about_ca_topic_score_codex":0.002451922,"about_ca_topic_score_gemma":0.003991719,"teacher_disagreement_score":0.008881876,"about_ca_system_score_codex":0.001525065,"about_ca_system_score_gemma":0.0009370204,"threshold_uncertainty_score":0.029712796},"labels":[],"label_agreement":null},{"id":"W2057272165","doi":"10.1007/s00224-014-9555-7","title":"Special Issue on Approximation and Online Algorithms","year":2014,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Algorithm","score_opus":0.019501056301076253,"score_gpt":0.2620512783076757,"score_spread":0.24255022200659945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057272165","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001923089,0.096706025,0.057807446,0.047672153,0.6194295,0.00023122747,0.0018074401,0.00096845266,0.1734546],"genre_scores_gemma":[0.017738365,0.05589989,0.016175905,0.008054255,0.6681786,0.00040059313,0.0025505016,0.0016981174,0.22930382],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9953629,0.0010699739,0.0002856968,0.0011391605,0.0018103078,0.0003318866],"domain_scores_gemma":[0.98635036,0.0072681406,0.00051547465,0.0021149416,0.0023614129,0.0013896673],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003862468,0.00395028,0.0067269993,0.006263153,0.0024214033,0.009782222,0.0036889045,0.004914445,0.12914932],"category_scores_gemma":[0.014895422,0.0013461546,0.0031390244,0.008359568,0.0026269362,0.0087608285,0.003219629,0.008352713,0.041686457],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012593679,0.00016458728,0.00030948478,0.0008188523,0.000105053055,0.00008534321,0.000028293985,0.0018086595,0.00027677583,0.049359772,0.8699975,0.076919734],"study_design_scores_gemma":[0.00008318404,0.00012512639,0.0010314219,0.00064573914,0.00014484825,0.00045034286,0.000051959367,0.0121394005,0.00040407843,0.1323416,0.85252184,0.000060440616],"about_ca_topic_score_codex":0.0012004096,"about_ca_topic_score_gemma":0.0019640995,"teacher_disagreement_score":0.12914932,"about_ca_system_score_codex":0.004592403,"about_ca_system_score_gemma":0.0032868097,"threshold_uncertainty_score":0.4320475},"labels":[],"label_agreement":null},{"id":"W2058122117","doi":"10.1007/s00453-014-9939-8","title":"Convergecast and Broadcast by Power-Aware Mobile Agents","year":2014,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Theory of computation; Atomic broadcast; Approximation algorithm; Distributed computing; Set (abstract data type); Computer network; Distributed algorithm; Mobile agent; Broadcasting (networking); Algorithm","score_opus":0.005753744172305512,"score_gpt":0.22708732742875873,"score_spread":0.22133358325645322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2058122117","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05119004,0.0008800273,0.93406844,0.0009744249,0.00020271403,0.00006768255,0.00007199598,0.00016166858,0.012382936],"genre_scores_gemma":[0.92681855,0.0007725339,0.059665103,0.00014477037,0.00017138082,0.00013178651,0.000072172974,0.00007815803,0.012145537],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993661,0.00024581456,0.000024326313,0.00010673081,0.0001584317,0.000098654906],"domain_scores_gemma":[0.996566,0.0027187387,0.00018842761,0.00018518408,0.00022130537,0.0001203439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014042411,0.00081712106,0.0012523774,0.0007519252,0.0008067345,0.0017303753,0.0013018406,0.0017004042,0.0029940212],"category_scores_gemma":[0.010030389,0.0006439952,0.0006604311,0.0009660711,0.001440377,0.0022062631,0.0017355268,0.00166051,0.0003414485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003219058,0.000054504108,0.00043683048,0.00011073978,0.000046235557,0.00009513084,0.00016980415,0.8351079,0.001615243,0.13559268,0.002297793,0.024151241],"study_design_scores_gemma":[0.000037280086,0.00003412736,0.00006357251,0.000009179572,0.000012148518,0.00002477201,0.000034484692,0.93977225,0.00045107788,0.05879648,0.00075809984,0.000006507888],"about_ca_topic_score_codex":0.002529797,"about_ca_topic_score_gemma":0.0023982648,"teacher_disagreement_score":0.0029940212,"about_ca_system_score_codex":0.0009894571,"about_ca_system_score_gemma":0.0008565391,"threshold_uncertainty_score":0.010016024},"labels":[],"label_agreement":null},{"id":"W2059543065","doi":"10.1145/1542362.1542412","title":"Cache-oblivious range reporting with optimal queries requires superlinear space","year":2009,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Cache; Range (aeronautics); Range query (database); Block (permutation group theory); Upper and lower bounds; Space (punctuation); Block size; Query optimization; Theoretical computer science; Mathematics; Parallel computing; Combinatorics; Sargable; Web search query; Data mining; Information retrieval; Key (lock); Search engine","score_opus":0.027373880164629282,"score_gpt":0.2754844298772666,"score_spread":0.24811054971263735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059543065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15656398,0.004144064,0.8076178,0.005643077,0.00017009297,0.00031987042,0.001517557,0.0070594163,0.01696419],"genre_scores_gemma":[0.7132077,0.0014630533,0.27598736,0.0010060362,0.0003293636,0.00047591748,0.0016412099,0.000703877,0.005185485],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99012417,0.0027011638,0.00063990674,0.001351418,0.0032641143,0.00191941],"domain_scores_gemma":[0.94748247,0.034898154,0.0037748567,0.01143512,0.0016990323,0.0007103197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0061617694,0.0016085836,0.0030577178,0.0011085506,0.0014309209,0.004901748,0.005868542,0.0026769764,0.005838087],"category_scores_gemma":[0.031535078,0.0009275692,0.0017376149,0.004727822,0.0026035183,0.015134779,0.00430184,0.0036278593,0.0016228033],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034310024,0.0010336279,0.0044804686,0.0015120928,0.00037997984,0.00032792284,0.0007141285,0.600128,0.026679209,0.13659772,0.028873818,0.19584204],"study_design_scores_gemma":[0.00022066271,0.0003061799,0.00068970677,0.00006407074,0.00010134732,0.0003075372,0.0002455907,0.88515586,0.012546799,0.09701013,0.0033031073,0.00004896524],"about_ca_topic_score_codex":0.0035348097,"about_ca_topic_score_gemma":0.0033051276,"teacher_disagreement_score":0.0061617694,"about_ca_system_score_codex":0.002730276,"about_ca_system_score_gemma":0.0033260128,"threshold_uncertainty_score":0.032586932},"labels":[],"label_agreement":null},{"id":"W2059952830","doi":"10.1080/10798587.2014.906377","title":"Anniversary Editorial–<i>Intelligent Automation and Soft Computing</i>is Twenty Years Old","year":2014,"lang":"en","type":"article","venue":"Intelligent Automation & Soft Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Library science; Centennial; Medal; Gold medal; China; Management; Computer science; Operations research; Art history; Engineering; Political science; History; Law; Archaeology","score_opus":0.01597650208399992,"score_gpt":0.26313500153064895,"score_spread":0.24715849944664903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059952830","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000111942456,0.007853248,0.000569507,0.020943671,0.90475684,0.00005286284,0.00037666928,0.0006136146,0.06472157],"genre_scores_gemma":[0.0015221257,0.011081972,0.0006118853,0.017459912,0.6273341,0.00005944647,0.00076961477,0.0006723563,0.34048858],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9979139,0.00016810774,0.00017469193,0.000325712,0.0012172008,0.00020039301],"domain_scores_gemma":[0.9873492,0.0014583955,0.00061208656,0.00063094497,0.0074624247,0.0024869826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002203002,0.002008037,0.0018662608,0.0034540552,0.0018843999,0.008356813,0.0020549109,0.0037652475,0.25288892],"category_scores_gemma":[0.009563898,0.00064620917,0.0017313805,0.001637178,0.0009758185,0.0044297613,0.0017890707,0.005164048,0.21437739],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012474799,0.000005447269,0.000013623791,0.00006907861,0.0000028204865,0.000021490767,0.0000034064512,0.000015664373,0.00008303191,0.0002618284,0.9899303,0.009580841],"study_design_scores_gemma":[0.0000034077884,0.000009658259,0.000065474225,0.0000756388,0.0000031369834,0.00005341364,0.000009720039,0.000024696534,0.00005444791,0.00025255702,0.99944323,0.0000044612148],"about_ca_topic_score_codex":0.0012175182,"about_ca_topic_score_gemma":0.0028038332,"teacher_disagreement_score":0.25288892,"about_ca_system_score_codex":0.0016703011,"about_ca_system_score_gemma":0.0015144193,"threshold_uncertainty_score":0.8459977},"labels":[],"label_agreement":null},{"id":"W2061226732","doi":"10.1145/1082473.1082620","title":"An online POMDP algorithm for complex multiagent environments","year":2005,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":93,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Computer science; Formalism (music); Partially observable Markov decision process; Action (physics); Online algorithm; Artificial intelligence; Distributed computing; Theoretical computer science; Algorithm; Machine learning; Markov chain","score_opus":0.08067230983721858,"score_gpt":0.3221294756271801,"score_spread":0.24145716578996151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061226732","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011274938,0.000043959495,0.99705744,0.000053005348,0.000022519089,0.000049987946,0.000028273294,0.00041184016,0.0012055722],"genre_scores_gemma":[0.08126087,0.00009804201,0.91611826,0.0000765695,0.00002301183,0.00032856656,0.00011757861,0.00012360171,0.0018535592],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993741,0.00017066931,0.000035755165,0.00016437494,0.00019373257,0.0000614171],"domain_scores_gemma":[0.9991849,0.0005086976,0.000057458077,0.00010334773,0.000091874324,0.00005384751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011182405,0.00093237037,0.000953892,0.0004912447,0.00068500615,0.000935742,0.0015904829,0.0012131163,0.0067543047],"category_scores_gemma":[0.0023475797,0.00050172536,0.0006921877,0.00039899757,0.0007530402,0.001721899,0.0016994835,0.0016727614,0.0010149896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019204618,0.00024965068,0.0004733317,0.00027018876,0.0000823206,0.0001523059,0.00014921624,0.64726377,0.0036752748,0.093245134,0.0067886338,0.24745813],"study_design_scores_gemma":[0.000060328486,0.00002617499,0.00003468208,0.0000108394115,0.00000945883,0.000026789146,0.000014863185,0.9749623,0.0008537925,0.020559419,0.0034331204,0.000008203347],"about_ca_topic_score_codex":0.003314068,"about_ca_topic_score_gemma":0.0039293445,"teacher_disagreement_score":0.0067543047,"about_ca_system_score_codex":0.0009319041,"about_ca_system_score_gemma":0.0019219494,"threshold_uncertainty_score":0.022595406},"labels":[],"label_agreement":null},{"id":"W2061436084","doi":"10.1016/j.dam.2008.01.027","title":"Constant memory routing in quasi-planar and quasi-polyhedral graphs","year":2008,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University; Carleton University","funders":"","keywords":"Mathematics; Constant (computer programming); Planar graph; Combinatorics; Routing (electronic design automation); Planar; Discrete mathematics; Graph; Computer science","score_opus":0.02407151804749936,"score_gpt":0.249513418155564,"score_spread":0.22544190010806464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061436084","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.52702916,0.0022354047,0.4455533,0.0028072242,0.00021444817,0.00012291831,0.0013263852,0.00082846556,0.01988271],"genre_scores_gemma":[0.8986455,0.0014102065,0.08583054,0.00035872118,0.00009777419,0.00011961518,0.0005374417,0.00022668275,0.012773508],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995592,0.00010260909,0.00002403448,0.000120146855,0.000060070364,0.00013393766],"domain_scores_gemma":[0.9963767,0.00211948,0.0005243837,0.0004473403,0.00026862195,0.00026338565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077154534,0.0006059298,0.00086558633,0.0008555899,0.0011118477,0.0029233221,0.0023904662,0.0012082164,0.009715282],"category_scores_gemma":[0.0055617117,0.00064387795,0.00047104506,0.0018517518,0.0013438156,0.0061241593,0.0013134012,0.0013894096,0.0005622293],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000994289,0.00013418985,0.0015939778,0.00052475504,0.000057587768,0.0002194718,0.0002926709,0.26474553,0.0063991356,0.6600545,0.008474349,0.056509648],"study_design_scores_gemma":[0.00012825168,0.00014312912,0.0007942486,0.00005057958,0.000046966117,0.00021556935,0.00025733386,0.44635245,0.002388183,0.5461171,0.003474257,0.000031898377],"about_ca_topic_score_codex":0.0042327447,"about_ca_topic_score_gemma":0.0056151487,"teacher_disagreement_score":0.009715282,"about_ca_system_score_codex":0.001779189,"about_ca_system_score_gemma":0.001005997,"threshold_uncertainty_score":0.032500863},"labels":[],"label_agreement":null},{"id":"W2061601299","doi":"10.1016/j.dam.2012.08.003","title":"Batching and delivery in semi-online distribution systems","year":2012,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Competitive analysis; Online algorithm; Distribution center; Instant; Distribution (mathematics); Order (exchange); Total cost; Line (geometry); Simple (philosophy); Computer science; Mathematics; Mathematical optimization; Operations research; Business; Upper and lower bounds; Marketing","score_opus":0.021888167250066887,"score_gpt":0.2541182552183995,"score_spread":0.23223008796833258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061601299","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.116400905,0.002055985,0.87174565,0.0019495434,0.0003129403,0.0001992186,0.0006109024,0.00067592587,0.0060488023],"genre_scores_gemma":[0.9350327,0.0013643954,0.042454954,0.00023665473,0.00032672062,0.00017202506,0.00036657683,0.00026700384,0.019778935],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99685776,0.0012500116,0.0002262747,0.0006428841,0.0004726127,0.00055046583],"domain_scores_gemma":[0.98007697,0.015388842,0.0015645005,0.000990803,0.0012077757,0.00077108596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006185373,0.0014521346,0.0041627577,0.0010679781,0.001475579,0.0038148654,0.0042600445,0.0025795053,0.008598133],"category_scores_gemma":[0.021325698,0.0019881413,0.001335577,0.0022902754,0.0024014257,0.0059095896,0.0022647476,0.0026752304,0.0008551393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009994386,0.00021801605,0.0012616306,0.000354794,0.00008185558,0.00031508322,0.00022677133,0.8633496,0.0022331413,0.099979974,0.0040385653,0.0269412],"study_design_scores_gemma":[0.000031524403,0.000066347835,0.00027143006,0.000011783752,0.000020085577,0.00005135022,0.000028910985,0.970324,0.0005346633,0.028174933,0.00046652247,0.0000185735],"about_ca_topic_score_codex":0.010938231,"about_ca_topic_score_gemma":0.005254007,"teacher_disagreement_score":0.010938231,"about_ca_system_score_codex":0.0033179466,"about_ca_system_score_gemma":0.0021841323,"threshold_uncertainty_score":0.032711744},"labels":[],"label_agreement":null},{"id":"W2064766370","doi":"10.1007/pl00008935","title":"Assigning labels in an unknown anonymous network with a leader","year":2001,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Task (project management); Node (physics); A priori and a posteriori; Network topology; Protocol (science); Process (computing); Computer network; Quality (philosophy); Time complexity; Range (aeronautics); Theoretical computer science; Algorithm; Distributed computing","score_opus":0.026435736169659056,"score_gpt":0.27016343630201634,"score_spread":0.24372770013235728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064766370","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22728983,0.00016069037,0.7637348,0.0019220029,0.0001027341,0.00022487994,0.00019829559,0.00045103405,0.0059157326],"genre_scores_gemma":[0.7764744,0.00017260102,0.2105197,0.00021041419,0.00014987915,0.0002264809,0.00017286063,0.00014917628,0.011924557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965035,0.0018289484,0.00012953024,0.00066516374,0.00047025445,0.00040262294],"domain_scores_gemma":[0.98506355,0.010541538,0.0012036421,0.0012611499,0.0009828745,0.0009472986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005534482,0.0006103884,0.0017813,0.0011865462,0.0034572622,0.0035872923,0.0032609259,0.0026420134,0.0023394711],"category_scores_gemma":[0.015421945,0.00071241276,0.0005936733,0.0020393566,0.0024941438,0.0052176327,0.002945661,0.0015642771,0.00050717755],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015961216,0.0006090926,0.003151414,0.00020915765,0.000085509106,0.0004410718,0.0010131624,0.7109883,0.0025880868,0.21117087,0.005447079,0.06270014],"study_design_scores_gemma":[0.00007711949,0.00005819869,0.00015849477,0.0000088916795,0.00002419269,0.000035465237,0.0001501778,0.9010614,0.00093088386,0.096583694,0.00089562964,0.000015846597],"about_ca_topic_score_codex":0.004050685,"about_ca_topic_score_gemma":0.005154645,"teacher_disagreement_score":0.005534482,"about_ca_system_score_codex":0.0021655012,"about_ca_system_score_gemma":0.0018839791,"threshold_uncertainty_score":0.029269516},"labels":[],"label_agreement":null},{"id":"W2064871734","doi":"10.1016/j.tcs.2006.06.017","title":"Deterministic M2M multicast in radio networks","year":2006,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; Carleton University","funders":"","keywords":"Multicast; Computer network; Computer science; Node (physics); Graph; Source-specific multicast; Distributed computing; Topology (electrical circuits); Theoretical computer science; Mathematics; Combinatorics","score_opus":0.007809796145720538,"score_gpt":0.24408707871843138,"score_spread":0.23627728257271086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064871734","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14633948,0.0019461899,0.8360623,0.002743203,0.00020057734,0.00015556383,0.00045443466,0.0005136119,0.011584555],"genre_scores_gemma":[0.91091764,0.0006000276,0.082368545,0.0003354632,0.00020751344,0.00021057014,0.0001617518,0.000106581574,0.005091795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975963,0.0012672294,0.000079604804,0.00031774913,0.00036116602,0.00037793643],"domain_scores_gemma":[0.9861501,0.011156782,0.0009082582,0.00085964444,0.00048405057,0.00044114434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003337578,0.00084704097,0.0020183183,0.0009164298,0.0017808777,0.0017029723,0.002395176,0.0029775556,0.002810776],"category_scores_gemma":[0.01726443,0.0012512036,0.0007747403,0.0015394893,0.0017994497,0.0029585117,0.0027233763,0.0014974581,0.00035876108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005708638,0.000092758,0.00093549764,0.00025044897,0.00005505413,0.00010951255,0.00011979874,0.8675716,0.0010333918,0.10192303,0.005453695,0.021884404],"study_design_scores_gemma":[0.00005412152,0.00004569697,0.00014438572,0.000012755801,0.00001554288,0.00003983473,0.000027245016,0.9366598,0.00027346474,0.061981495,0.000734793,0.0000109177245],"about_ca_topic_score_codex":0.002648243,"about_ca_topic_score_gemma":0.0036627634,"teacher_disagreement_score":0.003337578,"about_ca_system_score_codex":0.0025731202,"about_ca_system_score_gemma":0.001267629,"threshold_uncertainty_score":0.018669367},"labels":[],"label_agreement":null},{"id":"W2065444014","doi":"10.1016/j.tcs.2007.11.016","title":"The Magnus–Derek game","year":2007,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"University of Waterloo","keywords":"Security token; Combinatorial game theory; Mathematical game; Set (abstract data type); Mathematics; Game tree; Computer science; Repeated game; Combinatorics; Game theory; Mathematical economics; Simultaneous game; Computer network","score_opus":0.009851086488203221,"score_gpt":0.26878522570535635,"score_spread":0.25893413921715314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065444014","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17394763,0.0018334314,0.49664658,0.015221774,0.000650588,0.00021203095,0.00041189796,0.00022432915,0.31085175],"genre_scores_gemma":[0.89140135,0.00089378504,0.03414862,0.0008733121,0.00022722945,0.00018253353,0.00012352286,0.000068907764,0.072080694],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99894255,0.00051365985,0.00003818723,0.00012157933,0.00021718157,0.00016676189],"domain_scores_gemma":[0.99823403,0.0011514551,0.000096522104,0.00014057686,0.00012365455,0.00025376817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014868092,0.0007556162,0.0010906165,0.0006536785,0.0011681442,0.0026779682,0.0015071321,0.0023495806,0.010878653],"category_scores_gemma":[0.007857473,0.00033463252,0.000458682,0.00052266975,0.0025504576,0.0043798657,0.0022166977,0.0025151789,0.000899689],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000617323,0.000017080496,0.00009804635,0.000024630204,0.000009535346,0.000040793955,0.000058999765,0.006305681,0.00028589406,0.9839061,0.0027288243,0.006462574],"study_design_scores_gemma":[0.000030053761,0.000020437403,0.000075612596,0.000010988246,0.0000054001594,0.000052809617,0.00003747474,0.049162447,0.00017067732,0.94630045,0.004122359,0.000011337267],"about_ca_topic_score_codex":0.0020889959,"about_ca_topic_score_gemma":0.0016039822,"teacher_disagreement_score":0.010878653,"about_ca_system_score_codex":0.0016189928,"about_ca_system_score_gemma":0.0015223961,"threshold_uncertainty_score":0.03639269},"labels":[],"label_agreement":null},{"id":"W2066234959","doi":"10.1016/j.tcs.2012.11.022","title":"Exploring an unknown dangerous graph using tokens","year":2012,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science; Graph; Theoretical computer science; Combinatorics; Mathematics; Algorithm","score_opus":0.1472886519647449,"score_gpt":0.3144289435516493,"score_spread":0.1671402915869044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066234959","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33285075,0.00026986477,0.65176326,0.0014227352,0.00014357803,0.00015805004,0.0005507815,0.0010710614,0.011769984],"genre_scores_gemma":[0.6962088,0.00019441464,0.2974703,0.00011852828,0.0000316372,0.000084889005,0.0004325792,0.00032286352,0.0051359474],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99968386,0.00009317908,0.000013654721,0.00008570619,0.00006957585,0.00005396634],"domain_scores_gemma":[0.9982216,0.0012219528,0.000114402115,0.00020010374,0.00009708089,0.0001448902],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005563754,0.00059528137,0.00078609097,0.0011501433,0.0012974828,0.0011136169,0.001786147,0.0015352543,0.006043886],"category_scores_gemma":[0.00393998,0.0005496956,0.0012199251,0.0008973804,0.0015873391,0.004110866,0.0024137166,0.0014867818,0.0004732758],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001160055,0.00029033117,0.00672129,0.00057936664,0.00012925481,0.0023036944,0.0008159244,0.5207368,0.012261746,0.35024777,0.0060801585,0.09867351],"study_design_scores_gemma":[0.000039580285,0.00009353276,0.00022509099,0.000036979858,0.000045219396,0.00020447854,0.0002343808,0.78843665,0.0028418587,0.20483905,0.002981583,0.000021528891],"about_ca_topic_score_codex":0.0033183077,"about_ca_topic_score_gemma":0.005712531,"teacher_disagreement_score":0.006043886,"about_ca_system_score_codex":0.00073750556,"about_ca_system_score_gemma":0.0010256598,"threshold_uncertainty_score":0.02021879},"labels":[],"label_agreement":null},{"id":"W2066302983","doi":"10.1109/cig.2007.368093","title":"Using Stochastic AI Techniques to Achieve Unbounded Resolution in Finite Player Goore Games and its Applications","year":2007,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Pruning; Automaton; Domain (mathematical analysis); Learning automata; Implementation; Theoretical computer science; Resolution (logic); Field (mathematics); Artificial intelligence; Mathematical optimization; Mathematics","score_opus":0.04705829363744853,"score_gpt":0.3418484609963348,"score_spread":0.2947901673588863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066302983","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021912634,0.0002814691,0.9720035,0.00048392854,0.000028247227,0.00006760699,0.000022598795,0.00029728326,0.004902689],"genre_scores_gemma":[0.6579251,0.00041948818,0.3349281,0.0005646411,0.00010311873,0.00041219924,0.00012138577,0.00017064705,0.005355329],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99750227,0.0010621377,0.000115079805,0.00035079356,0.0006152287,0.0003544143],"domain_scores_gemma":[0.98570955,0.012283026,0.0006506836,0.00056948763,0.00043356942,0.00035375924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034633626,0.001387273,0.0016949963,0.001035441,0.0010550824,0.001344078,0.0021070172,0.0016974614,0.0021738168],"category_scores_gemma":[0.019275067,0.00069798226,0.0015734065,0.00065299385,0.004118244,0.002701188,0.0037881033,0.0038246126,0.0003667547],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108408625,0.00009026199,0.0007298706,0.00012602453,0.00007530647,0.00017196887,0.00032670295,0.75449675,0.0024690097,0.21949443,0.0007045769,0.021206675],"study_design_scores_gemma":[0.00002123327,0.00003443333,0.000045384946,0.0000120106615,0.000009357874,0.000020426654,0.000016370303,0.9081827,0.0005428674,0.0906038,0.0005027497,0.000008739784],"about_ca_topic_score_codex":0.0037178968,"about_ca_topic_score_gemma":0.0041559953,"teacher_disagreement_score":0.0037178968,"about_ca_system_score_codex":0.0013708279,"about_ca_system_score_gemma":0.0016228178,"threshold_uncertainty_score":0.01831621},"labels":[],"label_agreement":null},{"id":"W2066449891","doi":"10.1007/s00453-008-9208-9","title":"An Improved Algorithm for Online Unit Clustering","year":2008,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Cluster analysis; Theory of computation; Online algorithm; Partition (number theory); Mathematics; Combinatorics; Dimension (graph theory); Upper and lower bounds; Randomized algorithm; Algorithm; Sequence (biology); Unit (ring theory); Approximation algorithm; Computer science; Discrete mathematics; Statistics","score_opus":0.041953442326293944,"score_gpt":0.2997598735524124,"score_spread":0.25780643122611846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2066449891","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0056275795,0.00021415003,0.9895076,0.00016331108,0.0001633843,0.00012370554,0.00014651487,0.0016631769,0.0023905912],"genre_scores_gemma":[0.052433565,0.00011846697,0.94015074,0.00014994592,0.000107277876,0.00028667218,0.000473399,0.00035116286,0.0059287855],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980096,0.00048270548,0.00012182611,0.00047386732,0.0006624041,0.00024960696],"domain_scores_gemma":[0.99727005,0.0008524413,0.0001443742,0.0008202172,0.0007237156,0.0001891744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017467221,0.0014260522,0.0027665657,0.0022175193,0.0017710289,0.0021002258,0.0051246407,0.0028923564,0.012941349],"category_scores_gemma":[0.0071146544,0.0009013432,0.0014739844,0.0042799762,0.001016169,0.0033453226,0.003858876,0.0025103455,0.0049400846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000722962,0.0003846549,0.0007723488,0.00025572837,0.00012875223,0.00010287309,0.00018885202,0.2449895,0.005685458,0.042136073,0.023739545,0.68089324],"study_design_scores_gemma":[0.00009112934,0.000056399076,0.00018210673,0.000011834501,0.000027842354,0.00007438356,0.000027852604,0.9760971,0.0019864454,0.017130805,0.0042928713,0.000021175672],"about_ca_topic_score_codex":0.007803629,"about_ca_topic_score_gemma":0.011125102,"teacher_disagreement_score":0.012941349,"about_ca_system_score_codex":0.0020400973,"about_ca_system_score_gemma":0.0033031711,"threshold_uncertainty_score":0.043293178},"labels":[],"label_agreement":null},{"id":"W2067257332","doi":"10.1080/15326340701470937","title":"Optimal Shopping When the Sales Are on—a Markovian Full-Information Best-Choice Problem","year":2007,"lang":"en","type":"article","venue":"Stochastic Models","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Optimal stopping; Context (archaeology); Infinity; Markov process; Function (biology); Stopping time; Markov chain; Poisson distribution; Mathematical optimization; Value (mathematics); Applied mathematics; Statistics; Mathematical analysis","score_opus":0.03384811400664647,"score_gpt":0.26438307362821,"score_spread":0.23053495962156353,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067257332","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39855114,0.0023735308,0.5636351,0.007148131,0.00019959015,0.00025658187,0.00074959436,0.0002951009,0.026791282],"genre_scores_gemma":[0.9230249,0.0009871282,0.060525134,0.00035599264,0.00013841646,0.0002224777,0.00037924614,0.00012163609,0.014245139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978988,0.0010127634,0.00009965224,0.00038079414,0.00021320707,0.00039473808],"domain_scores_gemma":[0.9892887,0.008385073,0.0007636016,0.0002481359,0.00040693447,0.00090757717],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004445331,0.0012567707,0.0033717523,0.0013895128,0.0010539562,0.0029347886,0.0021069301,0.004135851,0.0063435338],"category_scores_gemma":[0.015128235,0.0016783207,0.001693072,0.0012598615,0.0033166916,0.0047283713,0.0018109919,0.0027336823,0.00055531954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006361186,0.0003038308,0.0024033748,0.00030856335,0.00020523372,0.00066372525,0.00035475398,0.6188855,0.001197197,0.3571496,0.0028395692,0.015052489],"study_design_scores_gemma":[0.000110637484,0.00010198206,0.0004278792,0.000039276216,0.000035722544,0.00008291652,0.00009016372,0.7995175,0.00028408936,0.19838092,0.0008836374,0.000045283323],"about_ca_topic_score_codex":0.00749083,"about_ca_topic_score_gemma":0.0036499712,"teacher_disagreement_score":0.00749083,"about_ca_system_score_codex":0.0029603227,"about_ca_system_score_gemma":0.0024933752,"threshold_uncertainty_score":0.023509443},"labels":[],"label_agreement":null},{"id":"W2067326981","doi":"10.5555/545381.545481","title":"Incremental) priority algorithms","year":2002,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Greedy algorithm; Computer science; Simplicity; Greedy randomized adaptive search procedure; Mathematical optimization; Algorithm; Scheduling (production processes); Limit (mathematics); Approximation algorithm; Theoretical computer science; Mathematics","score_opus":0.024356093509823745,"score_gpt":0.26322250264118136,"score_spread":0.23886640913135762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067326981","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0128082195,0.0009446715,0.9618294,0.0009800198,0.0003811589,0.00019890544,0.00022105737,0.0013407584,0.021295844],"genre_scores_gemma":[0.35207504,0.0014843153,0.6262023,0.0011350443,0.0006373653,0.0004487362,0.00074565917,0.00047957784,0.016791891],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974027,0.00065665797,0.00013479445,0.00054116815,0.00073978753,0.00052477256],"domain_scores_gemma":[0.9945878,0.0027220738,0.00040901842,0.0012292573,0.00065072713,0.00040111094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003341125,0.0011321651,0.0010989294,0.001013137,0.0010285248,0.0028414042,0.0044359756,0.0016543957,0.0111122],"category_scores_gemma":[0.015973095,0.00054163847,0.0009949531,0.001633093,0.0009509447,0.0053337505,0.0025877133,0.0025182397,0.0035823835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006270834,0.0004860408,0.0020315903,0.0005485067,0.00011999565,0.0001545201,0.0003082831,0.11886966,0.003737807,0.47518063,0.03220524,0.3657307],"study_design_scores_gemma":[0.00017627781,0.00029251215,0.0003690152,0.000058560312,0.00008468612,0.00029955298,0.00011702098,0.49363083,0.0029559927,0.47690636,0.025076326,0.000033013544],"about_ca_topic_score_codex":0.0017529816,"about_ca_topic_score_gemma":0.0026096127,"teacher_disagreement_score":0.0111122,"about_ca_system_score_codex":0.0015127958,"about_ca_system_score_gemma":0.0021397471,"threshold_uncertainty_score":0.037174046},"labels":[],"label_agreement":null},{"id":"W2068825173","doi":"10.1016/j.tcs.2010.12.065","title":"Fast edge searching and fast searching on graphs","year":2011,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Search problem; Mathematics; Combinatorics; Graph; Enhanced Data Rates for GSM Evolution; Search algorithm; Discrete mathematics; Computer science; Algorithm; Artificial intelligence","score_opus":0.027501399335166436,"score_gpt":0.2653047214923998,"score_spread":0.23780332215723338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068825173","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.062495932,0.003948228,0.9192044,0.0012934407,0.0002560507,0.000121742836,0.00042951878,0.0009829112,0.011267709],"genre_scores_gemma":[0.30928215,0.0029748748,0.6696381,0.0005310697,0.00027601988,0.00031935022,0.00095120794,0.0006243689,0.01540293],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99861586,0.0005376798,0.00006705616,0.00025331456,0.00035794076,0.00016816314],"domain_scores_gemma":[0.98938876,0.00817019,0.00042179102,0.0011506836,0.0006091306,0.0002594341],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019341193,0.0011161817,0.0018251975,0.0025626987,0.0011560704,0.001988129,0.0024163509,0.0023230345,0.008198333],"category_scores_gemma":[0.016192606,0.000966373,0.0011671243,0.004263592,0.001784942,0.007873406,0.0025575515,0.0031084511,0.0009777122],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012047103,0.00018550563,0.0012011094,0.0009949929,0.00012439166,0.0001534077,0.00036888896,0.31725746,0.0054081245,0.41490537,0.019601002,0.23859508],"study_design_scores_gemma":[0.0001347749,0.00009673815,0.00031602426,0.000058190013,0.000046576963,0.00012277858,0.000063855674,0.49259454,0.0018963789,0.499658,0.0049848235,0.000027388889],"about_ca_topic_score_codex":0.0024113676,"about_ca_topic_score_gemma":0.0022838505,"teacher_disagreement_score":0.008198333,"about_ca_system_score_codex":0.001038449,"about_ca_system_score_gemma":0.0010353792,"threshold_uncertainty_score":0.027426124},"labels":[],"label_agreement":null},{"id":"W2068905681","doi":"10.1145/1139113.1139123","title":"Online pricing for web service providers","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Service provider; Online algorithm; Web service; Service (business); Overtime; Variation (astronomy); World Wide Web; Algorithm; Business","score_opus":0.023813752150149147,"score_gpt":0.2679550919869116,"score_spread":0.24414133983676245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2068905681","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048891854,0.000634464,0.9397654,0.0022423752,0.00018587559,0.00019103808,0.00018631999,0.00059435,0.007308367],"genre_scores_gemma":[0.85319257,0.000613548,0.13683414,0.0003477209,0.0003177134,0.00023328354,0.00028029046,0.00016981078,0.0080109425],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968251,0.0014900758,0.00011975276,0.0005072368,0.0005613914,0.0004964122],"domain_scores_gemma":[0.9914991,0.0062265177,0.00055303425,0.0007813889,0.0005020495,0.00043781416],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037855837,0.0011108577,0.0020552492,0.0006658022,0.0012195186,0.002616236,0.0032557826,0.0031229462,0.0077741556],"category_scores_gemma":[0.017978882,0.001178658,0.000834163,0.001922114,0.0014517668,0.008249242,0.0018561056,0.0030055316,0.0007699692],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041487487,0.00044294528,0.0017712103,0.00020120345,0.000058427973,0.00021807833,0.0001837525,0.7123334,0.0015469919,0.17100357,0.008315663,0.10350992],"study_design_scores_gemma":[0.000023790877,0.000026054418,0.00012808287,0.000005636351,0.00000666533,0.000033588578,0.000029196712,0.9293514,0.0002844981,0.06927946,0.00082212174,0.000009494952],"about_ca_topic_score_codex":0.004442414,"about_ca_topic_score_gemma":0.0031309933,"teacher_disagreement_score":0.0077741556,"about_ca_system_score_codex":0.002688787,"about_ca_system_score_gemma":0.001971206,"threshold_uncertainty_score":0.026007116},"labels":[],"label_agreement":null},{"id":"W2069552341","doi":"10.1016/j.cviu.2009.06.010","title":"Visual search for an object in a 3D environment using a mobile robot","year":2010,"lang":"en","type":"article","venue":"Computer Vision and Image Understanding","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":98,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Artificial intelligence; Object (grammar); Limit (mathematics); Mobile robot; Robot; Computer vision; Visual search; Space (punctuation); Optimization problem; Mechanism (biology); Mathematics; Algorithm","score_opus":0.06650966170180576,"score_gpt":0.3477666385531639,"score_spread":0.28125697685135814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069552341","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16787417,0.00037225598,0.8280104,0.00026348888,0.000039413855,0.00006979377,0.000048602455,0.00069935265,0.0026225836],"genre_scores_gemma":[0.75357896,0.00021462099,0.24416962,0.000069420945,0.000025335374,0.000067348774,0.00004895855,0.000065466316,0.0017602588],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987745,0.000016461237,0.0000052425553,0.0000470434,0.000038893526,0.000014879122],"domain_scores_gemma":[0.9998491,0.000059231512,0.000027443897,0.000018918714,0.00002046682,0.00002477709],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023192933,0.00062426523,0.00076343666,0.00068052934,0.000647124,0.0008212094,0.0007678516,0.0015218578,0.0014553415],"category_scores_gemma":[0.000810246,0.0005929549,0.0007706386,0.0006811357,0.00066602783,0.0011295967,0.0012768023,0.000495124,0.000256738],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009558316,0.0001951298,0.0036079728,0.00025594007,0.00022003967,0.0012003904,0.0007085077,0.5305512,0.13239303,0.013832368,0.0022285723,0.31385097],"study_design_scores_gemma":[0.000038650785,0.00014601016,0.0007338244,0.0000123454065,0.00003374462,0.00022300825,0.00008213879,0.98703057,0.0059738983,0.00478609,0.00092120137,0.000018629526],"about_ca_topic_score_codex":0.0057892003,"about_ca_topic_score_gemma":0.0054332986,"teacher_disagreement_score":0.0057892003,"about_ca_system_score_codex":0.00043026192,"about_ca_system_score_gemma":0.00053730124,"threshold_uncertainty_score":0.011510968},"labels":[],"label_agreement":null},{"id":"W2070382302","doi":"10.1109/ccece.2014.6900990","title":"Cellular automata and Mobile Wireless Sensor Networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Wireless sensor network; Computer science; Automaton; Cellular automaton; Learning automata; Key distribution in wireless sensor networks; Set (abstract data type); Point (geometry); Wireless; Wireless network; Computer network; Real-time computing; Algorithm; Theoretical computer science; Mathematics; Telecommunications","score_opus":0.00754208984604546,"score_gpt":0.21569169498196583,"score_spread":0.20814960513592037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070382302","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08716779,0.009491179,0.87476635,0.0028105227,0.0005884061,0.00007406386,0.00029685473,0.00041788758,0.024386939],"genre_scores_gemma":[0.90119123,0.0049783783,0.08372688,0.00031059422,0.0002580546,0.00016350068,0.0002451664,0.000046338624,0.009079851],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996897,0.00012516383,0.00001726066,0.000064398475,0.0000638509,0.000039606435],"domain_scores_gemma":[0.9989505,0.00070399506,0.0001128992,0.000066020664,0.000111701,0.00005490636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029552882,0.0005615802,0.0004997708,0.00051994773,0.00044197173,0.0010058715,0.0006837372,0.0011377112,0.0017693242],"category_scores_gemma":[0.0023209378,0.00021622119,0.0004767083,0.00089510804,0.0012313824,0.00097116246,0.00053202466,0.0008274923,0.0002887925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004113716,0.000022557408,0.0011454948,0.00012107036,0.00004457334,0.00015441279,0.00014218119,0.5765838,0.0015247314,0.39843187,0.0019037074,0.019884469],"study_design_scores_gemma":[0.000014361522,0.00003700603,0.000252557,0.000023958353,0.000014408013,0.00006563891,0.00005183653,0.7331719,0.00038594299,0.2578076,0.008160408,0.000014375814],"about_ca_topic_score_codex":0.0049007735,"about_ca_topic_score_gemma":0.0030545332,"teacher_disagreement_score":0.0049007735,"about_ca_system_score_codex":0.00093051733,"about_ca_system_score_gemma":0.00047749278,"threshold_uncertainty_score":0.009744525},"labels":[],"label_agreement":null},{"id":"W2070441373","doi":"10.1109/tsmcb.2013.2238230","title":"Modeling the “Learning Process” of the Teacher in a Tutorial-Like System Using Learning Automata","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Cybernetics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Component (thermodynamics); Computer science; Process (computing); Field (mathematics); Domain (mathematical analysis); Task (project management); Software; Tutorial system; Automaton; Human–computer interaction; Artificial intelligence; Mathematics education; Software engineering; Programming language; Psychology","score_opus":0.02394945484910472,"score_gpt":0.26045155844835355,"score_spread":0.23650210359924884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070441373","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.089577466,0.00018581256,0.89729285,0.00041421875,0.000054015218,0.00014148513,0.00014767355,0.0008032751,0.011383116],"genre_scores_gemma":[0.89265144,0.00032146648,0.09818875,0.00007807949,0.000037675305,0.00038096623,0.00014588644,0.00007565104,0.008119958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995981,0.00015687564,0.000026722768,0.00009960798,0.00006404177,0.000054719876],"domain_scores_gemma":[0.9987871,0.00072598876,0.0001249862,0.00012410773,0.00015805221,0.000079794736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058048137,0.0006215029,0.00040822523,0.00036419474,0.00051627547,0.0015882205,0.0013566097,0.001694467,0.004452478],"category_scores_gemma":[0.0026629812,0.00033554345,0.0005881994,0.00020760104,0.001063483,0.0018327292,0.0010268937,0.0011375205,0.0007304898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011273393,0.00014057661,0.0027239174,0.0001213736,0.00003238971,0.00025267547,0.00062744896,0.90295166,0.0075791003,0.07210267,0.00051994034,0.0128355045],"study_design_scores_gemma":[0.00001072586,0.00004566764,0.00016573111,0.000008999896,0.000010424064,0.000023212331,0.00002564509,0.9910416,0.0009680456,0.0067328955,0.00095868565,0.000008366933],"about_ca_topic_score_codex":0.0054859356,"about_ca_topic_score_gemma":0.004408307,"teacher_disagreement_score":0.0054859356,"about_ca_system_score_codex":0.00095285417,"about_ca_system_score_gemma":0.00112555,"threshold_uncertainty_score":0.014894962},"labels":[],"label_agreement":null},{"id":"W2070526994","doi":"10.1016/j.tcs.2008.02.035","title":"Time constrained graph searching","year":2008,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vertex (graph theory); Visibility; Computer science; Graph; Combinatorics; Theoretical computer science; Mathematics; Geography","score_opus":0.015721146206224182,"score_gpt":0.2531572785783627,"score_spread":0.2374361323721385,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070526994","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03732021,0.0017285076,0.874756,0.002894863,0.0004322349,0.0002585767,0.0010181064,0.0015714942,0.0800201],"genre_scores_gemma":[0.44335914,0.0010001839,0.49502218,0.00089564244,0.00027159022,0.00040010636,0.0018989053,0.0011807033,0.055971585],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987903,0.0003903953,0.00004151595,0.00032101863,0.0002963941,0.00016037397],"domain_scores_gemma":[0.9965354,0.0023350494,0.00017726338,0.0005480022,0.0002212091,0.00018309818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009357677,0.0010505094,0.0016388451,0.0012334484,0.0009525846,0.0020214624,0.002457134,0.0019988033,0.035436947],"category_scores_gemma":[0.0075065233,0.00067239674,0.0009778333,0.0027696313,0.0011798509,0.0040445165,0.0019140133,0.0026028014,0.002663911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009539232,0.00041475377,0.0006967234,0.000626716,0.00012803679,0.00019791872,0.00023496841,0.3616204,0.0041006664,0.3053722,0.057110332,0.26854333],"study_design_scores_gemma":[0.00013126484,0.00008708313,0.0002946569,0.000035948593,0.000043918968,0.000113390044,0.00006147285,0.7722383,0.0017821363,0.21399389,0.011201063,0.000016848766],"about_ca_topic_score_codex":0.0051128343,"about_ca_topic_score_gemma":0.007527255,"teacher_disagreement_score":0.035436947,"about_ca_system_score_codex":0.0016229484,"about_ca_system_score_gemma":0.0018484294,"threshold_uncertainty_score":0.11854845},"labels":[],"label_agreement":null},{"id":"W2071941627","doi":"10.1002/1097-0037(200009)36:2<96::aid-net4>3.0.co;2-n","title":"Impact of topographic information on graph exploration efficiency","year":2000,"lang":"en","type":"article","venue":"Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Traverse; Graph; A priori and a posteriori; Computer science; Biconnected graph; Theoretical computer science; Strength of a graph; Knowledge graph; Combinatorics; Algorithm; Line graph; Artificial intelligence; Mathematics; Voltage graph; Geography","score_opus":0.013144953852214782,"score_gpt":0.2557916865583918,"score_spread":0.242646732706177,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2071941627","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.93753356,0.001329889,0.05128863,0.0008137019,0.000029334962,0.00003723564,0.00030048913,0.0005589351,0.008108283],"genre_scores_gemma":[0.9924827,0.00029835774,0.0064210985,0.00003280278,0.000011021652,0.000017511042,0.00016207836,0.00007129798,0.00050312234],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99794024,0.0008388593,0.000110905654,0.00031056182,0.00043053244,0.00036891806],"domain_scores_gemma":[0.9661954,0.028693587,0.0011375662,0.0025993648,0.0009148821,0.00045926822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023473576,0.0005815208,0.0010502982,0.00092720566,0.00073906785,0.0016921987,0.000863737,0.0012767798,0.00216766],"category_scores_gemma":[0.042695034,0.00043902418,0.0004125558,0.0014800542,0.0011706265,0.005285787,0.0016350743,0.0007842675,0.0004648418],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006905005,0.00017262691,0.008295046,0.00014316954,0.000089844245,0.00022155717,0.00014961488,0.9140038,0.0041940627,0.003430753,0.00082559686,0.06778334],"study_design_scores_gemma":[0.00006873405,0.00049699156,0.0071818354,0.000042282103,0.00011769764,0.00048054193,0.0002642019,0.96779364,0.010939817,0.011657046,0.0009151392,0.000042061067],"about_ca_topic_score_codex":0.002289211,"about_ca_topic_score_gemma":0.002637015,"teacher_disagreement_score":0.0023473576,"about_ca_system_score_codex":0.0007390555,"about_ca_system_score_gemma":0.0010577857,"threshold_uncertainty_score":0.012414217},"labels":[],"label_agreement":null},{"id":"W2072269078","doi":"10.1007/s00453-009-9361-9","title":"Trade-offs Between the Size of Advice and Broadcasting Time in Trees","year":2009,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Broadcasting (networking); Advice (programming); Competitive analysis; Computer science; Tree (set theory); Node (physics); Theory of computation; Dissemination; Oracle; Network topology; Computer network; Theoretical computer science; Distributed computing; Upper and lower bounds; Mathematics; Algorithm; Telecommunications; Combinatorics","score_opus":0.012749794725829575,"score_gpt":0.24902462796678823,"score_spread":0.23627483324095866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072269078","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7577163,0.0042508948,0.20453222,0.010916119,0.00032766085,0.00022417675,0.0009207169,0.0032404074,0.017871454],"genre_scores_gemma":[0.92575926,0.0010097644,0.06756003,0.0005230172,0.0003397708,0.00014492423,0.00031540336,0.0009154887,0.003432359],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9935796,0.00280318,0.00047135647,0.0008504389,0.001112309,0.0011830715],"domain_scores_gemma":[0.72379863,0.255785,0.0052043144,0.007801864,0.0033178735,0.004092384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009573509,0.0011822128,0.0025081555,0.0016993952,0.0014474487,0.0033999684,0.0036238765,0.004191154,0.00823271],"category_scores_gemma":[0.098550424,0.0016999299,0.0009360237,0.0021609694,0.0026973458,0.011219681,0.0022347185,0.0030828023,0.0010280306],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0069222953,0.0014583571,0.012045057,0.0012412465,0.00028139522,0.00034094445,0.0014709315,0.61028725,0.044490118,0.0692685,0.014178177,0.23801579],"study_design_scores_gemma":[0.00077940774,0.0008280287,0.0026728993,0.00009139863,0.000318531,0.0004000608,0.0003927536,0.87848365,0.010801369,0.103685014,0.001471562,0.00007533139],"about_ca_topic_score_codex":0.0021061993,"about_ca_topic_score_gemma":0.0064436686,"teacher_disagreement_score":0.009573509,"about_ca_system_score_codex":0.0022751486,"about_ca_system_score_gemma":0.0032080102,"threshold_uncertainty_score":0.050630152},"labels":[],"label_agreement":null},{"id":"W2072577896","doi":"10.1145/1383369.1383379","title":"The relative worst order ratio applied to seat reservation","year":2008,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Reservation; Order (exchange); Competitive analysis; Computer science; Online algorithm; Measure (data warehouse); Quality (philosophy); Mathematical optimization; Algorithm; Mathematics; Upper and lower bounds; Data mining; Computer network","score_opus":0.04390905179000232,"score_gpt":0.27495948158162753,"score_spread":0.2310504297916252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072577896","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008627886,0.005036048,0.97443026,0.0005756885,0.0005494916,0.00011051674,0.00013772957,0.00075749535,0.009774933],"genre_scores_gemma":[0.4564494,0.0076106405,0.5238345,0.0008489979,0.0018298908,0.00037715753,0.00047415364,0.001178345,0.0073969043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98647505,0.0066724457,0.0006709545,0.001874556,0.003476754,0.0008301506],"domain_scores_gemma":[0.96921647,0.022977522,0.001733518,0.003575286,0.0019171187,0.0005800907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009631382,0.0031500254,0.0035640667,0.0030579779,0.001484109,0.0046609906,0.0038170207,0.002337729,0.0056734816],"category_scores_gemma":[0.053350564,0.0011197446,0.0022345027,0.006406904,0.004222762,0.008361399,0.00304738,0.006072049,0.0026360631],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007577537,0.00022841158,0.001622605,0.0004994842,0.00019966492,0.0002155311,0.00031087917,0.5357772,0.0029452248,0.2933456,0.008039616,0.15605798],"study_design_scores_gemma":[0.00007987586,0.0003718193,0.0005386582,0.000080267375,0.00008627016,0.0003427909,0.000088238885,0.7226604,0.0033178127,0.26197484,0.010386058,0.00007311676],"about_ca_topic_score_codex":0.004845267,"about_ca_topic_score_gemma":0.0017744572,"teacher_disagreement_score":0.009631382,"about_ca_system_score_codex":0.0028032346,"about_ca_system_score_gemma":0.0027727187,"threshold_uncertainty_score":0.050936222},"labels":[],"label_agreement":null},{"id":"W2073076713","doi":"10.1016/j.tcs.2008.03.006","title":"Self-deployment of mobile sensors on a ring","year":2008,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":88,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Software deployment; Ring (chemistry); Computer science; Visibility; Mathematical proof; Simple (philosophy); Impossibility; RADIUS; Coordinate system; Cover (algebra); Distributed computing; Topology (electrical circuits); Mathematics; Geometry; Physics; Computer network; Combinatorics; Artificial intelligence; Engineering","score_opus":0.015550064127749272,"score_gpt":0.2578851609787024,"score_spread":0.2423350968509531,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073076713","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38021198,0.0006227565,0.612715,0.00056316226,0.00014209087,0.000069766604,0.00010772265,0.00037354755,0.005193933],"genre_scores_gemma":[0.9645006,0.00024512218,0.030917902,0.000046449673,0.0000398154,0.000040295952,0.00004578793,0.000024530495,0.0041395486],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928623,0.00022505087,0.000029908531,0.00020560116,0.0001115352,0.00014170409],"domain_scores_gemma":[0.99767727,0.00092966814,0.0004349209,0.0004391877,0.000257878,0.00026113738],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010320427,0.00046615102,0.00093570043,0.0005074694,0.0006771868,0.00096761546,0.0014641588,0.0011041068,0.0012027662],"category_scores_gemma":[0.0044552903,0.0006575349,0.00041983736,0.0005643747,0.0008527141,0.0021851354,0.0021111679,0.00058503007,0.0004727812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009836461,0.00021550279,0.006262548,0.00018247095,0.00012538343,0.000674492,0.000282443,0.85817456,0.042365044,0.038018446,0.0022162981,0.050499126],"study_design_scores_gemma":[0.000021162643,0.00023395118,0.00070866174,0.0000071284385,0.000020867676,0.00013272242,0.000094901116,0.98716205,0.005318219,0.0053871823,0.0008992897,0.000013863098],"about_ca_topic_score_codex":0.00071157474,"about_ca_topic_score_gemma":0.00067145925,"teacher_disagreement_score":0.0014641588,"about_ca_system_score_codex":0.0004389583,"about_ca_system_score_gemma":0.0003523019,"threshold_uncertainty_score":0.0054579973},"labels":[],"label_agreement":null},{"id":"W2073089651","doi":"10.1111/j.1475-3995.2006.00558.x","title":"On‐orbit servicing: a time‐dependent, moving‐target traveling salesman problem","year":2006,"lang":"en","type":"article","venue":"International Transactions in Operational Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Université du Québec à Montréal","funders":"","keywords":"Spacecraft; Spare part; Travelling salesman problem; Consumables; Computer science; Orbit (dynamics); Real-time computing; Aerospace engineering; Simulation; Operations management; Algorithm; Engineering; Business","score_opus":0.041835978915175695,"score_gpt":0.347755440408976,"score_spread":0.3059194614938003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2073089651","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25282016,0.0019333469,0.710435,0.0035018953,0.00034050742,0.00057366566,0.0013181305,0.00050942705,0.028567843],"genre_scores_gemma":[0.8440647,0.0013527331,0.13472629,0.00045304192,0.0002321991,0.00038999083,0.0012730066,0.00025935448,0.017248612],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989987,0.00041902583,0.000036286827,0.00021468858,0.000112690796,0.00021855473],"domain_scores_gemma":[0.99829286,0.0011451623,0.00016870377,0.000056966932,0.000116892246,0.00021940049],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014579,0.0019174205,0.0025858644,0.0008178657,0.00089814,0.002351184,0.0025853552,0.0037849145,0.007909776],"category_scores_gemma":[0.0027066525,0.0011222343,0.0012273578,0.0016162351,0.0011497473,0.0026834705,0.0011982152,0.0018077606,0.0007533866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017409668,0.00019947857,0.00048585085,0.00018421694,0.00008791119,0.0002823331,0.00008496479,0.9587167,0.00053869333,0.02328985,0.0051973644,0.010758559],"study_design_scores_gemma":[0.000048573565,0.000056664798,0.000121080004,0.000011106449,0.000018559493,0.00003542646,0.00005529623,0.98802096,0.00013682974,0.010760467,0.00072694576,0.000008088356],"about_ca_topic_score_codex":0.014352645,"about_ca_topic_score_gemma":0.0072681187,"teacher_disagreement_score":0.014352645,"about_ca_system_score_codex":0.002054904,"about_ca_system_score_gemma":0.002061458,"threshold_uncertainty_score":0.028538227},"labels":[],"label_agreement":null},{"id":"W2074771880","doi":"10.1016/j.tcs.2008.08.025","title":"Monotonicity in digraph search problems","year":2008,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Digraph; Monotonic function; Mathematics; Combinatorics; Computer science; Discrete mathematics","score_opus":0.023210485426576315,"score_gpt":0.2634368297401455,"score_spread":0.24022634431356918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074771880","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14607401,0.012829555,0.734122,0.009637398,0.00039286056,0.00025022594,0.0007318182,0.0004503668,0.095511794],"genre_scores_gemma":[0.78864247,0.010350258,0.1689313,0.0013729758,0.00068522454,0.00060502754,0.00093368173,0.00031956832,0.028159352],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979728,0.0011147643,0.00009971716,0.00024230656,0.00037727045,0.00019315729],"domain_scores_gemma":[0.9787266,0.01862755,0.0005143755,0.00067224394,0.0008447052,0.00061450567],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039543686,0.00091487775,0.0022824567,0.0017043436,0.0016526994,0.0038967286,0.002192855,0.002196839,0.006421954],"category_scores_gemma":[0.023789395,0.0010988839,0.0011681302,0.003295671,0.0031258485,0.009123431,0.002471339,0.0058028125,0.0007715873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014425981,0.00015081636,0.0012740911,0.00052148703,0.00004018654,0.00015946374,0.0003390654,0.022749787,0.0006217815,0.9173597,0.006607068,0.05003222],"study_design_scores_gemma":[0.00003565464,0.000034315293,0.00028170855,0.000069913665,0.00002070159,0.000116056595,0.00007964664,0.077997215,0.00033026768,0.9169197,0.004102721,0.000011983493],"about_ca_topic_score_codex":0.0019383009,"about_ca_topic_score_gemma":0.0021003105,"teacher_disagreement_score":0.006421954,"about_ca_system_score_codex":0.0020236233,"about_ca_system_score_gemma":0.0017356268,"threshold_uncertainty_score":0.0214836},"labels":[],"label_agreement":null},{"id":"W2076965738","doi":"10.1007/s10878-007-9042-z","title":"Monotonicity of strong searching on digraphs","year":2007,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Digraph; Monotonic function; Theory of computation; Combinatorics; Enhanced Data Rates for GSM Evolution; Mathematics; Discrete mathematics; Computer science; Algorithm; Artificial intelligence","score_opus":0.015271290622068032,"score_gpt":0.2832409714051561,"score_spread":0.267969680783088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076965738","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4122244,0.0018757562,0.51149094,0.003051235,0.00017628427,0.00021031187,0.0009979754,0.0005532457,0.06941984],"genre_scores_gemma":[0.90535885,0.0016242987,0.07801694,0.0005310351,0.00023231664,0.0002613222,0.0005415863,0.00021459279,0.01321904],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977494,0.0008774137,0.00014874844,0.00042603342,0.00047068886,0.0003276964],"domain_scores_gemma":[0.95464706,0.035713118,0.00221462,0.002597006,0.0026408618,0.002187306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003203665,0.0009137017,0.0021516208,0.0024398456,0.0016036219,0.0038892785,0.002326795,0.0015837166,0.008897034],"category_scores_gemma":[0.028761413,0.0014664857,0.0013540585,0.002463914,0.0031843327,0.010355292,0.0029215019,0.0033442494,0.00077052036],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022128443,0.00012952847,0.0019479152,0.0003278838,0.000047773396,0.00021018431,0.00040305598,0.01560452,0.0028338227,0.94946265,0.0025475135,0.026263848],"study_design_scores_gemma":[0.000052967724,0.00010556014,0.0008133988,0.000059757796,0.000033784127,0.00035502904,0.00013864825,0.0681653,0.0011057951,0.9268579,0.002287283,0.000024648258],"about_ca_topic_score_codex":0.0013192515,"about_ca_topic_score_gemma":0.0018140017,"teacher_disagreement_score":0.008897034,"about_ca_system_score_codex":0.0014347279,"about_ca_system_score_gemma":0.0013883474,"threshold_uncertainty_score":0.02976358},"labels":[],"label_agreement":null},{"id":"W2078130991","doi":"10.1007/s00446-014-0220-9","title":"Forming sequences of geometric patterns with oblivious mobile robots","year":2014,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Robot; Computer science; Simple (philosophy); Series (stratigraphy); Mobile robot; Orientation (vector space); Theoretical computer science; Theory of computation; Distributed computing; Artificial intelligence; Algorithm; Mathematics; Geometry","score_opus":0.012430973757408781,"score_gpt":0.2426073737867117,"score_spread":0.23017640002930292,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078130991","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.105843395,0.00010988089,0.8894525,0.0001896353,0.000039421582,0.00013644519,0.00005610604,0.0004234236,0.003749228],"genre_scores_gemma":[0.6083172,0.00020591705,0.38223585,0.00009656754,0.000026431839,0.0003224644,0.00021510698,0.00014838652,0.008432167],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99937755,0.00016744739,0.000043408963,0.00015182474,0.00017851371,0.00008142512],"domain_scores_gemma":[0.9987249,0.00051859353,0.00022867577,0.00030586778,0.00011082341,0.00011108244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005985481,0.00060260936,0.0010010736,0.00070424087,0.00079834793,0.0008262084,0.0018549089,0.0009867318,0.0034409447],"category_scores_gemma":[0.0033146907,0.0008231797,0.0006281958,0.0012356626,0.0013524399,0.0019097214,0.0024557763,0.0009987102,0.000727844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043294084,0.0001382973,0.0017065317,0.00018675915,0.000059776175,0.00020240077,0.0005019716,0.78890127,0.011769792,0.07438716,0.0016882087,0.12002485],"study_design_scores_gemma":[0.00006498057,0.00019679761,0.00029257117,0.000018782615,0.000015143468,0.0001115455,0.0001559777,0.91803074,0.006363535,0.07206865,0.002662597,0.000018643399],"about_ca_topic_score_codex":0.0017325067,"about_ca_topic_score_gemma":0.0020960802,"teacher_disagreement_score":0.0034409447,"about_ca_system_score_codex":0.00062775676,"about_ca_system_score_gemma":0.00075359695,"threshold_uncertainty_score":0.011511087},"labels":[],"label_agreement":null},{"id":"W2078479354","doi":"10.1007/s00446-013-0196-x","title":"Leader election for anonymous asynchronous agents in arbitrary networks","year":2013,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerstwo Edukacji i Nauki; Université du Québec en Outaouais","keywords":"Leader election; Asynchronous communication; Computer science; Adversarial system; Adversary; Graph; Theoretical computer science; Computer network; Distributed computing; Computer security; Artificial intelligence","score_opus":0.02571712385047296,"score_gpt":0.27218891363136144,"score_spread":0.2464717897808885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078479354","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12831123,0.0002204045,0.86248636,0.0004714344,0.000045263918,0.00006692681,0.00006613718,0.00017422368,0.00815806],"genre_scores_gemma":[0.9214944,0.0002843867,0.07271769,0.000059287362,0.00004560653,0.00012128603,0.000088137465,0.00003802752,0.0051511233],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992908,0.00032396195,0.000022233446,0.00013139474,0.00011772679,0.00011379208],"domain_scores_gemma":[0.99803,0.0012633484,0.00029392642,0.00012340135,0.00015387438,0.00013538336],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011424827,0.00043905352,0.00057289156,0.0006115921,0.0010501397,0.0010651635,0.0011559834,0.0008257456,0.0013223838],"category_scores_gemma":[0.005366917,0.0002404979,0.0003597171,0.0008263691,0.001225777,0.0015392012,0.001342255,0.0006417539,0.00023318166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000121711055,0.000040844836,0.000577323,0.00004992916,0.000016504568,0.00018405041,0.00017415558,0.84961057,0.0013621311,0.13503204,0.00091961905,0.011911134],"study_design_scores_gemma":[0.000020390982,0.000020683945,0.000071385315,0.0000032125029,0.000004312687,0.000018640892,0.000046311223,0.94461936,0.00037403728,0.054169264,0.0006479604,0.0000044895937],"about_ca_topic_score_codex":0.0014970881,"about_ca_topic_score_gemma":0.0015140516,"teacher_disagreement_score":0.0014970881,"about_ca_system_score_codex":0.00076189113,"about_ca_system_score_gemma":0.0005650648,"threshold_uncertainty_score":0.006042123},"labels":[],"label_agreement":null},{"id":"W2078597682","doi":"10.1109/robio.2012.6491290","title":"Multi-robot repeated boundary coverage under uncertainty","year":2012,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Boundary (topology); Robot; Event (particle physics); Computer science; Heuristic; Travelling salesman problem; Artificial intelligence; Path (computing); Mobile robot; Mathematical optimization; Algorithm; Mathematics","score_opus":0.045193919496528165,"score_gpt":0.29688644021853877,"score_spread":0.2516925207220106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078597682","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24134439,0.0006799612,0.7527164,0.00034159748,0.00004507621,0.00006895333,0.00008885894,0.00047633462,0.0042384067],"genre_scores_gemma":[0.96087646,0.00012381862,0.037284892,0.000031794523,0.000019444371,0.00007365762,0.00007933117,0.000041291398,0.0014692618],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993284,0.00021621604,0.000021522597,0.00016491259,0.00013362392,0.000135319],"domain_scores_gemma":[0.9973917,0.0016141987,0.0004636477,0.00018512536,0.0001424211,0.00020284245],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092187925,0.0008762889,0.0014389696,0.00052803074,0.00059624243,0.000782388,0.0015827714,0.0015207444,0.0013483866],"category_scores_gemma":[0.0035188445,0.00051548454,0.0007471563,0.0006699635,0.001216044,0.0014861503,0.0018108039,0.0008524302,0.00021254722],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006386861,0.000020326135,0.0003027256,0.000028866103,0.000017322312,0.00012052552,0.000040722058,0.99156266,0.00087658054,0.001493561,0.00014020271,0.0053326907],"study_design_scores_gemma":[0.000013015809,0.00004400874,0.00014200356,0.0000031780046,0.000004684985,0.000030144707,0.000017707729,0.9963379,0.00044077562,0.0027949123,0.00016657979,0.000005090486],"about_ca_topic_score_codex":0.0038782747,"about_ca_topic_score_gemma":0.0017856787,"teacher_disagreement_score":0.0038782747,"about_ca_system_score_codex":0.00080110016,"about_ca_system_score_gemma":0.0005673546,"threshold_uncertainty_score":0.0077114105},"labels":[],"label_agreement":null},{"id":"W2078850190","doi":"10.1145/1132516.1132609","title":"Simple cost sharing schemes for multicommodity rent-or-buy and stochastic Steiner tree","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Steiner tree problem; Simple (philosophy); Computer science; Mathematical optimization; Tree (set theory); Mathematics; Combinatorics","score_opus":0.04752247368256846,"score_gpt":0.30300298513530827,"score_spread":0.2554805114527398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078850190","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022333238,0.00053585484,0.9652967,0.0005324799,0.00013263426,0.00035458733,0.00021492949,0.00045970498,0.01013988],"genre_scores_gemma":[0.4838469,0.0007037547,0.50282645,0.00030654913,0.00014156701,0.00064601295,0.00035187852,0.00021829556,0.010958696],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99753225,0.0009804231,0.000117293785,0.0003182391,0.0007017561,0.000350046],"domain_scores_gemma":[0.99728656,0.001356735,0.00021666715,0.00074620993,0.0002616083,0.00013223331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040980447,0.001209903,0.0015700071,0.0007732692,0.0011090413,0.0016502717,0.00422668,0.0023221571,0.011491416],"category_scores_gemma":[0.010705821,0.00075815397,0.0016396622,0.002182023,0.0013589612,0.0051342305,0.0028481106,0.0025136194,0.0012676694],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038003802,0.00016800556,0.00025406445,0.00023305872,0.000051806634,0.00007613231,0.00022540656,0.4398785,0.0028573477,0.45897093,0.006443119,0.09046164],"study_design_scores_gemma":[0.00007212994,0.00008928101,0.00009604707,0.000028735718,0.000021248754,0.00004654656,0.000026539194,0.8637823,0.0009993827,0.12990138,0.0049124816,0.000024009752],"about_ca_topic_score_codex":0.0022005392,"about_ca_topic_score_gemma":0.0032550246,"teacher_disagreement_score":0.011491416,"about_ca_system_score_codex":0.0035989233,"about_ca_system_score_gemma":0.0018566031,"threshold_uncertainty_score":0.03844261},"labels":[],"label_agreement":null},{"id":"W2078856178","doi":"10.1007/s10878-008-9156-y","title":"The canadian traveller problem and its competitive analysis","year":2008,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Theory of computation; Vertex (graph theory); Computer science; Competitive analysis; Adaptive strategies; Graph; Grid; Mathematical optimization; Shortest path problem; Greedy algorithm; Enhanced Data Rates for GSM Evolution; Mathematics; Combinatorics; Theoretical computer science; Algorithm; Upper and lower bounds; Artificial intelligence; Geography","score_opus":0.014219725251747941,"score_gpt":0.2319537224110097,"score_spread":0.21773399715926176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078856178","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2314587,0.003963054,0.37930104,0.010156232,0.00034705122,0.0009083451,0.0028018302,0.0008041481,0.3702596],"genre_scores_gemma":[0.89602125,0.0024972584,0.059910715,0.0009211478,0.00034622443,0.0005776406,0.0014584464,0.000262678,0.03800478],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99709713,0.0008695553,0.000061216604,0.00048633752,0.0007224403,0.0007633748],"domain_scores_gemma":[0.9932628,0.0041595083,0.00047742398,0.00040332275,0.0007647344,0.0009321522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020386134,0.0017700451,0.0017694118,0.0018793195,0.0031948374,0.004188172,0.005376137,0.0033304445,0.023184849],"category_scores_gemma":[0.013742438,0.0005178149,0.0010531347,0.0034376024,0.0026729591,0.005057308,0.0025840658,0.002989682,0.0015781206],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065320666,0.0003577366,0.0024249454,0.00043331238,0.00013880793,0.00042724793,0.00049466523,0.21282591,0.0011463641,0.690898,0.039599158,0.050600745],"study_design_scores_gemma":[0.00020507489,0.00017581112,0.0010992619,0.00005724116,0.000072420495,0.00033831652,0.00036072484,0.66146845,0.0006877746,0.31214696,0.023310354,0.00007758397],"about_ca_topic_score_codex":0.09749472,"about_ca_topic_score_gemma":0.061604,"teacher_disagreement_score":0.09749472,"about_ca_system_score_codex":0.0079563325,"about_ca_system_score_gemma":0.0065819602,"threshold_uncertainty_score":0.19385445},"labels":[],"label_agreement":null},{"id":"W2080610036","doi":"10.1007/s10479-008-0337-y","title":"Efficient solution approaches for a discrete multi-facility competitive interaction model","year":2008,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science","score_opus":0.5969619837764057,"score_gpt":0.47512096968329526,"score_spread":0.12184101409311049,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080610036","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009829772,0.00063572964,0.97932947,0.00054280437,0.00006817106,0.00012735021,0.00017452605,0.000089182206,0.009202993],"genre_scores_gemma":[0.47059518,0.0015279127,0.5083915,0.0003221621,0.00026977944,0.00079999655,0.000496082,0.00020007526,0.017397366],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985663,0.0006301347,0.00004446417,0.00019888501,0.00031889396,0.00024122073],"domain_scores_gemma":[0.9968971,0.0024063303,0.00017718437,0.00012192008,0.0002289333,0.0001686251],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002205285,0.0018434136,0.0032170254,0.0016114004,0.0010250352,0.003086543,0.0048399013,0.0040877126,0.008936232],"category_scores_gemma":[0.0053299675,0.0014573087,0.0017665867,0.0027959342,0.0016716731,0.0028369818,0.0033821191,0.0034302657,0.0007931424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054980563,0.000087142886,0.00012947107,0.00014307353,0.00004673274,0.00005696121,0.00004871491,0.9177094,0.00026408522,0.06953783,0.0017942456,0.010127414],"study_design_scores_gemma":[0.000018968805,0.000013652663,0.000023282684,0.0000069184503,0.000009165546,0.000009613172,0.00001431457,0.9802893,0.000042292024,0.019065091,0.0005022168,0.0000051774023],"about_ca_topic_score_codex":0.009736752,"about_ca_topic_score_gemma":0.00847574,"teacher_disagreement_score":0.009736752,"about_ca_system_score_codex":0.0031029093,"about_ca_system_score_gemma":0.002972475,"threshold_uncertainty_score":0.02989465},"labels":[],"label_agreement":null},{"id":"W2080745503","doi":"10.1016/j.tcs.2007.05.011","title":"Map construction of unknown graphs by multiple agents","year":2007,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":83,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Rendezvous; Traverse; Graph; Computer science; Theoretical computer science; Combinatorics; Mathematics; Discrete mathematics; Algorithm","score_opus":0.01071225163422513,"score_gpt":0.2594873612681509,"score_spread":0.2487751096339258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080745503","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059084058,0.00010583563,0.93481266,0.00032976113,0.000044812943,0.00008392001,0.00010529962,0.0006207251,0.0048128515],"genre_scores_gemma":[0.5845117,0.0002327641,0.40529865,0.00009206539,0.00004207253,0.00017712978,0.0003223293,0.00030667838,0.009016654],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992675,0.00029510199,0.000022707782,0.00017925678,0.00014551655,0.00008978465],"domain_scores_gemma":[0.997456,0.0014259323,0.00013881929,0.0005692996,0.0002190356,0.00019098667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00082562875,0.00068840006,0.0011504955,0.0011256782,0.0013928701,0.0015859039,0.0018539609,0.0016931574,0.0045497385],"category_scores_gemma":[0.0055892435,0.0008316221,0.0015690514,0.000967614,0.0013286651,0.003458294,0.0038490614,0.0017379789,0.0007190696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044456418,0.00019414553,0.0016875244,0.00036950462,0.00016202728,0.00059618615,0.00095112715,0.6354782,0.010826648,0.20894979,0.0048959907,0.13544425],"study_design_scores_gemma":[0.000028167093,0.00004208845,0.00022624359,0.000013933486,0.000031982792,0.00006619877,0.000119825665,0.8822056,0.0041725705,0.11074325,0.0023316918,0.000018494658],"about_ca_topic_score_codex":0.0035942874,"about_ca_topic_score_gemma":0.0028343042,"teacher_disagreement_score":0.0045497385,"about_ca_system_score_codex":0.000947457,"about_ca_system_score_gemma":0.00092355715,"threshold_uncertainty_score":0.015220404},"labels":[],"label_agreement":null},{"id":"W2081055073","doi":"","title":"Delays Induce an Exponential Memory Gap for Rendezvous in Trees","year":2011,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA); Université du Québec en Outaouais","keywords":"Rendezvous; Computer science; Exponential function; Exponential growth; Tree (set theory); Parallel computing; Theoretical computer science; Mathematics; Combinatorics; Physics","score_opus":0.21363344366847736,"score_gpt":0.20982607274773118,"score_spread":0.003807370920746178,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081055073","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8369841,0.0010786809,0.14786556,0.0016220034,0.000059130656,0.00006151671,0.00041392064,0.0012695454,0.010645472],"genre_scores_gemma":[0.9818556,0.0003365736,0.015182118,0.00018739977,0.00003648858,0.00011262901,0.00018095183,0.00017380127,0.0019344355],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99846554,0.00022851981,0.0000984774,0.00034789246,0.00028478916,0.00057476154],"domain_scores_gemma":[0.97566336,0.01890908,0.001723528,0.0023057293,0.00057616667,0.00082208024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011133978,0.000687923,0.001085753,0.00073136116,0.0012144592,0.0023364937,0.0017553086,0.0012455187,0.0046800408],"category_scores_gemma":[0.014217412,0.00057412067,0.00085119525,0.0007077108,0.002194946,0.006879834,0.0031862252,0.0021717336,0.0005470771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005768907,0.00049417134,0.008459187,0.0011825738,0.00022510166,0.0014770012,0.0022451305,0.4232534,0.09987686,0.37063086,0.005667224,0.08071958],"study_design_scores_gemma":[0.00022872136,0.00049242616,0.0018659693,0.000093573,0.00013979763,0.0006956007,0.0005319767,0.5936682,0.04133484,0.35669628,0.0041787997,0.00007376505],"about_ca_topic_score_codex":0.0010518163,"about_ca_topic_score_gemma":0.0010737752,"teacher_disagreement_score":0.0046800408,"about_ca_system_score_codex":0.0015537441,"about_ca_system_score_gemma":0.0011012517,"threshold_uncertainty_score":0.015656292},"labels":[],"label_agreement":null},{"id":"W2081264158","doi":"10.2316/journal.206.2010.4.206-3325","title":"REACHABLE GRASPS ON A POLYGON OF A ROBOT ARM: FINDING CONVEX ROPES WITHOUT TRIANGULATION","year":2010,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Regular polygon; Simple polygon; Vertex (graph theory); Polygon (computer graphics); Convex hull; Convex polygon; Polygon covering; Combinatorics; Mathematics; Robot; Minimum-weight triangulation; Computer science; Artificial intelligence; Delaunay triangulation; Geometry; Constrained Delaunay triangulation","score_opus":0.020892876619404244,"score_gpt":0.2969573623987184,"score_spread":0.27606448577931414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2081264158","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0890577,0.00020310323,0.90534604,0.00012733266,0.000018649027,0.00010700216,0.00015865617,0.00055664853,0.0044247806],"genre_scores_gemma":[0.58456725,0.0002783959,0.41048455,0.000035913577,0.000019305307,0.00016460202,0.00038242276,0.00023416035,0.0038334732],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99955326,0.00009636399,0.000031586846,0.00014100446,0.000112843285,0.00006498846],"domain_scores_gemma":[0.9988482,0.0006520703,0.00017009393,0.00019468402,0.00006564589,0.00006943884],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005856878,0.00094542763,0.0015294141,0.0007102039,0.0006137836,0.00095449976,0.0014529182,0.001643171,0.00325764],"category_scores_gemma":[0.0036048945,0.0013875682,0.0014259932,0.00066533097,0.0014474777,0.0025002763,0.0025918495,0.0011785564,0.00069738016],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033199912,0.000069510075,0.00053377653,0.00024065135,0.000049672348,0.0005366013,0.00034353702,0.91970235,0.007214393,0.019387111,0.0012175462,0.05037287],"study_design_scores_gemma":[0.000039116356,0.00011969638,0.00018484193,0.000030924995,0.000015110454,0.0001379477,0.000105107945,0.9724161,0.0014974546,0.024475725,0.00095354626,0.000024344385],"about_ca_topic_score_codex":0.003146332,"about_ca_topic_score_gemma":0.0020403059,"teacher_disagreement_score":0.00325764,"about_ca_system_score_codex":0.0005792055,"about_ca_system_score_gemma":0.00072044827,"threshold_uncertainty_score":0.010897875},"labels":[],"label_agreement":null},{"id":"W2082940000","doi":"10.1145/1989493.1989513","title":"Brief announcement","year":2011,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paging; Computer science; Cache; Competitive analysis; CPU cache; Cache algorithms; Parallel computing; Multi-core processor; Metric (unit); Time complexity; Online algorithm; Upper and lower bounds; Operating system; Algorithm; Mathematics","score_opus":0.0693261546613576,"score_gpt":0.24316357650580536,"score_spread":0.17383742184444778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082940000","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022989772,0.04066354,0.0043198657,0.17121042,0.4311845,0.0003715527,0.0040118587,0.00093479495,0.34500447],"genre_scores_gemma":[0.015007508,0.029084956,0.0019472851,0.03884664,0.13209715,0.00023684936,0.0030434255,0.00023453332,0.7795016],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999067,0.00010882541,0.00007430696,0.00021130727,0.00039019706,0.00014841316],"domain_scores_gemma":[0.9966852,0.00051083654,0.00015099395,0.00023528004,0.0012276219,0.0011901123],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014179845,0.0007757232,0.00062606914,0.0010556274,0.0013284486,0.0029951518,0.0014028376,0.0048524435,0.22497824],"category_scores_gemma":[0.0053616073,0.00028500636,0.00055023364,0.0007866743,0.00052546285,0.002085357,0.0013371424,0.003430634,0.11585162],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011760067,0.00005727804,0.00022354347,0.0002279916,0.000007296475,0.00021773831,0.000024999117,0.00004979716,0.00059975026,0.005585635,0.9180369,0.07485146],"study_design_scores_gemma":[0.000010087007,0.000030963532,0.00033444318,0.00005801495,0.000004668655,0.00015278562,0.00002540991,0.000027681144,0.00018551474,0.001011664,0.9981541,0.0000045776696],"about_ca_topic_score_codex":0.0013385382,"about_ca_topic_score_gemma":0.0028807456,"teacher_disagreement_score":0.7750218,"about_ca_system_score_codex":0.0014410019,"about_ca_system_score_gemma":0.001936749,"threshold_uncertainty_score":0.7526272},"labels":[],"label_agreement":null},{"id":"W2084046657","doi":"10.1016/j.disopt.2012.01.001","title":"Emergency path restoration problems","year":2012,"lang":"en","type":"article","venue":"Discrete Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Server; Scheduling (production processes); Computer science; Path (computing); Time complexity; Node (physics); Computer network; Distributed computing; Mathematical optimization; Mathematics; Algorithm; Engineering","score_opus":0.024719906679499283,"score_gpt":0.27085628613100643,"score_spread":0.24613637945150715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084046657","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023028644,0.0016509439,0.89660305,0.0023655875,0.00057505653,0.0001809594,0.00062036637,0.00041928398,0.07455624],"genre_scores_gemma":[0.59920925,0.0027045317,0.26190585,0.00070000655,0.0006392369,0.00043807251,0.0015282274,0.0005436123,0.13233119],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993917,0.0001713161,0.000018806899,0.00016184777,0.00014789584,0.000108459535],"domain_scores_gemma":[0.99925727,0.00036556428,0.00008655885,0.000081295984,0.00010751035,0.000101741876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008175296,0.00096174097,0.0012350578,0.0008282015,0.0008549935,0.0019517785,0.0014214646,0.002264851,0.01791007],"category_scores_gemma":[0.003165204,0.00050492835,0.0008550133,0.00095107657,0.0012245236,0.001846067,0.0017346456,0.0027164978,0.0013709312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017578299,0.00014380434,0.00039754622,0.0002972299,0.000051694868,0.0002744343,0.00011878537,0.5189404,0.0009589979,0.36151895,0.0318101,0.0853123],"study_design_scores_gemma":[0.000059761205,0.00007159742,0.00025048456,0.000066625355,0.000026213247,0.0003476112,0.00016164144,0.6455126,0.001080376,0.32101157,0.031386957,0.000024592397],"about_ca_topic_score_codex":0.0020405962,"about_ca_topic_score_gemma":0.0016844886,"teacher_disagreement_score":0.01791007,"about_ca_system_score_codex":0.0012042772,"about_ca_system_score_gemma":0.0012705517,"threshold_uncertainty_score":0.059915125},"labels":[],"label_agreement":null},{"id":"W2085216434","doi":"10.1016/s0304-3975(00)00144-4","title":"The ultimate strategy to search on m rays?","year":2001,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":58,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Competitive analysis; Upper and lower bounds; Mathematics; Combinatorics; Algorithm; Computer science; Mathematical analysis","score_opus":0.02509891212686544,"score_gpt":0.30945091024063853,"score_spread":0.2843519981137731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085216434","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07438202,0.006781055,0.7807874,0.02637974,0.0010550016,0.0001375134,0.0004299018,0.0010153591,0.109032005],"genre_scores_gemma":[0.56570363,0.0031638723,0.37024513,0.0031529309,0.00064635143,0.00024523409,0.0004165875,0.00055753975,0.05586856],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990693,0.000413295,0.000048526264,0.00017443193,0.0001431271,0.00015145518],"domain_scores_gemma":[0.9974752,0.001290876,0.00019786485,0.00050929835,0.0002755764,0.00025106623],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016837232,0.000774751,0.0011054329,0.00092236476,0.0014544284,0.0033859725,0.0017984966,0.0035895072,0.016008869],"category_scores_gemma":[0.013212392,0.00074393145,0.00076516723,0.001079047,0.0025135966,0.0070541026,0.0022812323,0.0026301788,0.004459389],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036046185,0.000096420496,0.0017670913,0.00026114722,0.00008859085,0.0000986246,0.0002778004,0.017476676,0.0014186796,0.7949327,0.022821784,0.16039993],"study_design_scores_gemma":[0.00007201312,0.00012328473,0.00037285828,0.00019451222,0.000043136788,0.00026756938,0.0004944738,0.07971374,0.0015291832,0.88358647,0.033565383,0.000037457557],"about_ca_topic_score_codex":0.0007909136,"about_ca_topic_score_gemma":0.0011123361,"teacher_disagreement_score":0.016008869,"about_ca_system_score_codex":0.00085002364,"about_ca_system_score_gemma":0.0010022693,"threshold_uncertainty_score":0.05355507},"labels":[],"label_agreement":null},{"id":"W2085532579","doi":"10.1109/hpcs.2010.5547101","title":"Hardware acceleration of Scatter Search","year":2010,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Computer science; Field-programmable gate array; Software; High-level programming language; Implementation; Gate array; Heuristic; Parallel computing; Computer engineering; Computer architecture; Parallelism (grammar); Programming language; Computer hardware; Programming paradigm; Artificial intelligence","score_opus":0.02614716184700726,"score_gpt":0.2827352670658159,"score_spread":0.25658810521880865,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2085532579","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14267631,0.0009632412,0.8366101,0.00025926175,0.00012627458,0.00006784915,0.000113807815,0.0058648284,0.013318385],"genre_scores_gemma":[0.64133704,0.00027099348,0.35390115,0.00012685593,0.000022651584,0.000079870944,0.00024900128,0.00037397383,0.0036385201],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996518,0.00008522565,0.000017258064,0.000055052325,0.00013273895,0.000057938327],"domain_scores_gemma":[0.99911374,0.00048599148,0.00005381195,0.00013027193,0.00018184185,0.00003433608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038504784,0.00055230677,0.0004894135,0.0004628645,0.00035673115,0.00060217356,0.000775572,0.0004512747,0.0059454893],"category_scores_gemma":[0.0017284655,0.00021331791,0.00036877592,0.0006961288,0.00029441263,0.00071276794,0.00054347643,0.000497524,0.0011293886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010157981,0.00015191128,0.0034263527,0.00040239343,0.00011558654,0.00025069836,0.00021608015,0.4394991,0.05353908,0.013275569,0.007400887,0.48070648],"study_design_scores_gemma":[0.00012645614,0.00032556674,0.0010357617,0.00003079091,0.00003560062,0.0002060136,0.00005444052,0.9641347,0.022186209,0.003704028,0.00814259,0.000017820787],"about_ca_topic_score_codex":0.0029624626,"about_ca_topic_score_gemma":0.0040064687,"teacher_disagreement_score":0.0059454893,"about_ca_system_score_codex":0.0004244553,"about_ca_system_score_gemma":0.000845092,"threshold_uncertainty_score":0.019889712},"labels":[],"label_agreement":null},{"id":"W2086312880","doi":"10.1016/j.tcs.2014.03.028","title":"Multi-target ray searching problems","year":2014,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Agence Nationale de la Recherche","keywords":"Multiplicative function; Context (archaeology); Mathematics; Mathematical optimization; Metric (unit); Measure (data warehouse); Disjoint sets; Linear search; Asymptotically optimal algorithm; Competitive analysis; Beam search; Computer science; Algorithm; Search algorithm; Discrete mathematics; Upper and lower bounds; Data mining","score_opus":0.017390947517490634,"score_gpt":0.26955533553006034,"score_spread":0.2521643880125697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086312880","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012991605,0.0012038215,0.9605766,0.0006748931,0.00010244003,0.000113535345,0.0002521502,0.00031140668,0.02377352],"genre_scores_gemma":[0.46381813,0.0023856557,0.48269907,0.0006144899,0.00032839525,0.0007355393,0.0010726424,0.0007028277,0.04764325],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99849,0.00057858275,0.000059489754,0.0003122199,0.0004352104,0.00012450402],"domain_scores_gemma":[0.99607676,0.003056258,0.00024953845,0.0001816742,0.0002479467,0.00018776016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021497388,0.0018004624,0.002230454,0.0017389612,0.0009804926,0.0030070506,0.002462227,0.004789277,0.011569322],"category_scores_gemma":[0.009806955,0.0011359456,0.0016104785,0.0023329319,0.0014170017,0.0032396105,0.003702652,0.0026788318,0.0020478521],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045603394,0.00014310522,0.0009769977,0.00055356,0.00019716586,0.00035772147,0.00019470887,0.7935922,0.0024152258,0.1287442,0.008373222,0.063995756],"study_design_scores_gemma":[0.000058225138,0.00010551599,0.00032360584,0.000052398304,0.000044968663,0.00024064678,0.00008072443,0.91496164,0.0014551372,0.07829022,0.0043563973,0.000030442437],"about_ca_topic_score_codex":0.0010562128,"about_ca_topic_score_gemma":0.0007120971,"teacher_disagreement_score":0.011569322,"about_ca_system_score_codex":0.0014383654,"about_ca_system_score_gemma":0.00079614174,"threshold_uncertainty_score":0.038703263},"labels":[],"label_agreement":null},{"id":"W2086702855","doi":"10.1145/1978782.1978789","title":"Randomized rendezvous with limited memory","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Rendezvous; Corollary; Computer science; Node (physics); State (computer science); Ring (chemistry); Discrete mathematics; Mathematics; Combinatorics; Algorithm; Physics","score_opus":0.04869198837809187,"score_gpt":0.25294687808002886,"score_spread":0.204254889701937,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086702855","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36577415,0.0004148793,0.62072843,0.0007274542,0.00006206526,0.0001906388,0.00021017199,0.0016383032,0.010253921],"genre_scores_gemma":[0.94766647,0.00007370698,0.048953515,0.00007641396,0.000020364962,0.00013514409,0.00009154576,0.000062307205,0.0029204865],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982008,0.00054940867,0.000091840135,0.0004342551,0.00027799336,0.0004456715],"domain_scores_gemma":[0.99282396,0.003749008,0.00087834365,0.0018637428,0.0002924331,0.0003924747],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016963894,0.00055810425,0.00089335546,0.00039631082,0.0008639651,0.0010783677,0.0020377317,0.0007650914,0.0040379856],"category_scores_gemma":[0.00816338,0.00043142543,0.0005178289,0.00039290474,0.0014497801,0.0031190803,0.0028492361,0.000808124,0.0006330096],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004103332,0.00025968143,0.0026165575,0.00028349747,0.00014802384,0.00057442277,0.00041673973,0.790143,0.02999976,0.11683898,0.0030036122,0.051612385],"study_design_scores_gemma":[0.00031192641,0.00035616252,0.00037707985,0.000014680367,0.000039023445,0.00014434649,0.00009230222,0.9420141,0.0106901815,0.044445753,0.0014822172,0.000032282995],"about_ca_topic_score_codex":0.0013121765,"about_ca_topic_score_gemma":0.0021633354,"teacher_disagreement_score":0.0040379856,"about_ca_system_score_codex":0.0009067541,"about_ca_system_score_gemma":0.0011344359,"threshold_uncertainty_score":0.013508379},"labels":[],"label_agreement":null},{"id":"W2087097376","doi":"10.1145/564870.564906","title":"Capture of an intruder by mobile agents","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":158,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"University of Ottawa","keywords":"Computer science; Jump; Point (geometry); Tree (set theory); Graph; Tree network; Time complexity; Distributed computing; Theoretical computer science; Algorithm; Mathematics","score_opus":0.020587912109694226,"score_gpt":0.2554402453622562,"score_spread":0.23485233325256194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087097376","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34496683,0.00041999764,0.64537215,0.0005707293,0.000056928737,0.00025331468,0.00016289209,0.00061980856,0.0075773457],"genre_scores_gemma":[0.7978427,0.00036097114,0.19672912,0.00011367693,0.000020295538,0.00018491506,0.0003013422,0.000047944584,0.0043990808],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995745,0.00008926692,0.00002548444,0.000099183526,0.00007893337,0.00013263416],"domain_scores_gemma":[0.99929607,0.0003471262,0.00011801788,0.00008108404,0.000055292934,0.00010234873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004291657,0.00082800456,0.00082001835,0.00055196177,0.00079856935,0.0009767457,0.0016791287,0.0014402508,0.0025445265],"category_scores_gemma":[0.0025792145,0.00053274067,0.0010224126,0.0005610403,0.0006503481,0.0019039903,0.0023374788,0.0008536942,0.0004250262],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006071561,0.0002136775,0.00832737,0.00040745395,0.00021983449,0.0017361862,0.0008147071,0.84269136,0.02065801,0.039942186,0.0027681487,0.081613995],"study_design_scores_gemma":[0.00004025448,0.00018064391,0.00076258444,0.00002387418,0.000044812183,0.00030423704,0.0004070161,0.98136234,0.0036911364,0.010300607,0.002865992,0.000016353166],"about_ca_topic_score_codex":0.00393295,"about_ca_topic_score_gemma":0.004159134,"teacher_disagreement_score":0.00393295,"about_ca_system_score_codex":0.00064596377,"about_ca_system_score_gemma":0.00068225706,"threshold_uncertainty_score":0.0085122585},"labels":[],"label_agreement":null},{"id":"W2088456596","doi":"10.1016/j.orl.2014.12.008","title":"A tight bound on the speed-up through storage for quickest multi-commodity flows","year":2014,"lang":"en","type":"article","venue":"Operations Research Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of British Columbia; Deutsche Forschungsgemeinschaft","keywords":"Upper and lower bounds; Computer science; Speedup; Commodity; Parallel computing; Mathematics; Mathematical optimization; Simulation; Business; Mathematical analysis","score_opus":0.14718004806790977,"score_gpt":0.38045640621018106,"score_spread":0.2332763581422713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088456596","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12806548,0.027433226,0.7467665,0.014756726,0.0032291473,0.0006058146,0.0045921947,0.005026421,0.069524534],"genre_scores_gemma":[0.76204747,0.01236873,0.18944752,0.003139042,0.0023823816,0.00085073995,0.0015355957,0.0027997673,0.025428737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9942697,0.0011701885,0.00024503353,0.0010187079,0.0010877243,0.0022086634],"domain_scores_gemma":[0.9464102,0.04208922,0.0017222017,0.0052301777,0.002653646,0.0018945755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009013445,0.0052570705,0.006001925,0.0037839687,0.003299172,0.008695236,0.0061558504,0.005187835,0.030398315],"category_scores_gemma":[0.06829456,0.0026110166,0.002505337,0.0067754094,0.0050566145,0.021296484,0.007304707,0.009042829,0.0038070197],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.004131096,0.00054283126,0.001907597,0.0029541973,0.00030582142,0.00047740142,0.0006120673,0.5783427,0.017683081,0.18903872,0.060527947,0.14347653],"study_design_scores_gemma":[0.00015532898,0.00032417287,0.00082921365,0.00047013848,0.00021285511,0.0004271028,0.0002348867,0.7687767,0.00747552,0.21408807,0.0068855244,0.0001205579],"about_ca_topic_score_codex":0.0035793057,"about_ca_topic_score_gemma":0.0033882535,"teacher_disagreement_score":0.030398315,"about_ca_system_score_codex":0.0038581975,"about_ca_system_score_gemma":0.0058366866,"threshold_uncertainty_score":0.1016925},"labels":[],"label_agreement":null},{"id":"W2088810319","doi":"10.1007/s10878-013-9614-z","title":"Generalized Canadian traveller problems","year":2013,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"National Tsing Hua University; National Science Council","keywords":"Competitive analysis; Theory of computation; Combinatorics; Constant (computer programming); Upper and lower bounds; Bounded function; Online algorithm; Vertex (graph theory); Enhanced Data Rates for GSM Evolution; Computer science; Mathematics; Generalization; Discrete mathematics; Mathematical optimization; Graph; Algorithm; Telecommunications","score_opus":0.013212597777398477,"score_gpt":0.2240957758642578,"score_spread":0.21088317808685933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088810319","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1483045,0.0038729673,0.2892544,0.008051698,0.00081095065,0.00033146946,0.0032780762,0.0004686771,0.5456273],"genre_scores_gemma":[0.6907567,0.002480868,0.05627492,0.0007248831,0.0003457197,0.00026873985,0.0022089868,0.00026076214,0.24667846],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99907076,0.0002391221,0.000031223633,0.00017786393,0.00025197674,0.00022903612],"domain_scores_gemma":[0.99840087,0.00061535084,0.000113180235,0.00015385744,0.00041745245,0.0002993105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084731623,0.0011941128,0.0013821556,0.0018414836,0.0026230672,0.0041195294,0.002762686,0.0028241796,0.028429776],"category_scores_gemma":[0.005635703,0.00055120315,0.0010198817,0.0026720746,0.0024042856,0.0032595186,0.0021856367,0.0032439095,0.0014350872],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000051262352,0.000022731267,0.00016430019,0.000046476973,0.000017924316,0.00005357217,0.000077236604,0.028350167,0.00013523514,0.941576,0.018644255,0.010860757],"study_design_scores_gemma":[0.000049280447,0.000021956166,0.0003319221,0.000032338634,0.00001967894,0.00009128672,0.00023512114,0.12231067,0.00022890657,0.84556645,0.03106506,0.000047207548],"about_ca_topic_score_codex":0.13550794,"about_ca_topic_score_gemma":0.14833404,"teacher_disagreement_score":0.13550794,"about_ca_system_score_codex":0.008791914,"about_ca_system_score_gemma":0.006373425,"threshold_uncertainty_score":0.2694384},"labels":[],"label_agreement":null},{"id":"W2089187143","doi":"10.1145/2594581","title":"Deterministic Network Exploration by Anonymous Silent Agents with Local Traffic Reports","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Node (physics); Normalization property; Computer network; Theoretical computer science","score_opus":0.02026235510793927,"score_gpt":0.24898517807918782,"score_spread":0.22872282297124855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089187143","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18093172,0.00015132835,0.8140061,0.00035941447,0.000017391487,0.00011024449,0.00013148814,0.0005873057,0.0037050163],"genre_scores_gemma":[0.84664065,0.000114407216,0.14877856,0.000089273424,0.000023582303,0.00029602047,0.00029389895,0.00007711345,0.0036864402],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969893,0.0013448178,0.00016476902,0.00056992477,0.0004727738,0.00045844773],"domain_scores_gemma":[0.9837531,0.01152424,0.001447097,0.002043815,0.00064457575,0.00058716716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032985527,0.0007518371,0.0011663001,0.00073815096,0.000992764,0.001452526,0.0022756334,0.0013344556,0.0013181781],"category_scores_gemma":[0.017507244,0.000701168,0.0012804259,0.0007734056,0.002083638,0.0034044806,0.00392938,0.0013895227,0.00031596996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016426521,0.000170291,0.0046570646,0.00021189298,0.0001278876,0.000559774,0.0012724581,0.8251135,0.00703233,0.11375149,0.0013277704,0.044132862],"study_design_scores_gemma":[0.00007176758,0.00007518058,0.00021010404,0.000017838483,0.000029590494,0.000071041264,0.00009689283,0.9460953,0.00286659,0.04948662,0.00095544476,0.000023687004],"about_ca_topic_score_codex":0.0015196067,"about_ca_topic_score_gemma":0.0015400118,"teacher_disagreement_score":0.0032985527,"about_ca_system_score_codex":0.0011746298,"about_ca_system_score_gemma":0.0014567676,"threshold_uncertainty_score":0.01744461},"labels":[],"label_agreement":null},{"id":"W2089845008","doi":"10.1007/s00453-015-9982-0","title":"Anonymous Meeting in Networks","year":2015,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Node (physics); Computer science; Theory of computation; Deterministic algorithm; Upper and lower bounds; Time complexity; Algorithm; Construct (python library); Existential quantification; Theoretical computer science; Mathematics; Discrete mathematics; Computer network","score_opus":0.028371181002250098,"score_gpt":0.2560131383583552,"score_spread":0.2276419573561051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2089845008","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04647278,0.0016454388,0.124704145,0.024909338,0.0056537297,0.00024183514,0.0023662301,0.0012520239,0.7927546],"genre_scores_gemma":[0.39545044,0.0010447896,0.024448011,0.0016543756,0.0017564108,0.00018456446,0.0011585768,0.00031968547,0.5739832],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855286,0.00061501766,0.000037622267,0.0003067252,0.00027289632,0.00021487927],"domain_scores_gemma":[0.99775714,0.0006060828,0.00021331896,0.00049775117,0.00037076543,0.00055501633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001156798,0.00051784597,0.00046156716,0.0008538532,0.0032930374,0.0030721186,0.0011227995,0.002075016,0.09204441],"category_scores_gemma":[0.007466613,0.00022421981,0.00041023936,0.0011153186,0.0007924273,0.004601624,0.0027696153,0.0018074817,0.020364307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030736648,0.000099454584,0.0015249267,0.00015908341,0.00004396308,0.00045335243,0.00068098336,0.0057958206,0.0011816263,0.5819921,0.2773355,0.1304259],"study_design_scores_gemma":[0.000034576904,0.000045428642,0.0010822036,0.00004937529,0.00003175077,0.00035988342,0.00086697,0.01437907,0.00096244924,0.35109058,0.6310663,0.000031441734],"about_ca_topic_score_codex":0.0018765061,"about_ca_topic_score_gemma":0.0035347205,"teacher_disagreement_score":0.09204441,"about_ca_system_score_codex":0.0012166707,"about_ca_system_score_gemma":0.001209763,"threshold_uncertainty_score":0.30791926},"labels":[],"label_agreement":null},{"id":"W2091712762","doi":"10.1002/rsa.20504","title":"Random walks which prefer unvisited edges: Exploring high girth even degree expanders in linear time","year":2013,"lang":"en","type":"article","venue":"Random Structures and Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council","keywords":"Combinatorics; Mathematics; Edge cover; Vertex (graph theory); Degree (music); Discrete mathematics; Random walk; Random regular graph; Regular graph; Upper and lower bounds; Graph; Graph power; Line graph; 1-planar graph; Physics","score_opus":0.03572688288415451,"score_gpt":0.2431883776456975,"score_spread":0.207461494761543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091712762","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8065007,0.00025436215,0.18619566,0.0004559436,0.000023812569,0.0001340975,0.00012784207,0.0006373148,0.005670199],"genre_scores_gemma":[0.94904965,0.000117944524,0.047530968,0.000089988236,0.00002077939,0.0001204665,0.00018117565,0.00012568725,0.0027632364],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99945754,0.00017284462,0.00002058761,0.00009912465,0.00009385201,0.00015594304],"domain_scores_gemma":[0.993236,0.0056059575,0.00038249601,0.0003027669,0.00015262599,0.00032025308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090148195,0.00057107967,0.0008254439,0.0007615173,0.00053764525,0.0010413567,0.0010304133,0.00086874596,0.0038293554],"category_scores_gemma":[0.00693691,0.0004124038,0.0006291518,0.0006783637,0.0008670655,0.0018811256,0.0012614591,0.00078951905,0.00038942302],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013823526,0.00035443003,0.004800284,0.00024955478,0.0001197771,0.0006842423,0.0005525175,0.8441635,0.023620442,0.073203474,0.0022996764,0.048569757],"study_design_scores_gemma":[0.000054998218,0.000096293086,0.00029967,0.000009061772,0.0000154821,0.00004882228,0.000046282013,0.9640438,0.001714206,0.03329913,0.0003650484,0.000007263764],"about_ca_topic_score_codex":0.0011886683,"about_ca_topic_score_gemma":0.0016849531,"teacher_disagreement_score":0.0038293554,"about_ca_system_score_codex":0.00067077647,"about_ca_system_score_gemma":0.0004249324,"threshold_uncertainty_score":0.012810469},"labels":[],"label_agreement":null},{"id":"W2091878431","doi":"10.1177/026455050104800112","title":"Stop and Search","year":2001,"lang":"en","type":"article","venue":"Probation Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Humber College","funders":"","keywords":"Psychology; History","score_opus":0.02940339629854249,"score_gpt":0.2747926312209453,"score_spread":0.24538923492240283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091878431","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034708228,0.0038277942,0.5915183,0.010544353,0.0021876397,0.00056885206,0.0012349455,0.005327638,0.35008225],"genre_scores_gemma":[0.353758,0.0018907168,0.22017156,0.005021446,0.0006673911,0.0008076989,0.0025293306,0.0034420253,0.41171187],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99752957,0.00065989443,0.000119995886,0.00041590785,0.0009796475,0.00029507375],"domain_scores_gemma":[0.9927549,0.0037539613,0.00035428038,0.0015253961,0.0012262773,0.0003850982],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024188466,0.0011652979,0.0016936332,0.0019039024,0.0021313082,0.0045406944,0.0016465535,0.0033910144,0.04984492],"category_scores_gemma":[0.015389564,0.00062791357,0.0012052751,0.0011307369,0.0019393483,0.004426774,0.003135785,0.004243416,0.018325666],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009737503,0.00032300074,0.0025774997,0.0006705169,0.00013088036,0.0008467177,0.0009194733,0.014942014,0.009074741,0.5294536,0.1185046,0.32158327],"study_design_scores_gemma":[0.00018272451,0.00041207892,0.0013499557,0.00027312082,0.00014426824,0.0013107704,0.00055927143,0.09485915,0.013930497,0.5538087,0.33308202,0.00008750462],"about_ca_topic_score_codex":0.0008614981,"about_ca_topic_score_gemma":0.001633246,"teacher_disagreement_score":0.04984492,"about_ca_system_score_codex":0.0009757566,"about_ca_system_score_gemma":0.0017663428,"threshold_uncertainty_score":0.16674787},"labels":[],"label_agreement":null},{"id":"W2091969952","doi":"10.1142/s0129054111008295","title":"UNIFORM SCATTERING OF AUTONOMOUS MOBILE ROBOTS IN A GRID","year":2011,"lang":"en","type":"article","venue":"International Journal of Foundations of Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Computer science; Grid; Asynchronous communication; Occupancy grid mapping; Mobile robot; Constructive proof; Distributed computing; Artificial intelligence; Mathematics; Computer network; Geometry","score_opus":0.035633509501549594,"score_gpt":0.30527993390190744,"score_spread":0.26964642440035785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091969952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20956105,0.00019228576,0.78395987,0.00045221715,0.00003716232,0.000072091556,0.00006116709,0.00017282851,0.0054913084],"genre_scores_gemma":[0.9447655,0.00019459713,0.051825173,0.00007128674,0.000022760245,0.0001222946,0.00009300489,0.00004116352,0.0028642374],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991027,0.0003069184,0.000043063166,0.00015109222,0.00020203338,0.00019415728],"domain_scores_gemma":[0.99724233,0.0017596143,0.00031825432,0.00027560454,0.00023011226,0.00017408756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010360049,0.00054469774,0.0007166595,0.00052015524,0.00078961573,0.0009861882,0.0009095047,0.0008086494,0.001173256],"category_scores_gemma":[0.004671213,0.00035706765,0.000605623,0.00050874247,0.0018884932,0.0017845214,0.003090679,0.0008122071,0.00024555813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003226356,0.000052638883,0.0025134855,0.0001025206,0.00005400942,0.000832185,0.0003379622,0.7980113,0.0069247596,0.1796085,0.0007593446,0.010480635],"study_design_scores_gemma":[0.00004366293,0.00006156903,0.00016223676,0.0000073707697,0.000007988101,0.00005872437,0.0001054786,0.9213091,0.0014531795,0.076175846,0.00060635305,0.000008453869],"about_ca_topic_score_codex":0.0022328503,"about_ca_topic_score_gemma":0.001070181,"teacher_disagreement_score":0.0022328503,"about_ca_system_score_codex":0.0007720289,"about_ca_system_score_gemma":0.0005269726,"threshold_uncertainty_score":0.0056014657},"labels":[],"label_agreement":null},{"id":"W2092863347","doi":"10.1007/s00224-011-9379-7","title":"Deterministic Rendezvous of Asynchronous Bounded-Memory Agents in Polygonal Terrains","year":2011,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Terrain; Asynchronous communication; Polygon (computer graphics); Computer science; Bounded function; Trajectory; Point (geometry); Algorithm; Mathematics; Geometry; Geography; Frame (networking); Mathematical analysis; Engineering","score_opus":0.06548969616562526,"score_gpt":0.28180400628514773,"score_spread":0.21631431011952246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2092863347","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6649819,0.0005435252,0.32078478,0.00061316026,0.000112804366,0.00006205658,0.00017927542,0.00038720833,0.012335296],"genre_scores_gemma":[0.98834026,0.000083507235,0.0094132405,0.000021218333,0.000012650957,0.000023152923,0.000053455733,0.000030100442,0.0020224801],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994935,0.00011659023,0.000027028185,0.00010160185,0.00012317226,0.00013802704],"domain_scores_gemma":[0.99771833,0.0013082923,0.00028079937,0.0002526904,0.00018045196,0.0002594675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005492535,0.0005013783,0.0012484916,0.0006747906,0.0013044532,0.0014944708,0.0018941036,0.0010915353,0.0025050223],"category_scores_gemma":[0.0054201656,0.00062946574,0.0005526082,0.00067171047,0.0017924247,0.0017557081,0.0027127208,0.0007464891,0.00026203587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036119018,0.000035814686,0.0009006448,0.000053268745,0.000031882595,0.00023197461,0.00016480616,0.952221,0.0020756316,0.03731753,0.00055541727,0.0060508195],"study_design_scores_gemma":[0.000026334914,0.000019557889,0.00013937893,0.0000033361976,0.0000061461333,0.000019195817,0.000050415183,0.9862818,0.0004066639,0.012791777,0.00024890027,0.0000065392187],"about_ca_topic_score_codex":0.008524616,"about_ca_topic_score_gemma":0.007246266,"teacher_disagreement_score":0.008524616,"about_ca_system_score_codex":0.0009145153,"about_ca_system_score_gemma":0.0006342681,"threshold_uncertainty_score":0.016950011},"labels":[],"label_agreement":null},{"id":"W2093015753","doi":"10.1016/j.tcs.2009.04.023","title":"On the relative dominance of paging algorithms","year":2009,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Austrian Science Fund","keywords":"Paging; Computer science; Algorithm; Thrashing; Demand paging; Interval (graph theory); Mathematics; Virtual memory; Parallel computing; Combinatorics; Operating system; Memory management","score_opus":0.013791904763709497,"score_gpt":0.2660141089415978,"score_spread":0.2522222041778883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093015753","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13562194,0.010502571,0.7268359,0.006878623,0.00074136857,0.0002459787,0.000639456,0.0006056956,0.11792854],"genre_scores_gemma":[0.8122628,0.006994543,0.14355366,0.0019997444,0.0017893005,0.00044538148,0.0007007449,0.00084529474,0.0314086],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9893231,0.005871721,0.00034988148,0.00072464085,0.002383186,0.0013474997],"domain_scores_gemma":[0.93903404,0.051178027,0.0016632491,0.0033590642,0.0030333798,0.0017322042],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010451717,0.002203675,0.004003275,0.0028660847,0.0027096532,0.0065031294,0.004450327,0.002877304,0.012306551],"category_scores_gemma":[0.06398213,0.0013915859,0.0015930102,0.0053325747,0.0042889104,0.012630519,0.0044979397,0.005689218,0.0020894888],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010214174,0.00031396514,0.0014057831,0.00048202332,0.00010922729,0.00013598977,0.0005448136,0.103908576,0.0022831617,0.7782071,0.017497964,0.09409004],"study_design_scores_gemma":[0.00014749145,0.00025643726,0.0005286261,0.00012424585,0.00009829135,0.00027875823,0.0001610548,0.264923,0.0010526609,0.7238074,0.008580866,0.000041077998],"about_ca_topic_score_codex":0.002875619,"about_ca_topic_score_gemma":0.0022980026,"teacher_disagreement_score":0.012306551,"about_ca_system_score_codex":0.0031008008,"about_ca_system_score_gemma":0.0033954117,"threshold_uncertainty_score":0.055274606},"labels":[],"label_agreement":null},{"id":"W2093224514","doi":"10.1007/s10878-005-1778-8","title":"Robotic-Cell Scheduling: Special Polynomially Solvable Cases of the Traveling Salesman Problem on Permuted Monge Matrices","year":2005,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Travelling salesman problem; Theory of computation; Scheduling (production processes); Mathematics; Computer science; Implementation; Combinatorics; Mathematical optimization; Algorithm","score_opus":0.015425101370619199,"score_gpt":0.2412177868623189,"score_spread":0.2257926854916997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093224514","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73288107,0.00040271677,0.22011253,0.0012880684,0.00018266862,0.00022479301,0.00094631466,0.0003490915,0.043612685],"genre_scores_gemma":[0.95329934,0.000195081,0.038426377,0.00010253668,0.00009396965,0.00007746676,0.000588197,0.00009247317,0.0071245297],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989504,0.00028504623,0.00005961137,0.00021771273,0.000117465126,0.0003697426],"domain_scores_gemma":[0.9950067,0.003055759,0.0007378647,0.0005471195,0.0002748412,0.00037765157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010824931,0.0008608186,0.0014633838,0.00066906575,0.0013787453,0.0030434506,0.0015983408,0.002451781,0.008744835],"category_scores_gemma":[0.0068018795,0.0006529942,0.0011209672,0.0011574593,0.0012815825,0.0031884736,0.0011221926,0.0014361878,0.000699082],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017022077,0.0007046948,0.0033575245,0.0006132847,0.00018267351,0.0030087284,0.0006366363,0.3833822,0.008396162,0.54752076,0.018190268,0.032304823],"study_design_scores_gemma":[0.00020992888,0.00011507181,0.0005749353,0.000016225797,0.000037236343,0.00067937706,0.00033978166,0.6446012,0.0023355146,0.34875166,0.002297696,0.000041420517],"about_ca_topic_score_codex":0.002323725,"about_ca_topic_score_gemma":0.0034849623,"teacher_disagreement_score":0.008744835,"about_ca_system_score_codex":0.00084275915,"about_ca_system_score_gemma":0.0012107291,"threshold_uncertainty_score":0.029254377},"labels":[],"label_agreement":null},{"id":"W2093995619","doi":"10.1016/j.tcs.2005.11.023","title":"Efficient algorithms for robustness in resource allocation and scheduling problems","year":2005,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Robustness (evolution); Scheduling (production processes); Algorithm; Mathematical optimization; Distributed computing; Mathematics","score_opus":0.019938166810192462,"score_gpt":0.27476555904362915,"score_spread":0.2548273922334367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2093995619","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005909426,0.000608523,0.9905894,0.00033552325,0.00006759948,0.00006240844,0.00005997945,0.00033511425,0.0020319729],"genre_scores_gemma":[0.4742645,0.0015318985,0.51730484,0.00043403683,0.0005139383,0.0006628514,0.0004864599,0.0005280037,0.004273529],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954821,0.0023540931,0.00021389041,0.0006148936,0.00087788026,0.00045720034],"domain_scores_gemma":[0.9805982,0.016033087,0.0012537441,0.0010889333,0.0006774475,0.00034860653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0073167565,0.0025424266,0.0027958106,0.0025255603,0.0009823542,0.0030449254,0.0030234335,0.0031093939,0.004178653],"category_scores_gemma":[0.031098995,0.0012993551,0.0020647233,0.0021458177,0.0026499284,0.0040923352,0.0038043985,0.004303695,0.00074866693],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002714925,0.000084623876,0.00025991024,0.00017482479,0.000089309906,0.000041635518,0.000068225716,0.8882728,0.0010652686,0.059480026,0.0022996245,0.04789223],"study_design_scores_gemma":[0.0000418158,0.00003213423,0.000048346876,0.000014715015,0.000017098,0.000015308944,0.000010586856,0.9444652,0.0003399719,0.05449842,0.0005085358,0.000007840212],"about_ca_topic_score_codex":0.0022438124,"about_ca_topic_score_gemma":0.0013841987,"teacher_disagreement_score":0.0073167565,"about_ca_system_score_codex":0.0022665919,"about_ca_system_score_gemma":0.001748414,"threshold_uncertainty_score":0.038695157},"labels":[],"label_agreement":null},{"id":"W2094391659","doi":"10.1016/j.tcs.2013.12.023","title":"Price of asynchrony in mobile agents computing","year":2014,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Asynchrony (computer programming); Asynchronous communication; Rendezvous; Computer science; Distributed computing; Task (project management); Context (archaeology); Grid; Node (physics); Synchronization (alternating current); Distributed algorithm; Integer (computer science); Computer network; Mathematics; Spacecraft","score_opus":0.01074761978554087,"score_gpt":0.27420456160855056,"score_spread":0.26345694182300966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094391659","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30889925,0.0070883418,0.567707,0.0342268,0.0031044676,0.00017127019,0.00048121306,0.0012009011,0.077120714],"genre_scores_gemma":[0.97176987,0.0007208237,0.019215517,0.00054775,0.0007507922,0.00009752568,0.000047669582,0.0001825808,0.006667379],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963708,0.0014752891,0.00020017973,0.0005766452,0.0009169289,0.00046023296],"domain_scores_gemma":[0.957598,0.03204528,0.0020376947,0.004710835,0.0019369897,0.0016712871],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005337352,0.0005762818,0.0016759551,0.00083237083,0.0018240876,0.0042212023,0.0022635292,0.0031597205,0.012663185],"category_scores_gemma":[0.05128165,0.0008997383,0.0005488707,0.0010983925,0.0025986603,0.012275859,0.0035162303,0.005123039,0.0011917572],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014651822,0.00023698247,0.0024507064,0.00041605922,0.00010199791,0.0006367281,0.00060182816,0.14107099,0.0052212197,0.78512335,0.012084855,0.050590105],"study_design_scores_gemma":[0.00027605376,0.00021718591,0.00069825817,0.000051569914,0.00007251553,0.00029946183,0.00022531206,0.44723997,0.001339731,0.54213417,0.0074007367,0.00004506312],"about_ca_topic_score_codex":0.0010064547,"about_ca_topic_score_gemma":0.001246195,"teacher_disagreement_score":0.012663185,"about_ca_system_score_codex":0.0016190637,"about_ca_system_score_gemma":0.0015938574,"threshold_uncertainty_score":0.04236257},"labels":[],"label_agreement":null},{"id":"W2094695631","doi":"10.3166/jesa.38.1097-1119","title":"Optimisation par colonies de fourmis d'un site de génération d'énergie","year":2004,"lang":"fr","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Biology; Physics","score_opus":0.029775887218448163,"score_gpt":0.27065585013503735,"score_spread":0.2408799629165892,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094695631","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.498077,0.0006176283,0.4801053,0.0012284515,0.00043295178,0.00030564232,0.00023900042,0.0009962005,0.01799767],"genre_scores_gemma":[0.8477401,0.000186134,0.13311453,0.00012001953,0.000060996044,0.0003943724,0.00021727427,0.00027037074,0.017896146],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938405,0.00027252248,0.000021456493,0.00009870777,0.000121503675,0.00010169745],"domain_scores_gemma":[0.99776113,0.0014776689,0.00013733862,0.00012177708,0.00036629988,0.000135663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013966697,0.0013711655,0.0016814276,0.0011501361,0.0011140524,0.0019729543,0.0013837235,0.0031197413,0.0057042306],"category_scores_gemma":[0.004783546,0.0009075392,0.0015109429,0.00083544245,0.001213729,0.0009585237,0.0010298092,0.0015023671,0.0007087407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017596419,0.000052272957,0.0004648238,0.000029752948,0.000040396797,0.00006509279,0.000049265615,0.9832395,0.0011839686,0.0020897938,0.00048993283,0.012119254],"study_design_scores_gemma":[0.000060131468,0.000098319935,0.00044799995,0.000009142563,0.000015157636,0.00001808414,0.00003967578,0.9961506,0.001012494,0.0015350336,0.0006037266,0.000009576281],"about_ca_topic_score_codex":0.017631855,"about_ca_topic_score_gemma":0.01051926,"teacher_disagreement_score":0.017631855,"about_ca_system_score_codex":0.0023863032,"about_ca_system_score_gemma":0.001114728,"threshold_uncertainty_score":0.03505844},"labels":[],"label_agreement":null},{"id":"W2095553101","doi":"10.1016/j.orl.2006.03.014","title":"A list heuristic for vertex cover","year":2006,"lang":"en","type":"article","venue":"Operations Research Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Combinatorics; Vertex cover; Vertex (graph theory); Heuristic; Cover (algebra); Sequence (biology); Degree (music); Mathematics; Approximation algorithm; Order (exchange); Discrete mathematics; Mathematical optimization; Graph; Physics","score_opus":0.051379162552689324,"score_gpt":0.35267193164324034,"score_spread":0.301292769090551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095553101","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052364152,0.0027223048,0.90973556,0.00135714,0.00065480894,0.0007036997,0.0013225462,0.003519027,0.027620686],"genre_scores_gemma":[0.22995658,0.0010793826,0.7447876,0.00046048954,0.00030373925,0.0005576915,0.0018807136,0.00067416613,0.020299604],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902725,0.00031216396,0.000036278274,0.00011964476,0.00029287834,0.00021181011],"domain_scores_gemma":[0.99788946,0.0013270671,0.00010516828,0.00024461455,0.000279141,0.00015446328],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009233596,0.0012325088,0.0016615749,0.0030492365,0.0018069673,0.0024111175,0.002929427,0.0020849174,0.018960547],"category_scores_gemma":[0.004444561,0.0008601676,0.0013063865,0.0039254534,0.0008960479,0.002985817,0.0016665419,0.0015570942,0.0034658287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00093721366,0.00058836414,0.00073194655,0.0006792611,0.00013496984,0.00027587963,0.00023234852,0.42485407,0.0050342404,0.05502602,0.039039966,0.4724658],"study_design_scores_gemma":[0.00022615315,0.00029120003,0.00030046693,0.00008739643,0.00009286583,0.00013000985,0.000097529475,0.9364215,0.002673084,0.04787636,0.011754163,0.000049277744],"about_ca_topic_score_codex":0.00689727,"about_ca_topic_score_gemma":0.009010439,"teacher_disagreement_score":0.018960547,"about_ca_system_score_codex":0.0026856612,"about_ca_system_score_gemma":0.0026603155,"threshold_uncertainty_score":0.063429296},"labels":[],"label_agreement":null},{"id":"W2095682406","doi":"10.1109/tnsm.2009.03.090304","title":"Distributed adaptive diverse routing for voice-over-IP in service overlay networks","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Computer network; Overlay network; Voice over IP; Scalability; Overlay; Quality of service; Routing (electronic design automation); Node (physics); Distributed computing; Learning automata; Path (computing); Automaton; The Internet","score_opus":0.020859724117424518,"score_gpt":0.24558526346121773,"score_spread":0.22472553934379322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095682406","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048605844,0.00018068151,0.94994,0.000125983,0.000018829385,0.000034064997,0.00002331865,0.00021526846,0.0008559791],"genre_scores_gemma":[0.88200563,0.00013674572,0.11703246,0.000039216135,0.000024588993,0.00007733298,0.000047315098,0.000018818833,0.00061795244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954826,0.00014233631,0.000026130432,0.000110444744,0.0001230671,0.000049720948],"domain_scores_gemma":[0.9987112,0.0007240084,0.00015690921,0.00016980678,0.00015636621,0.00008171759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000808325,0.00036719025,0.0006047241,0.00043998973,0.00062181434,0.00057938497,0.0012188851,0.00063410215,0.0005930346],"category_scores_gemma":[0.0031891416,0.00022348754,0.0004061814,0.00036591236,0.0007723567,0.0010759179,0.0011149351,0.0006059642,0.00010291481],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000084755,0.000063556945,0.0010408597,0.000056178684,0.000035430203,0.000106552616,0.000098332705,0.89478,0.008862512,0.03072431,0.0005539014,0.06359361],"study_design_scores_gemma":[0.000005852016,0.000025580941,0.00006859729,0.0000012810601,0.000004050845,0.000019156518,0.000008549964,0.99204093,0.000557583,0.006992411,0.00027210847,0.0000038808635],"about_ca_topic_score_codex":0.0009963352,"about_ca_topic_score_gemma":0.00135584,"teacher_disagreement_score":0.0012188851,"about_ca_system_score_codex":0.000685873,"about_ca_system_score_gemma":0.00040957937,"threshold_uncertainty_score":0.004976392},"labels":[],"label_agreement":null},{"id":"W2096909102","doi":"10.1109/icnp.2008.4697038","title":"Competitive analysis of buffer policies with SLA commitments","year":2008,"lang":"en","type":"article","venue":"Proceedings/Proceedings - International Conference on Network Protocols","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Network packet; Computer science; Competitive analysis; Computer network; Revenue; Abstraction; Bandwidth (computing); Task (project management); Online algorithm; Algorithm; Upper and lower bounds; Business; Engineering","score_opus":0.07694593558326353,"score_gpt":0.3318369077999769,"score_spread":0.25489097221671336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2096909102","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18506731,0.0016084147,0.74873644,0.0037480863,0.00028061913,0.00046461707,0.0005835189,0.0007028198,0.05880815],"genre_scores_gemma":[0.9530471,0.0007579427,0.03721345,0.0004477668,0.00024179777,0.00033990215,0.00022754994,0.00019550293,0.007529091],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9949945,0.0021499677,0.00013624533,0.00055300957,0.0009269879,0.001239203],"domain_scores_gemma":[0.96642345,0.026295261,0.0022217922,0.0012042356,0.0018314908,0.0020238487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067869937,0.0020469227,0.0026453552,0.0015095464,0.0018871535,0.005429757,0.0035699068,0.0028853458,0.011169491],"category_scores_gemma":[0.03579971,0.0010411612,0.0011692,0.0018451209,0.0029955946,0.005983707,0.0030151987,0.0032273694,0.0008092067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00055133464,0.00024089038,0.0009959674,0.00020098506,0.0000807208,0.00013748945,0.00017974123,0.68348163,0.0012243717,0.29567012,0.0042235767,0.013013199],"study_design_scores_gemma":[0.00004472556,0.000057056604,0.00009902946,0.000011166216,0.000012497961,0.000023950393,0.00004375103,0.9402535,0.0002120719,0.05854815,0.0006822809,0.000011785227],"about_ca_topic_score_codex":0.0065673226,"about_ca_topic_score_gemma":0.0034255176,"teacher_disagreement_score":0.011169491,"about_ca_system_score_codex":0.0056830714,"about_ca_system_score_gemma":0.0045675403,"threshold_uncertainty_score":0.04123372},"labels":[],"label_agreement":null},{"id":"W2097621701","doi":"10.1109/tsmcb.2007.913602","title":"A Solution to the Stochastic Point Location Problem in Metalevel Nonstationary Environments","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Oracle; Point (geometry); Computer science; Rendering (computer graphics); Learning automata; Discretization; Space (punctuation); Point location; Interval (graph theory); Automaton; Mathematical optimization; Theoretical computer science; Artificial intelligence; Mathematics; Combinatorics; Geometry; Mathematical analysis","score_opus":0.029084022566893915,"score_gpt":0.23439888387207194,"score_spread":0.20531486130517804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2097621701","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011470649,0.00013614849,0.9844885,0.0006662922,0.000077961624,0.000026989903,0.00009903851,0.00019006664,0.002844364],"genre_scores_gemma":[0.49655426,0.00067919533,0.48463458,0.00057921093,0.0004019947,0.00029722895,0.00065704336,0.0002614338,0.01593514],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99869007,0.0003623777,0.00005789976,0.0003751214,0.000309184,0.00020537604],"domain_scores_gemma":[0.99591845,0.0025745363,0.00042394575,0.00036722334,0.00046162412,0.000254265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015783875,0.0008506252,0.0014342094,0.0006642716,0.0011316432,0.0013740859,0.0029922214,0.0034185636,0.004906509],"category_scores_gemma":[0.01051203,0.0007406496,0.0013694188,0.00087253464,0.0020544317,0.0026647612,0.0044892393,0.0030984918,0.0008246664],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019384218,0.000057115078,0.0012184683,0.00018224069,0.00007546168,0.00040584477,0.00033230826,0.68889874,0.0015049705,0.26787826,0.005762557,0.033490106],"study_design_scores_gemma":[0.00004015761,0.000054838827,0.00019480078,0.000019280737,0.000012929989,0.0000994465,0.000057323563,0.87167275,0.00043842636,0.124729946,0.0026542624,0.00002585459],"about_ca_topic_score_codex":0.0040239226,"about_ca_topic_score_gemma":0.002937205,"teacher_disagreement_score":0.004906509,"about_ca_system_score_codex":0.0010162687,"about_ca_system_score_gemma":0.0016317841,"threshold_uncertainty_score":0.016413867},"labels":[],"label_agreement":null},{"id":"W2099745962","doi":"10.1016/j.tcs.2011.09.002","title":"Asynchronous deterministic rendezvous in bounded terrains","year":2011,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Rendezvous; Robot; Asynchronous communication; Computer science; Terrain; Bounded function; Mobile robot; Polygon (computer graphics); A priori and a posteriori; Trajectory; Algorithm; Motion planning; Mathematical optimization; Mathematics; Artificial intelligence; Spacecraft; Engineering; Geography","score_opus":0.027579630914106534,"score_gpt":0.2618971261887515,"score_spread":0.23431749527464496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099745962","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40429333,0.0008512723,0.57606596,0.00064562564,0.00014169143,0.00006515864,0.00038314197,0.0008287318,0.016725142],"genre_scores_gemma":[0.97557175,0.00019942754,0.01936144,0.000041353233,0.000023529441,0.000041120104,0.00015604851,0.00008410024,0.0045213406],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99929273,0.00015981295,0.00003211294,0.0001554145,0.00017108154,0.00018878089],"domain_scores_gemma":[0.996933,0.0019832917,0.00026405498,0.00040500885,0.00017114957,0.00024352975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005803126,0.00050253735,0.001386089,0.0007189709,0.00120064,0.001385466,0.0015992244,0.0010447591,0.0043329704],"category_scores_gemma":[0.0054562385,0.00065510574,0.00048601098,0.0009380526,0.0015455539,0.0023391764,0.0030820828,0.0010628945,0.00049715873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005399718,0.000043955868,0.00086214737,0.00011306745,0.00003695226,0.00025077982,0.00019814304,0.86201805,0.004388732,0.11709571,0.0014437714,0.013008686],"study_design_scores_gemma":[0.000043706725,0.000023297893,0.0001777342,0.000005726015,0.000008589554,0.000036742116,0.00006254189,0.95351636,0.00067651836,0.044742893,0.00069630425,0.000009607367],"about_ca_topic_score_codex":0.005784438,"about_ca_topic_score_gemma":0.005980021,"teacher_disagreement_score":0.005784438,"about_ca_system_score_codex":0.0009901663,"about_ca_system_score_gemma":0.00056688057,"threshold_uncertainty_score":0.014495194},"labels":[],"label_agreement":null},{"id":"W2099943113","doi":"10.1287/opre.1070.0439","title":"Improved Bounds for the Symmetric Rendezvous Value on the Line","year":2007,"lang":"en","type":"article","venue":"Operations Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Rendezvous; Conjecture; Mathematics; Value (mathematics); Semidefinite programming; Line (geometry); Markov decision process; Markov chain; Combinatorics; Mathematical optimization; Quadratic equation; Applied mathematics; Discrete mathematics; Markov process; Statistics; Physics; Geometry","score_opus":0.1417237002608727,"score_gpt":0.42065610245908586,"score_spread":0.27893240219821314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2099943113","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1545997,0.0034342534,0.7920361,0.0017432721,0.000198807,0.00019052211,0.0004931624,0.00078537065,0.046518788],"genre_scores_gemma":[0.8710626,0.0013993201,0.12010561,0.00039062402,0.00016973639,0.0002509106,0.0004988987,0.00044519795,0.005677048],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952893,0.0014856512,0.00014946017,0.0008968967,0.0010755676,0.0011030982],"domain_scores_gemma":[0.96504754,0.025330082,0.002351109,0.0027112865,0.0031977398,0.0013622621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0059747538,0.0018657607,0.0022660657,0.0026599776,0.0017020028,0.0034963475,0.004060099,0.0019785403,0.012008035],"category_scores_gemma":[0.034510493,0.0007182731,0.0015771217,0.0019220327,0.0044158767,0.007764517,0.004205797,0.004865076,0.0017136786],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001179828,0.00024324941,0.0028997718,0.00051204953,0.00015965781,0.0002494286,0.00048626063,0.4586823,0.01473109,0.4705866,0.006129738,0.044140045],"study_design_scores_gemma":[0.000053611486,0.00017505874,0.0005677504,0.000115974224,0.000042025757,0.000120843346,0.00022746029,0.7730532,0.0071820673,0.21613768,0.0022519056,0.00007241752],"about_ca_topic_score_codex":0.0022194034,"about_ca_topic_score_gemma":0.002053082,"teacher_disagreement_score":0.012008035,"about_ca_system_score_codex":0.003520321,"about_ca_system_score_gemma":0.0019665435,"threshold_uncertainty_score":0.040170908},"labels":[],"label_agreement":null},{"id":"W2100580556","doi":"10.1137/1.9781611973075.3","title":"How to meet asynchronously (almost) everywhere","year":2010,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA); Université du Québec en Outaouais","keywords":"Computer science","score_opus":0.010235277045089258,"score_gpt":0.23684898590267645,"score_spread":0.2266137088575872,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100580556","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.082072355,0.0001256164,0.9061904,0.00087169616,0.00006340318,0.00015869181,0.00024068888,0.0020847286,0.00819248],"genre_scores_gemma":[0.6017067,0.00016015314,0.38865504,0.00017164499,0.00002748573,0.00023046904,0.00067075365,0.0003368019,0.0080409385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982249,0.00037913985,0.00014556073,0.00058642577,0.00038677885,0.00027723043],"domain_scores_gemma":[0.995116,0.0020530755,0.0004175211,0.0016528318,0.00048951805,0.00027098253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012397275,0.0008345871,0.00085235754,0.00035452828,0.0015497303,0.001915466,0.0022347537,0.0014488016,0.004196511],"category_scores_gemma":[0.008173278,0.0006468386,0.00085474213,0.0004970557,0.0016185312,0.0036623687,0.0024326073,0.0012405165,0.0017695416],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012702699,0.00018197892,0.005639047,0.00047957976,0.00017911146,0.00046778776,0.0018903478,0.46056068,0.02413516,0.29966283,0.011606219,0.19392706],"study_design_scores_gemma":[0.00017994404,0.00017966214,0.0006328584,0.000044497578,0.00007171488,0.00036512502,0.0006348133,0.7708567,0.022168182,0.18563905,0.019154528,0.00007296277],"about_ca_topic_score_codex":0.004558671,"about_ca_topic_score_gemma":0.004727483,"teacher_disagreement_score":0.004558671,"about_ca_system_score_codex":0.00092518074,"about_ca_system_score_gemma":0.0016299302,"threshold_uncertainty_score":0.014038801},"labels":[],"label_agreement":null},{"id":"W2101083305","doi":"10.1007/s10951-008-0078-4","title":"Minimizing the stretch when scheduling flows of divisible requests","year":2008,"lang":"en","type":"article","venue":"Journal of Scheduling","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Google (Canada)","funders":"","keywords":"Heuristics; Computer science; Preemption; Scheduling (production processes); Mathematical optimization; Pareto principle; Linear programming; Algorithm; Mathematics","score_opus":0.04646876579966042,"score_gpt":0.27423315951744676,"score_spread":0.22776439371778634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101083305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7716791,0.0007650712,0.21830839,0.00079133303,0.00025569453,0.00024322663,0.00021112036,0.0004747697,0.0072712605],"genre_scores_gemma":[0.9632283,0.0001757289,0.03358136,0.00006130375,0.000073542746,0.000047335732,0.00009474557,0.000103804705,0.0026338806],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992513,0.00021224833,0.00003961214,0.00011004664,0.00017795476,0.00020869862],"domain_scores_gemma":[0.9972397,0.0017007133,0.00030923294,0.00017172549,0.00018299166,0.0003957342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016612429,0.0008588777,0.0012916175,0.0007638558,0.0012017516,0.001601209,0.001097366,0.0009234678,0.002544028],"category_scores_gemma":[0.0063773366,0.00069271465,0.00042722237,0.0011160877,0.0006512282,0.0022530218,0.0013683517,0.0010250127,0.00013869497],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022587625,0.0002668034,0.0031753294,0.000265498,0.00006851751,0.00035772484,0.00033930683,0.87568253,0.015023218,0.0101910075,0.002082861,0.09028838],"study_design_scores_gemma":[0.000040299878,0.00027760625,0.0007992674,0.000013779902,0.000018389583,0.00005990885,0.00017021922,0.98559326,0.0029127952,0.00949055,0.0006116405,0.000012258647],"about_ca_topic_score_codex":0.0027804677,"about_ca_topic_score_gemma":0.0036904993,"teacher_disagreement_score":0.0027804677,"about_ca_system_score_codex":0.0015115105,"about_ca_system_score_gemma":0.0009849656,"threshold_uncertainty_score":0.010966837},"labels":[],"label_agreement":null},{"id":"W2101179918","doi":"10.1109/hpcsa.2002.1019137","title":"The characterization of parallel real-time optimization problems","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Class (philosophy); Computer science; Bounded function; Matroid; Optimization problem; Independence (probability theory); Characterization (materials science); Property (philosophy); Mathematical optimization; Tree (set theory); Parallel algorithm; Algorithm; Mathematics; Discrete mathematics; Combinatorics; Artificial intelligence","score_opus":0.014041623754439082,"score_gpt":0.2281642024924671,"score_spread":0.21412257873802804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101179918","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08299629,0.0009384207,0.8920207,0.0020539984,0.00007396972,0.00014382257,0.00034648005,0.0004223836,0.021004021],"genre_scores_gemma":[0.79671943,0.0013543807,0.18708931,0.0005184042,0.0005172052,0.0005355494,0.0010929122,0.0003480765,0.01182461],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983758,0.00035532718,0.000089478446,0.00047395052,0.00046554673,0.00023985695],"domain_scores_gemma":[0.99322766,0.0038832487,0.0012286163,0.0007673395,0.000588247,0.0003049016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018044182,0.0010639081,0.0012133498,0.0008191972,0.0007439524,0.0021205614,0.0015047444,0.0011695888,0.0043031946],"category_scores_gemma":[0.008537943,0.0005449581,0.00092854677,0.0014719014,0.0017051038,0.0046963547,0.0017538636,0.002846088,0.00059242756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003178876,0.0002566198,0.0016115775,0.0003474078,0.00008309756,0.00031998326,0.00022249496,0.5746869,0.0073726564,0.36086407,0.0051396084,0.04877771],"study_design_scores_gemma":[0.000024366691,0.000038108417,0.00033177392,0.000011347083,0.000012133423,0.0001246971,0.000043140386,0.7684829,0.0018976909,0.22523831,0.0037865443,0.000009013029],"about_ca_topic_score_codex":0.000946282,"about_ca_topic_score_gemma":0.00073537655,"teacher_disagreement_score":0.0043031946,"about_ca_system_score_codex":0.0012727566,"about_ca_system_score_gemma":0.00093033374,"threshold_uncertainty_score":0.014395595},"labels":[],"label_agreement":null},{"id":"W2101721652","doi":"10.1109/ipdps.2005.23","title":"A Fixed-Structure Learning Automaton Solution to the Stochastic Static Mapping Problem","year":2005,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Automaton; Focus (optics); Heuristic; Theoretical computer science; Set (abstract data type); Learning automata; Mathematical optimization; Algorithm; Artificial intelligence; Mathematics; Programming language","score_opus":0.013602729269242195,"score_gpt":0.24385453666194873,"score_spread":0.23025180739270654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101721652","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032925185,0.00012726472,0.961169,0.000268556,0.000052629945,0.000056546567,0.000053573425,0.0004681386,0.0048790565],"genre_scores_gemma":[0.7171815,0.00015348123,0.27728698,0.00013696794,0.000041849653,0.0002476705,0.00016271023,0.000071546805,0.004717379],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99964285,0.00010589368,0.000016993348,0.00009273617,0.00008099778,0.00006044929],"domain_scores_gemma":[0.99914205,0.00046182802,0.00007997709,0.00010578998,0.00014507236,0.000065275024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005259459,0.0003754345,0.00062461966,0.0003122459,0.00047211442,0.0005800115,0.001248707,0.0011002708,0.0029483458],"category_scores_gemma":[0.002875384,0.00023153581,0.00052548613,0.00033238652,0.0007716814,0.0006550658,0.00080619083,0.000931423,0.00047871988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000734305,0.00007331168,0.0005771769,0.000092294686,0.000029566183,0.00008330135,0.00010415816,0.8944537,0.0035311843,0.04243969,0.0015230665,0.05701917],"study_design_scores_gemma":[0.000012181347,0.000045754452,0.000059655144,0.000004402465,0.000004013095,0.000024731356,0.000012452392,0.9901247,0.0005302164,0.008392738,0.0007853405,0.0000037979278],"about_ca_topic_score_codex":0.0019594417,"about_ca_topic_score_gemma":0.0023935782,"teacher_disagreement_score":0.0029483458,"about_ca_system_score_codex":0.00056499935,"about_ca_system_score_gemma":0.0014180426,"threshold_uncertainty_score":0.009863198},"labels":[],"label_agreement":null},{"id":"W2101810678","doi":"10.1109/icde.2009.105","title":"On Efficient Recommendations for Online Exchange Markets","year":2009,"lang":"en","type":"article","venue":"Proceedings - International Conference on Data Engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Popularity; Database transaction; Focus (optics); Social network (sociolinguistics); Probabilistic logic; Value (mathematics); User modeling; World Wide Web; Class (philosophy); Recommender system; User interface; Social media; Database; Artificial intelligence; Machine learning","score_opus":0.11157168128214941,"score_gpt":0.34177713795701203,"score_spread":0.23020545667486264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2101810678","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033069395,0.0022041348,0.94506973,0.0020503907,0.0001889311,0.000961283,0.0024776224,0.0016321172,0.012346437],"genre_scores_gemma":[0.22747618,0.0020315899,0.7483399,0.0008166627,0.00034926028,0.0011405406,0.004897848,0.0003813678,0.014566654],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9947519,0.001965279,0.0003580459,0.0011334756,0.0010765656,0.00071479985],"domain_scores_gemma":[0.97673064,0.018548805,0.0009971347,0.0018675161,0.0013480932,0.0005078701],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0049201264,0.0030313449,0.005470948,0.002819482,0.0022279222,0.0042206934,0.006148966,0.005419899,0.017778274],"category_scores_gemma":[0.028098883,0.0023259304,0.002358176,0.008330872,0.0017599654,0.010088701,0.002996592,0.0048588905,0.0040117353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043818867,0.00061925146,0.001679274,0.00063381874,0.00017813109,0.0002752532,0.00038243816,0.72774875,0.000908989,0.07931943,0.02555072,0.16226573],"study_design_scores_gemma":[0.00015187937,0.00007540798,0.00021017279,0.00004996766,0.00003276181,0.00008850609,0.00013421048,0.9059875,0.0003123719,0.08908823,0.003851856,0.000017059694],"about_ca_topic_score_codex":0.012428175,"about_ca_topic_score_gemma":0.017674912,"teacher_disagreement_score":0.017778274,"about_ca_system_score_codex":0.003451732,"about_ca_system_score_gemma":0.0033053916,"threshold_uncertainty_score":0.05947429},"labels":[],"label_agreement":null},{"id":"W2102172432","doi":"10.1142/s0218195910003232","title":"GENERALIZED WATCHMAN ROUTE PROBLEM WITH DISCRETE VIEW COST","year":2010,"lang":"en","type":"article","venue":"International Journal of Computational Geometry & Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Polygon (computer graphics); Mathematics; Approximation algorithm; Combinatorics; Boundary (topology); Viewpoints; Time complexity; Mathematical optimization; Algorithm; Discrete mathematics; Computer science","score_opus":0.012058966365115536,"score_gpt":0.2997036074054154,"score_spread":0.28764464104029985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2102172432","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.083811566,0.0005227385,0.90842766,0.00049863453,0.00008201779,0.0001462676,0.0005904861,0.00052259886,0.005398057],"genre_scores_gemma":[0.4653206,0.0006560848,0.52240175,0.00020920791,0.000097965814,0.00040526743,0.0020211784,0.00031974594,0.008568166],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992841,0.00022139931,0.000032711694,0.00023584675,0.00011996669,0.000105918705],"domain_scores_gemma":[0.9989987,0.0005458712,0.00011562918,0.00018604449,0.000072720904,0.00008094975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006860593,0.0010327509,0.0013478782,0.00038448925,0.00052336074,0.0013072585,0.0020669203,0.0014849763,0.0053850682],"category_scores_gemma":[0.0019149291,0.00060894236,0.001065899,0.0009055522,0.0007589654,0.0034650255,0.001303505,0.001725198,0.00048351663],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045936918,0.00018460279,0.0010837903,0.00048745016,0.0001319951,0.0006744843,0.00023592058,0.784889,0.0061682467,0.10624196,0.008111833,0.09133134],"study_design_scores_gemma":[0.000106179745,0.00022485243,0.00043898742,0.00002457573,0.000043270717,0.00038121847,0.00014330924,0.912872,0.002097301,0.07530287,0.008334769,0.000030686046],"about_ca_topic_score_codex":0.002589149,"about_ca_topic_score_gemma":0.0030787908,"teacher_disagreement_score":0.0053850682,"about_ca_system_score_codex":0.0007509771,"about_ca_system_score_gemma":0.00080442266,"threshold_uncertainty_score":0.018014848},"labels":[],"label_agreement":null},{"id":"W2104796709","doi":"10.1109/sccc.1997.637100","title":"On the optimal search problem: the case when the target distribution is unknown","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Unobservable; Object (grammar); Computer science; Bin; Probability distribution; Mathematical optimization; Function (biology); Set (abstract data type); Probability density function; Distribution (mathematics); Algorithm; Data mining; Mathematics; Artificial intelligence; Statistics","score_opus":0.04116817572183037,"score_gpt":0.252364553691546,"score_spread":0.2111963779697156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104796709","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034623694,0.007326971,0.9380563,0.006113672,0.00018920469,0.00013477949,0.00037122003,0.00019823982,0.012985842],"genre_scores_gemma":[0.68269897,0.016355341,0.27714208,0.0018829589,0.0013685852,0.0008787508,0.0011462494,0.000551325,0.01797578],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9949256,0.002825183,0.00017686398,0.00087116467,0.00065900624,0.00054215844],"domain_scores_gemma":[0.92316467,0.07193886,0.0021066684,0.0007900195,0.0013494319,0.0006503737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008935264,0.002263608,0.0048466814,0.0024073343,0.0013910977,0.0033259257,0.002841357,0.0056596478,0.005255595],"category_scores_gemma":[0.06703082,0.0015347506,0.0013085216,0.003984436,0.006807983,0.007385281,0.0039204056,0.0037093882,0.00087532675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026666556,0.00008356179,0.0010320812,0.00036445315,0.00010467461,0.0003370927,0.0001479788,0.83861583,0.00019296614,0.13607216,0.0033170062,0.019465486],"study_design_scores_gemma":[0.000083679864,0.00006606264,0.00036735667,0.00008480703,0.000030432362,0.0001156434,0.0000727463,0.7820454,0.00014056532,0.21548775,0.0014728148,0.000032615982],"about_ca_topic_score_codex":0.010797572,"about_ca_topic_score_gemma":0.003964503,"teacher_disagreement_score":0.010797572,"about_ca_system_score_codex":0.0025735598,"about_ca_system_score_gemma":0.0024500322,"threshold_uncertainty_score":0.04725474},"labels":[],"label_agreement":null},{"id":"W2104859809","doi":"10.1007/978-3-319-08404-6_9","title":"Competitive Online Routing on Delaunay Triangulations","year":2014,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Carleton University","funders":"","keywords":"Delaunay triangulation; Constrained Delaunay triangulation; Computer science; Bowyer–Watson algorithm; Combinatorics; Competitive analysis; Pitteway triangulation; Shortest path problem; Algorithm; Graph; Mathematics; Theoretical computer science","score_opus":0.026425287501370364,"score_gpt":0.27531310677312987,"score_spread":0.24888781927175951,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104859809","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.052916184,0.0027118814,0.85501206,0.0013034833,0.00042287825,0.00027567608,0.00076016935,0.001010659,0.08558696],"genre_scores_gemma":[0.35049936,0.0037483503,0.57481647,0.0004706143,0.00057650317,0.0005639536,0.0016289392,0.00086522574,0.066830575],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9985362,0.00039595424,0.000057822366,0.00024072765,0.00056070485,0.00020856001],"domain_scores_gemma":[0.9973666,0.0014260378,0.00020580966,0.0004728936,0.00031767992,0.0002110213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093933375,0.00130769,0.001976725,0.0015888717,0.0013334462,0.0026585942,0.0038690695,0.0020385163,0.016690783],"category_scores_gemma":[0.0054821908,0.0009212989,0.001002841,0.0031843025,0.0013284184,0.0040901764,0.0034040583,0.002463499,0.003167862],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033234,0.00013801915,0.00031654543,0.0005276847,0.0000640905,0.00013513978,0.00017958302,0.27729645,0.004049012,0.50730425,0.03292138,0.17673554],"study_design_scores_gemma":[0.000060090108,0.000094199684,0.0001818193,0.00007070399,0.000024885916,0.00019590797,0.00008508616,0.645568,0.0013671397,0.3318585,0.020467207,0.000026596073],"about_ca_topic_score_codex":0.0028523214,"about_ca_topic_score_gemma":0.003820253,"teacher_disagreement_score":0.016690783,"about_ca_system_score_codex":0.0021259887,"about_ca_system_score_gemma":0.0009639206,"threshold_uncertainty_score":0.05583626},"labels":[],"label_agreement":null},{"id":"W2105159972","doi":"10.1142/s0129054114500129","title":"EFFICIENT GRID EXPLORATION WITH A STATIONARY TOKEN","year":2014,"lang":"en","type":"article","venue":"International Journal of Foundations of Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Security token; Node (physics); Computer science; Grid; Port (circuit theory); Degree (music); Traverse; Computer network; Topology (electrical circuits); Mathematics; Combinatorics; Geography; Engineering; Geometry; Physics","score_opus":0.020309873665442287,"score_gpt":0.2950705856064975,"score_spread":0.2747607119410552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105159972","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15092146,0.0004475221,0.8383511,0.00041731395,0.000058555353,0.00007441721,0.00026613937,0.0018885504,0.007574982],"genre_scores_gemma":[0.7791119,0.00015091425,0.21595539,0.00004794327,0.000012000517,0.0001268567,0.00025088756,0.00009439578,0.004249678],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963295,0.00008977954,0.00002782782,0.00006681515,0.000061906336,0.00012067674],"domain_scores_gemma":[0.9993919,0.00026240796,0.00006597442,0.00016922905,0.000049304006,0.000061097126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003780147,0.00035997166,0.00075373414,0.0002768829,0.0004991481,0.00071983784,0.0010469311,0.0005543306,0.0023083163],"category_scores_gemma":[0.0015529017,0.00031090557,0.00054968713,0.00063730206,0.00060399366,0.0013508718,0.002125305,0.00039174478,0.00052744546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008796258,0.000066784574,0.0023757836,0.00017234887,0.000046781082,0.0003500171,0.0002238114,0.8840099,0.006753909,0.027721487,0.0033899064,0.07400959],"study_design_scores_gemma":[0.000036191876,0.00004021755,0.00017562468,0.000006101249,0.000006296365,0.00006157896,0.000036973583,0.98652864,0.0012376944,0.010643818,0.001218895,0.000007885279],"about_ca_topic_score_codex":0.0034220307,"about_ca_topic_score_gemma":0.0036588449,"teacher_disagreement_score":0.0034220307,"about_ca_system_score_codex":0.0005636608,"about_ca_system_score_gemma":0.0011007913,"threshold_uncertainty_score":0.0077220798},"labels":[],"label_agreement":null},{"id":"W2105334284","doi":"10.1016/j.tcs.2014.12.007","title":"Searching on a line: A complete characterization of the optimal solution","year":2014,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Competitive analysis; Parameterized complexity; Mathematics; Position (finance); Upper and lower bounds; Mathematical optimization; Characterization (materials science); Line (geometry); Search problem; Combinatorics","score_opus":0.02262614493001695,"score_gpt":0.2660139534981598,"score_spread":0.24338780856814288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105334284","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028471222,0.0013556987,0.92038137,0.0019899476,0.00008714891,0.00013133504,0.0008527145,0.0002962262,0.0464343],"genre_scores_gemma":[0.48829454,0.0059969327,0.4581929,0.001772651,0.0008105763,0.0008918564,0.0024967662,0.001088294,0.040455464],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984756,0.00042804118,0.00010074358,0.0003959289,0.00039759412,0.00020214317],"domain_scores_gemma":[0.99677104,0.001808971,0.0003896766,0.00033921393,0.0004721986,0.00021888979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00167144,0.0018445511,0.002250502,0.0029786245,0.0013744602,0.004850482,0.002851002,0.0027926378,0.019970281],"category_scores_gemma":[0.010142162,0.001094969,0.001700176,0.0033816274,0.0028659878,0.010789605,0.0031683636,0.0042900424,0.0022564405],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000110433015,0.00009901643,0.00071729836,0.00033972628,0.000060287075,0.000088897534,0.000270072,0.09766402,0.0015459254,0.83197844,0.010111434,0.057014503],"study_design_scores_gemma":[0.000024609622,0.0001028432,0.0003090554,0.00009693424,0.000026721595,0.00013307478,0.00011910729,0.28255665,0.0005893956,0.7079807,0.008032764,0.000028095103],"about_ca_topic_score_codex":0.0015552398,"about_ca_topic_score_gemma":0.0010369794,"teacher_disagreement_score":0.019970281,"about_ca_system_score_codex":0.0012350361,"about_ca_system_score_gemma":0.0015825069,"threshold_uncertainty_score":0.06680721},"labels":[],"label_agreement":null},{"id":"W2105439786","doi":"10.1109/tsmcb.2009.2032528","title":"Solving Multiconstraint Assignment Problems Using Learning Automata","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Universitetet i Oslo","keywords":"Set (abstract data type); Computer science; Class (philosophy); Theoretical computer science; Constraint (computer-aided design); Automaton; Artificial intelligence; Algorithm; Information retrieval; Mathematics; Programming language","score_opus":0.03392984717873745,"score_gpt":0.25925422343491816,"score_spread":0.2253243762561807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105439786","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025147267,0.0002463828,0.97166294,0.00029199896,0.0000401911,0.00007925959,0.00005229953,0.00060236274,0.0018771571],"genre_scores_gemma":[0.5711128,0.00038037924,0.42396474,0.00023800835,0.00008730007,0.00039531628,0.00033744544,0.00014776387,0.0033363167],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986663,0.00040088096,0.00011463005,0.00045092657,0.00020178805,0.00016549222],"domain_scores_gemma":[0.9948548,0.004085327,0.00028669866,0.00034728704,0.0002789335,0.00014697433],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014909245,0.0012251355,0.001427186,0.0008090317,0.0010125244,0.0016287062,0.002383002,0.002049378,0.0024818256],"category_scores_gemma":[0.0063094804,0.0007109102,0.0014470911,0.0010506394,0.0016168846,0.0024971804,0.0020847516,0.0023008764,0.00035752938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004689724,0.000077017416,0.00082276535,0.00010544827,0.00004899275,0.00006647654,0.00013440955,0.9335958,0.00087346736,0.019687587,0.0005153248,0.04402575],"study_design_scores_gemma":[0.000010364343,0.000018440423,0.000044220546,0.00000556321,0.0000064227556,0.000013484022,0.000020653537,0.98326206,0.0004258608,0.0157747,0.0004130867,0.0000051211555],"about_ca_topic_score_codex":0.0071313344,"about_ca_topic_score_gemma":0.007159012,"teacher_disagreement_score":0.0071313344,"about_ca_system_score_codex":0.0014215478,"about_ca_system_score_gemma":0.0020599714,"threshold_uncertainty_score":0.014179647},"labels":[],"label_agreement":null},{"id":"W2105687001","doi":"10.1007/978-3-642-13731-0_1","title":"Optimal Exploration of Terrains with Obstacles","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Terrain; Computer science; Point (geometry); Artificial intelligence; Computer vision; Mobile robot; Robot; Convex hull; Trajectory; Regular polygon; Algorithm; Mathematics; Geography; Geometry; Cartography","score_opus":0.02995620708004124,"score_gpt":0.2577156093518895,"score_spread":0.22775940227184824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105687001","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.098464765,0.004655363,0.8507987,0.00043975387,0.00014976304,0.000050057813,0.00034444037,0.00049233047,0.044604886],"genre_scores_gemma":[0.70285386,0.0035546515,0.2703494,0.000090329486,0.000106267595,0.00010561091,0.00058244256,0.00029429255,0.022063162],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99987197,0.00002476216,0.0000051821858,0.000020663216,0.00005319281,0.000024269326],"domain_scores_gemma":[0.99985564,0.00009094519,0.000010282964,0.000014914255,0.000014603558,0.000013568815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001511892,0.0005766994,0.0007535891,0.00044780306,0.00029555953,0.00072820066,0.000771581,0.00060063426,0.0028094212],"category_scores_gemma":[0.0009021874,0.00043123995,0.0004721417,0.00066424,0.0005166006,0.0010018784,0.0012166835,0.000619456,0.00033458945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016018105,0.000042362997,0.00036644383,0.00026418007,0.00004141798,0.00011448563,0.00013220629,0.8325943,0.006728562,0.0509998,0.00509284,0.103463255],"study_design_scores_gemma":[0.000027170086,0.000047907015,0.00021725366,0.000035068548,0.000009998729,0.00010052871,0.000041831932,0.92699414,0.0014544098,0.06551694,0.0055421744,0.000012575829],"about_ca_topic_score_codex":0.0015392262,"about_ca_topic_score_gemma":0.0017953311,"teacher_disagreement_score":0.0028094212,"about_ca_system_score_codex":0.0002776048,"about_ca_system_score_gemma":0.00039205674,"threshold_uncertainty_score":0.00939852},"labels":[],"label_agreement":null},{"id":"W2105783854","doi":"10.1007/s00446-015-0248-5","title":"Getting close without touching: near-gathering for autonomous mobile robots","year":2015,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Mobile robot; Robot; Computer science; Human–computer interaction; Artificial intelligence","score_opus":0.03433678672213519,"score_gpt":0.29931038085304124,"score_spread":0.26497359413090604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105783854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1158875,0.00077403325,0.87533534,0.00056019094,0.00014058924,0.000056861674,0.000051124014,0.0003699601,0.006824409],"genre_scores_gemma":[0.85670054,0.00058491935,0.13468507,0.00013339912,0.00010908964,0.00007864359,0.00010355986,0.00016756335,0.007437288],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997482,0.00006358919,0.000010554545,0.000067400986,0.000068095345,0.000042149306],"domain_scores_gemma":[0.9992908,0.00038490884,0.000067787965,0.00008529918,0.00006629784,0.00010484107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005264209,0.0006475769,0.0009599339,0.0003884214,0.0013064196,0.0009710107,0.0012579832,0.0014958419,0.0021064528],"category_scores_gemma":[0.002857773,0.00046425135,0.0005523699,0.00059598644,0.0011166955,0.002549549,0.002736126,0.0011861699,0.00041377853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005542605,0.00025495337,0.0011523431,0.00026548805,0.00006698508,0.000462468,0.0008112345,0.76184857,0.012109291,0.04209102,0.00607003,0.17431335],"study_design_scores_gemma":[0.00001533483,0.00009258155,0.00017838243,0.000008438336,0.000014089219,0.00009603282,0.00011315485,0.9614931,0.00095866265,0.036055475,0.0009626026,0.000012223416],"about_ca_topic_score_codex":0.0019941574,"about_ca_topic_score_gemma":0.0019310225,"teacher_disagreement_score":0.0021064528,"about_ca_system_score_codex":0.00032503338,"about_ca_system_score_gemma":0.0004888489,"threshold_uncertainty_score":0.0070468187},"labels":[],"label_agreement":null},{"id":"W2108234048","doi":"","title":"Route planning under uncertainty: the Canadian traveller problem","year":2008,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Heuristics; Mathematical optimization; Computer science; Disjoint sets; Enhanced Data Rates for GSM Evolution; Markov chain; Approximation algorithm; Markov decision process; Markov process; Mathematics; Artificial intelligence; Discrete mathematics; Machine learning","score_opus":0.058927334232751656,"score_gpt":0.2637952815795497,"score_spread":0.20486794734679803,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108234048","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.352759,0.0044442164,0.54862225,0.012886783,0.00030713985,0.0005255551,0.007745107,0.0022574214,0.07045259],"genre_scores_gemma":[0.8711974,0.0018687621,0.108218156,0.00051164493,0.000093836556,0.0001470264,0.0024718998,0.000231114,0.015260074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99885535,0.00028946332,0.000026167583,0.00024734356,0.00032654766,0.00025516024],"domain_scores_gemma":[0.9983687,0.0010604225,0.00010321546,0.000090690155,0.00020639559,0.00017066792],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012332909,0.0011318426,0.0013230274,0.00093099533,0.0022662394,0.0019478609,0.0020600017,0.0022952252,0.0057202387],"category_scores_gemma":[0.0055569876,0.00049493974,0.00066909887,0.0031540783,0.0018635163,0.002732905,0.001318583,0.0018545116,0.0003078138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029832884,0.0000564504,0.0011418469,0.00011228953,0.00005358437,0.00017869957,0.00013234273,0.8863415,0.00048125265,0.0608117,0.014421204,0.035970904],"study_design_scores_gemma":[0.00008359617,0.00003839606,0.0007719119,0.000016573516,0.00003108744,0.000101282654,0.00013953618,0.944605,0.000544659,0.04610265,0.007518065,0.00004724634],"about_ca_topic_score_codex":0.5760457,"about_ca_topic_score_gemma":0.57768255,"teacher_disagreement_score":0.4239543,"about_ca_system_score_codex":0.010205537,"about_ca_system_score_gemma":0.01452419,"threshold_uncertainty_score":0.8529021},"labels":[],"label_agreement":null},{"id":"W2108540055","doi":"10.1109/3477.931507","title":"Continuous and discretized pursuit learning schemes: various algorithms and their comparison","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":140,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nortel (Canada); Carleton University","funders":"Indian Institute of Science","keywords":"Learning automata; Discretization; Computer science; Action (physics); Algorithm; Artificial intelligence; Automaton; Reinforcement learning; Class (philosophy); Machine learning; Mathematics","score_opus":0.022965798842747593,"score_gpt":0.25349352982921325,"score_spread":0.23052773098646565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108540055","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016125366,0.003463638,0.9741823,0.0003718153,0.000105898456,0.00007653921,0.000049971106,0.00031468883,0.005309787],"genre_scores_gemma":[0.44622025,0.0042960052,0.5445971,0.00022857926,0.00025050517,0.00031512935,0.00017010908,0.00014005901,0.003782306],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99797136,0.00067094195,0.0001704039,0.0002738887,0.00080698525,0.00010647375],"domain_scores_gemma":[0.9941103,0.0037892219,0.00040505032,0.00077711866,0.0006941427,0.00022419501],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027455194,0.0006506959,0.00095619546,0.0014241223,0.00046414422,0.0020922448,0.0019575283,0.0019866289,0.0024223272],"category_scores_gemma":[0.01335633,0.00034551116,0.0006156552,0.0017383322,0.0021797877,0.0035241968,0.0021660507,0.0018152783,0.00045279125],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043307513,0.00016221835,0.0014762714,0.00044890674,0.00009502671,0.00004356407,0.00022101327,0.31317243,0.0025016216,0.2911112,0.0018324672,0.3885022],"study_design_scores_gemma":[0.00007669522,0.00026421784,0.00042314205,0.00006706479,0.000021861159,0.000104967985,0.00005323533,0.934468,0.0016189273,0.059694383,0.0031727287,0.000034733683],"about_ca_topic_score_codex":0.0014109947,"about_ca_topic_score_gemma":0.0007697663,"teacher_disagreement_score":0.0027455194,"about_ca_system_score_codex":0.0014938285,"about_ca_system_score_gemma":0.0009679556,"threshold_uncertainty_score":0.01451987},"labels":[],"label_agreement":null},{"id":"W2108990830","doi":"10.1016/j.ic.2010.09.005","title":"Optimality and competitiveness of exploring polygons by mobile robots","year":2010,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Polygon (computer graphics); Simple polygon; Mobile robot; Focus (optics); Robot; Trajectory; Computer science; Boundary (topology); Metric (unit); Square (algebra); Point (geometry); Convex polygon; Computer vision; Artificial intelligence; Algorithm; Mathematics; Regular polygon; Geometry; Engineering","score_opus":0.01863673248393834,"score_gpt":0.2608629734210505,"score_spread":0.24222624093711217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108990830","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7789997,0.0014196084,0.17147253,0.001700754,0.000100671685,0.00011908984,0.000585934,0.00025055496,0.045351245],"genre_scores_gemma":[0.95036215,0.00055345614,0.042743478,0.00009158396,0.00009606836,0.00011581041,0.00045110603,0.00024168934,0.005344614],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986039,0.00050965935,0.00006025301,0.00021639811,0.00027011713,0.00033975893],"domain_scores_gemma":[0.99125564,0.006370353,0.0007130066,0.00043086064,0.00041001025,0.0008200374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016941662,0.00085511734,0.0025058922,0.001524149,0.0012949586,0.003564651,0.0018373214,0.0019333648,0.007170592],"category_scores_gemma":[0.013566041,0.00086850504,0.0013695394,0.0018651063,0.0034319826,0.0036019133,0.002627467,0.0017116104,0.00061055686],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016473712,0.00024578246,0.008892687,0.00035725464,0.00011374592,0.00032013812,0.00062327116,0.537872,0.0050213602,0.4017516,0.0052507655,0.03790394],"study_design_scores_gemma":[0.00020382673,0.00031821424,0.003857065,0.00005531053,0.00007120534,0.00023006451,0.00045267385,0.59197223,0.0025901382,0.397096,0.0031151723,0.000038019116],"about_ca_topic_score_codex":0.005262135,"about_ca_topic_score_gemma":0.004626542,"teacher_disagreement_score":0.007170592,"about_ca_system_score_codex":0.001444381,"about_ca_system_score_gemma":0.0016263027,"threshold_uncertainty_score":0.023988008},"labels":[],"label_agreement":null},{"id":"W2109827459","doi":"10.5555/1496770.1496845","title":"Scalably scheduling processes with arbitrary speedup curves","year":2009,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Speedup; Computer science; Scheduling (production processes); Parallel computing; Algorithm; Mathematical optimization; Mathematics","score_opus":0.014995589229568347,"score_gpt":0.24497026472642597,"score_spread":0.22997467549685763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2109827459","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09119867,0.0004643641,0.87945294,0.0008924426,0.00019589672,0.00024580373,0.00030291433,0.0065187407,0.020728318],"genre_scores_gemma":[0.56271785,0.00052305154,0.41699153,0.00030789446,0.00022411294,0.00048160844,0.0007891838,0.0012685667,0.016696222],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999099,0.00012398083,0.00005658172,0.00019296668,0.0002859259,0.00024147647],"domain_scores_gemma":[0.997491,0.0008747263,0.0002114229,0.0008674772,0.0003615273,0.00019390287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012450004,0.0011758903,0.0010851962,0.0006106252,0.0011199254,0.0018415037,0.0023708188,0.0011427124,0.009431539],"category_scores_gemma":[0.005415631,0.0005545016,0.0006896487,0.0015256731,0.0016066227,0.003247289,0.0023411,0.0017442901,0.0025155784],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017532274,0.00030237794,0.0020960246,0.00049074047,0.0000908195,0.00029868275,0.00032808573,0.57707155,0.08052541,0.1242083,0.017243812,0.19559093],"study_design_scores_gemma":[0.00011179317,0.00009568662,0.00021739236,0.000013395778,0.000019047595,0.000027906077,0.000026382193,0.9287792,0.014907668,0.05223822,0.0035458356,0.000017474555],"about_ca_topic_score_codex":0.0034625547,"about_ca_topic_score_gemma":0.004391152,"teacher_disagreement_score":0.009431539,"about_ca_system_score_codex":0.0021181167,"about_ca_system_score_gemma":0.0019999375,"threshold_uncertainty_score":0.03155166},"labels":[],"label_agreement":null},{"id":"W2110483583","doi":"10.1287/opre.2015.1349","title":"Technical Note—Trading Off Quick versus Slow Actions in Optimal Search","year":2015,"lang":"en","type":"article","venue":"Operations Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Iterative deepening depth-first search; Set (abstract data type); Search algorithm; Order (exchange); Computer science; Beam stack search; Search engine; Search problem; Search cost; Linear search; Best-first search; Beam search; Algorithm; Information retrieval; Economics","score_opus":0.2697715929038695,"score_gpt":0.4593099383107204,"score_spread":0.18953834540685094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110483583","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02404339,0.0012018434,0.9549042,0.0014525396,0.00015350604,0.00014299838,0.00018055187,0.00039612464,0.01752489],"genre_scores_gemma":[0.67634547,0.002257982,0.30722675,0.0011811471,0.00039834285,0.0005503772,0.00026847245,0.00044938127,0.0113220895],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968606,0.0011443774,0.00018688728,0.00067717204,0.00057181565,0.0005590686],"domain_scores_gemma":[0.98908025,0.00810623,0.0008136265,0.0010060143,0.00048722493,0.00050668506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040125377,0.0015970118,0.0021290977,0.00092473,0.0011410128,0.002809981,0.0022973402,0.002329195,0.00782445],"category_scores_gemma":[0.02231405,0.0010564931,0.0015687331,0.001125734,0.0034861749,0.005189856,0.004148136,0.003519642,0.0011648013],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003481194,0.0001537271,0.0019071569,0.00032394635,0.00011013677,0.00028110694,0.00023299771,0.68829226,0.0037005646,0.26597127,0.005659178,0.0330195],"study_design_scores_gemma":[0.00007364025,0.00015474459,0.00024242271,0.00007071224,0.000036476304,0.00009790616,0.000050896335,0.8039132,0.0011042962,0.19160554,0.0026156208,0.00003457907],"about_ca_topic_score_codex":0.004493981,"about_ca_topic_score_gemma":0.0028175535,"teacher_disagreement_score":0.00782445,"about_ca_system_score_codex":0.0015050647,"about_ca_system_score_gemma":0.0029511282,"threshold_uncertainty_score":0.02617538},"labels":[],"label_agreement":null},{"id":"W2111339397","doi":"10.1007/s00453-010-9420-2","title":"Nonclairvoyant Speed Scaling for Flow and Energy","year":2010,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dell’Istruzione, dell’Università e della Ricerca; University of Pittsburgh; National Science Foundation","keywords":"Competitive analysis; Scaling; Function (biology); Theory of computation; Mathematics; Energy (signal processing); Constant (computer programming); Power function; Combinatorics; Power (physics); Flow (mathematics); Power flow; Algorithm; Mathematical analysis; Physics; Computer science; Geometry; Electric power system; Statistics; Upper and lower bounds; Thermodynamics","score_opus":0.009830635981841078,"score_gpt":0.2407282012606789,"score_spread":0.2308975652788378,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111339397","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07390863,0.0015728669,0.8780265,0.0021913345,0.00028370135,0.0003813354,0.0003177301,0.0017876958,0.041530106],"genre_scores_gemma":[0.6513857,0.0013173978,0.32791337,0.0011946125,0.0005871893,0.0008910143,0.0004916708,0.0010922194,0.015126751],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9961831,0.00096514006,0.00016255719,0.00084521086,0.0011205423,0.0007233385],"domain_scores_gemma":[0.9876853,0.0076311883,0.00089229067,0.0021335504,0.0010907106,0.00056697463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031807204,0.002526215,0.0020852983,0.0014734435,0.0014450393,0.003214198,0.0038468903,0.002350077,0.010019301],"category_scores_gemma":[0.024872286,0.0007733853,0.001326388,0.0026697018,0.0027381147,0.0071474845,0.0028115632,0.003743156,0.001922352],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007351835,0.00084017054,0.0023152633,0.00068066607,0.0001256547,0.00018174997,0.00029690602,0.41198924,0.0145224985,0.3932509,0.020993236,0.15406856],"study_design_scores_gemma":[0.00011436254,0.00024165105,0.00037679062,0.0000359369,0.000029356925,0.00019986006,0.000048804734,0.8086267,0.0074194935,0.17774566,0.0051279697,0.000033354576],"about_ca_topic_score_codex":0.0016061601,"about_ca_topic_score_gemma":0.0016126059,"teacher_disagreement_score":0.010019301,"about_ca_system_score_codex":0.003040206,"about_ca_system_score_gemma":0.0037542523,"threshold_uncertainty_score":0.033517897},"labels":[],"label_agreement":null},{"id":"W2111429343","doi":"10.1109/robot.2004.1307520","title":"Autonomous initialization of robot formations","year":2004,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Robot; Initialization; Computer science; Conductor; Mobile robot; Artificial intelligence; Software deployment; Robot kinematics; Pruning; Computer vision; Simulation; Mathematics","score_opus":0.02606091034358685,"score_gpt":0.269254351191673,"score_spread":0.24319344084808617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111429343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06137262,0.00015961149,0.9301893,0.00011772212,0.00006568245,0.00014832361,0.00006782615,0.0015298683,0.006349028],"genre_scores_gemma":[0.7477287,0.00011115641,0.2476281,0.000047399153,0.000019022442,0.0002434833,0.00019981421,0.00020164157,0.0038207378],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957854,0.00010822913,0.000015173793,0.00009471754,0.00011118852,0.00009218968],"domain_scores_gemma":[0.99915206,0.00021910193,0.00011823045,0.00023443543,0.00015228317,0.00012376402],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006144538,0.00048685647,0.0005789875,0.0005451259,0.0007987333,0.0007158168,0.0011954483,0.00061694393,0.003336593],"category_scores_gemma":[0.0030026725,0.00046985596,0.00028064544,0.00033472123,0.0009000268,0.0009635161,0.0018912274,0.0006926064,0.000904898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040256674,0.00009475642,0.0034263872,0.00012193089,0.00003812361,0.0002521169,0.00044389785,0.8286531,0.01841736,0.047644172,0.0035902923,0.0969153],"study_design_scores_gemma":[0.000064659405,0.000120905024,0.00053980306,0.000016886439,0.000010743741,0.00007373078,0.00008397207,0.97156143,0.008482056,0.012438759,0.0065893847,0.00001765717],"about_ca_topic_score_codex":0.0017763561,"about_ca_topic_score_gemma":0.0023274303,"teacher_disagreement_score":0.003336593,"about_ca_system_score_codex":0.0007434283,"about_ca_system_score_gemma":0.0009407973,"threshold_uncertainty_score":0.011161983},"labels":[],"label_agreement":null},{"id":"W2111880148","doi":"10.1007/978-3-642-22212-2_15","title":"Gathering Asynchronous Oblivious Agents with Local Vision in Regular Bipartite Graphs","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Bipartite graph; Asynchronous communication; Theoretical computer science; Distributed computing; Computer network; Graph","score_opus":0.01815095563036638,"score_gpt":0.24187740175512792,"score_spread":0.22372644612476156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111880148","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08905804,0.00019195687,0.8997406,0.00045771565,0.00005328117,0.00017662086,0.00010130979,0.0006496261,0.009570807],"genre_scores_gemma":[0.8334115,0.00024337633,0.15487708,0.00019492344,0.00007551608,0.0003498975,0.0002091379,0.00019430873,0.010444253],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99891233,0.00041750062,0.00004497986,0.00024477957,0.00018307776,0.00019730872],"domain_scores_gemma":[0.9961365,0.0024910653,0.00033101442,0.00047948657,0.00025455674,0.0003073136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013746192,0.0008796226,0.0015991826,0.0008301265,0.0013020899,0.0016899962,0.002713372,0.0017048563,0.0029319853],"category_scores_gemma":[0.006485436,0.0008817843,0.00094338186,0.001108688,0.0015883764,0.0029995465,0.0036264155,0.0017607957,0.000560938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006682009,0.00025908084,0.0007924354,0.00043914016,0.00014703939,0.00031480935,0.00062643155,0.7013865,0.009470974,0.22705051,0.005526402,0.053318467],"study_design_scores_gemma":[0.00004333394,0.000053492262,0.00007784192,0.000009817826,0.000015503103,0.000034903216,0.00005103742,0.89984965,0.00089280336,0.09844788,0.00051293225,0.000010830695],"about_ca_topic_score_codex":0.0023607968,"about_ca_topic_score_gemma":0.0028029853,"teacher_disagreement_score":0.0029319853,"about_ca_system_score_codex":0.0011044856,"about_ca_system_score_gemma":0.001052586,"threshold_uncertainty_score":0.009808481},"labels":[],"label_agreement":null},{"id":"W2114871659","doi":"10.1109/tac.2004.825639","title":"Local Control Strategies for Groups of Mobile Autonomous Agents","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Automatic Control","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":859,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Convergence (economics); Focus (optics); Control (management); Computer science; Mathematical optimization; Mobile robot; Point (geometry); Autonomous agent; Control theory (sociology); Distributed computing; Mathematics; Artificial intelligence; Economics","score_opus":0.015221881860332234,"score_gpt":0.26273411756851334,"score_spread":0.2475122357081811,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114871659","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07803018,0.0012351598,0.9059486,0.0004868086,0.00006660617,0.00007681721,0.000027420861,0.0002510959,0.013877385],"genre_scores_gemma":[0.96752745,0.00047107105,0.024234911,0.000069685055,0.000034946137,0.00017281,0.000034367487,0.000023480168,0.0074313534],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996941,0.000092860224,0.000014071099,0.00005934932,0.00009021006,0.000049464943],"domain_scores_gemma":[0.99946564,0.00025368636,0.0001014775,0.000036305963,0.000089221205,0.000053597825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057976175,0.0006856321,0.00039076977,0.00044038246,0.00039574926,0.0011116179,0.00093268044,0.00063453236,0.0016724142],"category_scores_gemma":[0.0017669887,0.00017127291,0.0002534684,0.00030597489,0.0011478683,0.0007723214,0.001121903,0.00055133214,0.00034722465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013513256,0.00008912079,0.000613572,0.00019065998,0.000055554843,0.00033491175,0.00073279295,0.6959161,0.008745503,0.21874015,0.0018738543,0.0725726],"study_design_scores_gemma":[0.00005236683,0.00015112781,0.00015125902,0.000015897615,0.000016102324,0.000040250914,0.00011733848,0.9190264,0.0010978737,0.077215806,0.002104838,0.0000108368895],"about_ca_topic_score_codex":0.0024968607,"about_ca_topic_score_gemma":0.0017430509,"teacher_disagreement_score":0.0024968607,"about_ca_system_score_codex":0.0008311805,"about_ca_system_score_gemma":0.00042437422,"threshold_uncertainty_score":0.0060307384},"labels":[],"label_agreement":null},{"id":"W2118877434","doi":"10.1007/s00453-001-0003-0","title":"Optimal Search and One-Way Trading Online Algorithms","year":2001,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":210,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Competitive analysis; Portfolio; Stochastic game; Computer science; Online algorithm; Adversary; Mathematical economics; Economics; Algorithm; Mathematics; Upper and lower bounds; Financial economics","score_opus":0.046450555433268786,"score_gpt":0.29112199498195773,"score_spread":0.24467143954868895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2118877434","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04447879,0.008897284,0.9138749,0.0029590703,0.0005389432,0.00006400551,0.00012584007,0.00028389535,0.028777191],"genre_scores_gemma":[0.75052077,0.0051523456,0.20811643,0.000517999,0.00087515055,0.0002672497,0.00025775773,0.0002554581,0.03403676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99776053,0.0012356921,0.00009092547,0.00036507976,0.00037543866,0.00017241215],"domain_scores_gemma":[0.9887399,0.009399112,0.0004860889,0.0008183814,0.0003464455,0.00021011519],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029424378,0.001292301,0.00259838,0.0008870355,0.0010409123,0.0034632275,0.0024363142,0.0037888954,0.010652943],"category_scores_gemma":[0.020979024,0.0008506743,0.0010004758,0.0024136375,0.0031975384,0.009457158,0.0024387664,0.004051353,0.0009727311],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031372203,0.00023927381,0.0007041538,0.0003138181,0.00009441823,0.000091720794,0.00012912041,0.13907824,0.00040453215,0.7740598,0.006140816,0.0784305],"study_design_scores_gemma":[0.000038684982,0.00003035643,0.00011979358,0.000019231202,0.000020500012,0.00004489116,0.000019682693,0.21875754,0.00015532364,0.7790459,0.0017382322,0.000009861984],"about_ca_topic_score_codex":0.0008752346,"about_ca_topic_score_gemma":0.00080345786,"teacher_disagreement_score":0.010652943,"about_ca_system_score_codex":0.0012289435,"about_ca_system_score_gemma":0.0010708006,"threshold_uncertainty_score":0.035637617},"labels":[],"label_agreement":null},{"id":"W2119064581","doi":"","title":"The optimal searcher path problem with a visibility criterion in discrete time and space","year":2009,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; Université Laval","funders":"","keywords":"Mathematical optimization; Path (computing); Visibility; Discretization; Motion planning; Any-angle path planning; Computer science; Grid; Object (grammar); Integer programming; Mathematics; Algorithm; Topology (electrical circuits); Artificial intelligence","score_opus":0.009406986349011976,"score_gpt":0.2568604366521286,"score_spread":0.24745345030311663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119064581","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0550581,0.00029426892,0.9418299,0.00025622372,0.000025561563,0.000038621038,0.000059887923,0.00009743397,0.002340006],"genre_scores_gemma":[0.7078067,0.00021718573,0.2878796,0.000046439538,0.000028147404,0.00011569627,0.00013459608,0.00007706357,0.0036945],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989687,0.0004913917,0.00003546543,0.00021181144,0.00017121862,0.000121389035],"domain_scores_gemma":[0.99827373,0.0012006166,0.00019928272,0.00010224929,0.00011840453,0.0001056535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015174362,0.000637102,0.0013375672,0.00047953005,0.000369401,0.0012577483,0.0012925534,0.0014043013,0.002042512],"category_scores_gemma":[0.0032376922,0.0005773462,0.0005811573,0.00094280904,0.001263587,0.0026662366,0.0012588019,0.0011497232,0.00015719236],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014225816,0.000073787785,0.00041570104,0.0000614642,0.000026666601,0.000101410806,0.000057837544,0.94630367,0.0009927055,0.03777613,0.00054218696,0.013506164],"study_design_scores_gemma":[0.000013105622,0.00002762313,0.000064595675,0.0000024910796,0.000003234774,0.000012765431,0.000009934345,0.99164623,0.0001929061,0.0077796304,0.00024404995,0.0000034445225],"about_ca_topic_score_codex":0.0051393914,"about_ca_topic_score_gemma":0.0027100025,"teacher_disagreement_score":0.0051393914,"about_ca_system_score_codex":0.0012856863,"about_ca_system_score_gemma":0.0011702792,"threshold_uncertainty_score":0.010218918},"labels":[],"label_agreement":null},{"id":"W2119251691","doi":"10.1016/j.tcs.2004.05.019","title":"Competitive online routing in geometric graphs","year":2004,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Delaunay triangulation; Combinatorics; Mathematics; Routing (electronic design automation); Shortest path problem; Convex polygon; Regular polygon; Discrete mathematics; Computer science; Graph; Geometry","score_opus":0.014311499595550056,"score_gpt":0.2694103437007924,"score_spread":0.25509884410524236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119251691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39476964,0.004316061,0.52432895,0.007510772,0.0004860477,0.00032111994,0.0009400219,0.0009803616,0.06634708],"genre_scores_gemma":[0.874919,0.0023646094,0.09159408,0.0008620986,0.00063892023,0.0002746594,0.0009897952,0.00039252182,0.027964301],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977374,0.0009186753,0.00006775976,0.00039267298,0.0004780676,0.00040547425],"domain_scores_gemma":[0.9867237,0.009349375,0.0011715927,0.0008619017,0.00077517127,0.0011182689],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021666754,0.0013988088,0.0028179823,0.001833758,0.0023093917,0.004848305,0.0046588033,0.0039970498,0.013196325],"category_scores_gemma":[0.015050785,0.0011956675,0.0010444466,0.0036844853,0.0025293892,0.009668965,0.0027029146,0.0031155813,0.0013593833],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00074007455,0.00051045883,0.0013894897,0.000589955,0.00011421954,0.00024403646,0.0004491661,0.18661301,0.0023798598,0.72292566,0.025616253,0.058427904],"study_design_scores_gemma":[0.00014622207,0.00012410534,0.00042815483,0.000033131877,0.00006016385,0.00020280645,0.00016234932,0.42148018,0.0007163447,0.5712863,0.005333217,0.000027131035],"about_ca_topic_score_codex":0.004180997,"about_ca_topic_score_gemma":0.0053660106,"teacher_disagreement_score":0.013196325,"about_ca_system_score_codex":0.0032725702,"about_ca_system_score_gemma":0.0019091434,"threshold_uncertainty_score":0.04414606},"labels":[],"label_agreement":null},{"id":"W2120954276","doi":"10.1016/j.tcs.2010.03.014","title":"Randomized priority algorithms","year":2010,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Greedy algorithm; Randomized algorithm; Job shop scheduling; Class (philosophy); Approximation algorithm; Computer science; Scheduling (production processes); Algorithm; Context (archaeology); Deterministic algorithm; Mathematical optimization; Mathematics; Schedule; Artificial intelligence","score_opus":0.010635678378934522,"score_gpt":0.2768811115611415,"score_spread":0.26624543318220695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120954276","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015830858,0.0026231129,0.91890585,0.004693432,0.002070709,0.0004357008,0.0006908613,0.0036218464,0.05112754],"genre_scores_gemma":[0.36303926,0.002325974,0.55271006,0.003399654,0.00311525,0.0010417718,0.0021484045,0.0022778576,0.06994177],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9915194,0.0030743792,0.00034514786,0.0016552638,0.0020805672,0.0013252888],"domain_scores_gemma":[0.98223627,0.008521868,0.000709632,0.005435106,0.001754953,0.0013421908],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065389983,0.0020508734,0.0031415334,0.0023684832,0.0031384157,0.0058222087,0.0060948143,0.0032591517,0.036839634],"category_scores_gemma":[0.030585067,0.0014262763,0.0020399855,0.0038099398,0.0027820438,0.009174346,0.0046308893,0.0072208038,0.00956607],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021117127,0.00084374595,0.00080889254,0.00050561543,0.00013684647,0.00007168558,0.00019397053,0.037212837,0.0022147123,0.6561523,0.08082497,0.2189227],"study_design_scores_gemma":[0.0008506495,0.0003170614,0.00026719779,0.000077320925,0.00012348285,0.00015700978,0.00006634304,0.2188505,0.0023954962,0.7470512,0.029792182,0.00005161384],"about_ca_topic_score_codex":0.0022312542,"about_ca_topic_score_gemma":0.003513271,"teacher_disagreement_score":0.036839634,"about_ca_system_score_codex":0.0040685977,"about_ca_system_score_gemma":0.007472386,"threshold_uncertainty_score":0.12324083},"labels":[],"label_agreement":null},{"id":"W2121154134","doi":"10.1142/s0218195901000559","title":"LOWER BOUNDS FOR STREETS AND GENERALIZED STREETS","year":2001,"lang":"en","type":"article","venue":"International Journal of Computational Geometry & Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Competitive analysis; Mathematics; Combinatorics; Upper and lower bounds; Matching (statistics); Metric (unit); Simple (philosophy); Online algorithm; Line (geometry); Cross-ratio; Discrete mathematics; Mathematical optimization; Statistics; Geometry; Mathematical analysis; Pure mathematics","score_opus":0.019899946799461558,"score_gpt":0.31829916885142107,"score_spread":0.2983992220519595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121154134","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12103722,0.0072297957,0.768492,0.00336731,0.00037583345,0.00044048633,0.0015835271,0.0016370689,0.09583684],"genre_scores_gemma":[0.7032943,0.005542147,0.26876014,0.001156118,0.00081118324,0.0008347903,0.0025489705,0.0010473273,0.01600512],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99523526,0.0009295824,0.00016169024,0.00069566356,0.0015951082,0.0013827009],"domain_scores_gemma":[0.97933906,0.014019997,0.0015819173,0.0018984645,0.0016886533,0.0014719034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025634654,0.0021570523,0.0021277,0.0024194599,0.0017327606,0.005326975,0.0044720275,0.002334333,0.016832717],"category_scores_gemma":[0.02047136,0.00084829296,0.0018746287,0.0037462958,0.0025097833,0.008505857,0.0043299207,0.003987073,0.0026677677],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00070457894,0.00039222627,0.0036055304,0.0009468555,0.00023115147,0.00031537193,0.00030994022,0.27039558,0.0072314865,0.57763416,0.023353498,0.11487969],"study_design_scores_gemma":[0.000082948725,0.00034475749,0.0011635888,0.00010790578,0.00011859474,0.00068624836,0.00017096709,0.636436,0.00455386,0.33171532,0.02455838,0.00006142647],"about_ca_topic_score_codex":0.003218691,"about_ca_topic_score_gemma":0.0033577988,"teacher_disagreement_score":0.016832717,"about_ca_system_score_codex":0.0030161936,"about_ca_system_score_gemma":0.001741147,"threshold_uncertainty_score":0.05631101},"labels":[],"label_agreement":null},{"id":"W2121824931","doi":"","title":"The P-Norm Push: A Simple Convex Ranking Algorithm that Concentrates at the Top of the List","year":2009,"lang":"en","type":"article","venue":"DSpace@MIT (Massachusetts Institute of Technology)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":143,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"York University; National Science Foundation","keywords":"Ranking (information retrieval); Generalization; Computer science; Norm (philosophy); Ranking SVM; Learning to rank; Regular polygon; Boosting (machine learning); Simple (philosophy); Algorithm; Mathematics; Machine learning","score_opus":0.013258734075760496,"score_gpt":0.24577319728864783,"score_spread":0.23251446321288732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2121824931","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00936603,0.00022845926,0.9861605,0.00041464868,0.00006562281,0.00009848746,0.000087604574,0.0006028924,0.0029757137],"genre_scores_gemma":[0.17920451,0.00040087785,0.8094571,0.00062804355,0.0002502097,0.00043321963,0.00050468784,0.00065236073,0.008469056],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979019,0.0008584376,0.0001221184,0.00035466976,0.0005926719,0.00017012755],"domain_scores_gemma":[0.99609405,0.0017528035,0.00041804466,0.00068525295,0.00079867325,0.00025110625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055039474,0.0016758627,0.0024048474,0.0016691533,0.00099351,0.0024442924,0.0020584038,0.0024866646,0.004430805],"category_scores_gemma":[0.011074657,0.00068392226,0.0009954832,0.001785785,0.0020650888,0.0043370705,0.0025126343,0.0022339202,0.0028043292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004990648,0.00034534972,0.0019179903,0.0005780004,0.00017943696,0.0001568539,0.00022419545,0.28845614,0.012765913,0.08974797,0.028121017,0.57700807],"study_design_scores_gemma":[0.00007192719,0.0004154274,0.00048047618,0.000048283557,0.00003634166,0.00019635234,0.000059697566,0.9114503,0.008460974,0.07040114,0.008322808,0.00005623577],"about_ca_topic_score_codex":0.00089738553,"about_ca_topic_score_gemma":0.0011995381,"teacher_disagreement_score":0.0055039474,"about_ca_system_score_codex":0.00094914925,"about_ca_system_score_gemma":0.001751938,"threshold_uncertainty_score":0.029108047},"labels":[],"label_agreement":null},{"id":"W2122684646","doi":"10.1016/j.comgeo.2011.12.005","title":"Memoryless routing in convex subdivisions: Random walks are optimal","year":2011,"lang":"en","type":"article","venue":"Computational Geometry","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Carleton University","funders":"","keywords":"Combinatorics; Neighbourhood (mathematics); Vertex (graph theory); Subdivision; Regular polygon; Mathematics; Routing (electronic design automation); Discrete mathematics; Computer science; Graph","score_opus":0.04721833308990548,"score_gpt":0.26880988363864333,"score_spread":0.22159155054873786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2122684646","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1909632,0.0033720841,0.77305955,0.0037931374,0.00031456276,0.0001252389,0.00041063098,0.00050141924,0.027460217],"genre_scores_gemma":[0.8747149,0.003048517,0.099898376,0.00089955877,0.00030162078,0.00022892524,0.0004710026,0.0006591278,0.01977788],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992312,0.00027882945,0.00004346698,0.00017211783,0.00014546422,0.00012893083],"domain_scores_gemma":[0.9916317,0.0056542754,0.000868331,0.00079634745,0.00050521165,0.0005441302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014175349,0.0010948688,0.0019773515,0.0013841755,0.0012219168,0.002944705,0.0020261335,0.003376115,0.006784403],"category_scores_gemma":[0.017104123,0.00141923,0.0010756719,0.0015547475,0.0027385382,0.0065388745,0.0020494363,0.002798347,0.00073799136],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002119694,0.00010366142,0.0007235529,0.0001949055,0.000052250794,0.0000527295,0.00013803692,0.32754436,0.0011356259,0.636316,0.0063555627,0.027171345],"study_design_scores_gemma":[0.000026819482,0.00003497456,0.00015662092,0.00003433645,0.000017878921,0.00003109646,0.000039364568,0.46116307,0.00034271757,0.53716964,0.00096993026,0.000013558349],"about_ca_topic_score_codex":0.002575977,"about_ca_topic_score_gemma":0.00339496,"teacher_disagreement_score":0.006784403,"about_ca_system_score_codex":0.0014191186,"about_ca_system_score_gemma":0.0012905797,"threshold_uncertainty_score":0.022696137},"labels":[],"label_agreement":null},{"id":"W2123976299","doi":"10.1109/focs.2009.51","title":"On Allocating Goods to Maximize Fairness","year":2009,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":122,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Set (abstract data type); Logarithm; Approximation algorithm; Combinatorics; Computer science; Binary logarithm; Polynomial; Time complexity; Discrete mathematics; Mathematics; Algorithm","score_opus":0.020456454354735594,"score_gpt":0.28159667870495475,"score_spread":0.26114022435021916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2123976299","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042220328,0.0017978752,0.9362319,0.0029493556,0.00024187622,0.00021032474,0.0004650314,0.0008775679,0.015005623],"genre_scores_gemma":[0.45177484,0.0016213839,0.52723724,0.0010602452,0.0005838897,0.00043392574,0.0005690104,0.0005831663,0.016136345],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99440974,0.0024794368,0.00019968516,0.0012649698,0.0006078686,0.0010383388],"domain_scores_gemma":[0.9924912,0.0052575353,0.0005165863,0.0009903745,0.0003273345,0.0004170191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0066268337,0.0025855051,0.0034485648,0.0013764171,0.0028674204,0.005136445,0.0039176545,0.0036390265,0.007775509],"category_scores_gemma":[0.019254899,0.0012025423,0.0016687631,0.0036666775,0.0036682524,0.010129169,0.0038177336,0.003597776,0.0017741371],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017588667,0.00036242325,0.0016465624,0.00048620562,0.00014540447,0.00017444276,0.00066018384,0.52206576,0.0019854014,0.37777168,0.012702346,0.080240786],"study_design_scores_gemma":[0.00014557531,0.000090357345,0.00023833843,0.000058913116,0.000042704385,0.000114618284,0.00014649882,0.5534007,0.0011942771,0.43818676,0.0063484344,0.00003275852],"about_ca_topic_score_codex":0.006600243,"about_ca_topic_score_gemma":0.005125866,"teacher_disagreement_score":0.007775509,"about_ca_system_score_codex":0.0050107623,"about_ca_system_score_gemma":0.0044060578,"threshold_uncertainty_score":0.036355853},"labels":[],"label_agreement":null},{"id":"W2124402683","doi":"10.1145/2229163.2229172","title":"Scalably scheduling processes with arbitrary speedup curves","year":2012,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"National Science Foundation","keywords":"Speedup; Scheduling (production processes); Computer science; Parallel computing; Algorithm; Mathematics; Mathematical optimization","score_opus":0.03193889738509934,"score_gpt":0.2722814381290204,"score_spread":0.24034254074392106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124402683","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09480968,0.00043314774,0.87978005,0.0010116331,0.00022466973,0.00021670517,0.0002783988,0.0061369413,0.017108705],"genre_scores_gemma":[0.58292264,0.00044623372,0.39930552,0.00032061076,0.00023196888,0.00042896447,0.000732744,0.0010816632,0.0145295905],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989819,0.00012522512,0.00006181954,0.0002228278,0.00033662908,0.00027155213],"domain_scores_gemma":[0.997471,0.00081014994,0.00020998977,0.0008796854,0.00039731836,0.00023192198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013236016,0.0011269029,0.0010177521,0.0005508893,0.0011015771,0.0017070692,0.0024262918,0.0009786311,0.007739514],"category_scores_gemma":[0.004970075,0.00054325344,0.0007108051,0.0013410227,0.0015509999,0.0030011414,0.002352634,0.0017831103,0.0022569022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00212099,0.00035941368,0.00237945,0.0005364518,0.000104869076,0.0003327027,0.00037526665,0.5211437,0.09921835,0.13944903,0.019044053,0.21493573],"study_design_scores_gemma":[0.0001339501,0.00010564632,0.00022003135,0.000011710204,0.000022787886,0.00002876681,0.00002866794,0.9260819,0.016374696,0.053563446,0.0034100402,0.000018436938],"about_ca_topic_score_codex":0.003617541,"about_ca_topic_score_gemma":0.0045636347,"teacher_disagreement_score":0.007739514,"about_ca_system_score_codex":0.0021432594,"about_ca_system_score_gemma":0.0022814253,"threshold_uncertainty_score":0.025891244},"labels":[],"label_agreement":null},{"id":"W2124571279","doi":"10.1109/icis.2007.87","title":"Decontamination of Arbitrary Networks using a Team of Mobile Agents with Limited Visibility","year":2007,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Network topology; Visibility; Computer science; Computer network; Distributed computing; Mobile computing; Mobile agent; Topology (electrical circuits); Mathematics","score_opus":0.02216368570263773,"score_gpt":0.28998584504371383,"score_spread":0.2678221593410761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124571279","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17557292,0.00033991443,0.8210315,0.00022193612,0.000032527383,0.00009915587,0.000036306723,0.00036722943,0.0022984697],"genre_scores_gemma":[0.84506357,0.00024677973,0.15204757,0.00007113175,0.000022693677,0.000094542294,0.000083260165,0.000059112524,0.0023113282],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947006,0.00017778894,0.000025515115,0.00011311898,0.00011395987,0.000099708406],"domain_scores_gemma":[0.9984627,0.000808489,0.0002664779,0.0001999714,0.0001273492,0.00013506801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097458035,0.001006836,0.0010421491,0.000609127,0.0007666456,0.0007116836,0.0012108854,0.0010914926,0.0013742901],"category_scores_gemma":[0.0032717288,0.0003897569,0.00057653344,0.00051311334,0.00078960485,0.0017865672,0.0013636359,0.00058877654,0.000223012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025362562,0.00009241233,0.0008000512,0.00014471784,0.00004868599,0.00033888273,0.00016622564,0.9282414,0.01176467,0.005401031,0.0003969374,0.0523514],"study_design_scores_gemma":[0.00003479073,0.00020559339,0.00021941224,0.000011192089,0.000024939618,0.000114372124,0.00011886799,0.987571,0.004361797,0.0062640286,0.001065574,0.000008295723],"about_ca_topic_score_codex":0.0020489157,"about_ca_topic_score_gemma":0.0019667784,"teacher_disagreement_score":0.0020489157,"about_ca_system_score_codex":0.00050481834,"about_ca_system_score_gemma":0.00065638125,"threshold_uncertainty_score":0.005154133},"labels":[],"label_agreement":null},{"id":"W2126261522","doi":"10.1145/1367497.1367719","title":"Offline matching approximation algorithms in exchange markets","year":2008,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Heuristics; Matching (statistics); Computer science; Approximation algorithm; Probabilistic logic; Algorithm; Online and offline; Online algorithm; Foreign exchange market; Artificial intelligence; Foreign exchange; Economics; Mathematics","score_opus":0.03528139091037791,"score_gpt":0.2620805598819794,"score_spread":0.22679916897160152,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126261522","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.068686984,0.001306591,0.9185687,0.0012404318,0.000092639464,0.00022877769,0.00053706655,0.001303275,0.008035529],"genre_scores_gemma":[0.57748455,0.0008551462,0.41058248,0.0004734128,0.00016443,0.000394493,0.0014659513,0.00039845286,0.00818103],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99749917,0.00093045563,0.00014023097,0.00067938754,0.00033454323,0.00041631603],"domain_scores_gemma":[0.9906309,0.0068840203,0.00070625433,0.0010275277,0.0003609446,0.000390314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003387379,0.0015089967,0.0030030792,0.001366721,0.0012630582,0.002766113,0.003906339,0.0031475988,0.008007159],"category_scores_gemma":[0.01629124,0.0009079454,0.0012678691,0.0038610685,0.0013327225,0.0077945706,0.002317913,0.0027789357,0.0011507577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005221682,0.00060602126,0.0014868288,0.00037300974,0.00014111429,0.00016075723,0.00030756785,0.7631052,0.0010554941,0.104633376,0.010357485,0.11725098],"study_design_scores_gemma":[0.00008869175,0.000043378273,0.00012840529,0.000014353298,0.00001843566,0.00004782312,0.000056368106,0.915184,0.0003289138,0.08307125,0.0010095616,0.000008755397],"about_ca_topic_score_codex":0.004789584,"about_ca_topic_score_gemma":0.0048314,"teacher_disagreement_score":0.008007159,"about_ca_system_score_codex":0.0022590775,"about_ca_system_score_gemma":0.0024160738,"threshold_uncertainty_score":0.026786625},"labels":[],"label_agreement":null},{"id":"W2127104083","doi":"10.1109/70.964662","title":"An optimal periodic scheduler for dual-arm robots in cluster tools with residency constraints","year":2001,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics and Automation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":161,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Heuristics; Schedule; Scheduling (production processes); Correctness; Distributed computing; Mathematical optimization; Time limit; Time complexity; Computational complexity theory; Parallel computing; Algorithm; Mathematics; Engineering","score_opus":0.02765532918134312,"score_gpt":0.27859192003920896,"score_spread":0.25093659085786585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127104083","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059103254,0.00030070127,0.93576133,0.000116565796,0.000053710213,0.00014131215,0.00007071273,0.00084724976,0.0036051408],"genre_scores_gemma":[0.49216223,0.00022851757,0.5050666,0.00003291244,0.000030150959,0.00019103203,0.00012290585,0.00009336738,0.0020723755],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976367,0.000045434757,0.000014514883,0.000041148,0.000072732466,0.0000625414],"domain_scores_gemma":[0.9996829,0.00012111514,0.00005843155,0.000043874115,0.00005218007,0.000041567317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005322668,0.000477791,0.00044778344,0.0005027841,0.0007092867,0.00042855926,0.0010535788,0.00038111967,0.0020150093],"category_scores_gemma":[0.0010885047,0.00039907533,0.0003241984,0.00057334796,0.00038151388,0.00042671952,0.00037970007,0.00036837586,0.00031485915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005357201,0.00015705623,0.00078440027,0.00026862175,0.000039421797,0.00024686792,0.00015883545,0.75114197,0.024008738,0.030760752,0.004399428,0.18749817],"study_design_scores_gemma":[0.00007614431,0.00016861934,0.00025207485,0.000008720347,0.00001740098,0.000056809604,0.000025213772,0.9866643,0.0046083895,0.0056468775,0.0024622981,0.00001312408],"about_ca_topic_score_codex":0.003990409,"about_ca_topic_score_gemma":0.0060541094,"teacher_disagreement_score":0.003990409,"about_ca_system_score_codex":0.00069132115,"about_ca_system_score_gemma":0.0020534885,"threshold_uncertainty_score":0.0079343915},"labels":[],"label_agreement":null},{"id":"W2127629365","doi":"10.1016/j.ic.2015.07.005","title":"Position discovery for a system of bouncing robots","year":2015,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Agence Nationale de la Recherche; Royal Society","keywords":"Robot; Position (finance); Computer science; Mobile robot; Point (geometry); Line segment; Artificial intelligence; Constant (computer programming); Task (project management); Computer vision; Line (geometry); Ring (chemistry); Algorithm; Topology (electrical circuits); Mathematics; Geometry; Combinatorics; Engineering","score_opus":0.02835690603338894,"score_gpt":0.26699115665965323,"score_spread":0.23863425062626428,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127629365","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17480731,0.00050575915,0.8159691,0.0016917319,0.00009443189,0.0001119247,0.00024914273,0.0005189256,0.0060516493],"genre_scores_gemma":[0.87807137,0.00020067435,0.113200895,0.00009549752,0.00005655823,0.0000877717,0.0002072007,0.000057969806,0.0080220895],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993845,0.0001303592,0.000052129682,0.000194658,0.00012852899,0.00010976477],"domain_scores_gemma":[0.9972523,0.0017611595,0.00029756466,0.00016349184,0.00031517245,0.0002103309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014091952,0.0007237673,0.0013700031,0.0012378573,0.0021385858,0.0021735707,0.0020139145,0.0033551578,0.0052338145],"category_scores_gemma":[0.007863876,0.0008896646,0.00081655715,0.00127352,0.0020001992,0.0024485723,0.0026502586,0.0012669234,0.00057899195],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065889,0.00008495448,0.0024449467,0.00018063986,0.00007001854,0.0002906675,0.0002608555,0.9290506,0.0027733438,0.036151882,0.0009912862,0.02704196],"study_design_scores_gemma":[0.000031921336,0.000053242456,0.0002279018,0.000007128736,0.000015171334,0.000037917325,0.000032198062,0.9888748,0.00047555196,0.00998437,0.0002463804,0.000013398069],"about_ca_topic_score_codex":0.013612907,"about_ca_topic_score_gemma":0.0076710964,"teacher_disagreement_score":0.013612907,"about_ca_system_score_codex":0.0015363552,"about_ca_system_score_gemma":0.0017060603,"threshold_uncertainty_score":0.027067304},"labels":[],"label_agreement":null},{"id":"W2128105951","doi":"10.1007/s13042-014-0272-y","title":"Solving 0–1 Knapsack Problem using Cohort Intelligence Algorithm","year":2014,"lang":"en","type":"article","venue":"International Journal of Machine Learning and Cybernetics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":110,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Knapsack problem; Computational intelligence; Cohort; Computer science; Algorithm; Artificial intelligence; Quality (philosophy); Machine learning; Mathematical optimization; Mathematics; Statistics","score_opus":0.011927809311469183,"score_gpt":0.28050205294589786,"score_spread":0.26857424363442867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128105951","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034257274,0.000337029,0.9545496,0.0003053434,0.000153618,0.00014980123,0.00012133657,0.00018385635,0.009942209],"genre_scores_gemma":[0.44551876,0.00051299715,0.54237926,0.00023737221,0.00013722606,0.0004475503,0.0006117279,0.0001130399,0.010042066],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992192,0.00025581734,0.000052720912,0.00016983546,0.00016856812,0.00013378731],"domain_scores_gemma":[0.9984798,0.0009333923,0.00013860295,0.000105362036,0.0002548482,0.000088140056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016044291,0.00081999734,0.00135916,0.000999975,0.0010249668,0.0015505222,0.0015728382,0.0015716949,0.005701013],"category_scores_gemma":[0.0040409956,0.00045008317,0.000998782,0.0013728961,0.000611655,0.0013333414,0.0015668672,0.0014464305,0.0005787097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011017415,0.00017409331,0.0013899937,0.00020473277,0.00007549927,0.000112016976,0.000080496204,0.8796325,0.0009718501,0.03308995,0.0042554135,0.07990328],"study_design_scores_gemma":[0.000014718925,0.000062372936,0.00014636753,0.000015365047,0.000009447218,0.000021270356,0.000023104569,0.9839462,0.00027556316,0.01470092,0.0007765263,0.000008250799],"about_ca_topic_score_codex":0.006876629,"about_ca_topic_score_gemma":0.0043502003,"teacher_disagreement_score":0.006876629,"about_ca_system_score_codex":0.0006012689,"about_ca_system_score_gemma":0.0016791798,"threshold_uncertainty_score":0.019071758},"labels":[],"label_agreement":null},{"id":"W2128419582","doi":"10.1613/jair.4360","title":"Optimal Scheduling of Contract Algorithms for Anytime Problem-Solving","year":2014,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; University of Waterloo","funders":"","keywords":"Computer science; Dynamic programming; Schedule; Mathematical optimization; Computation; Acceleration; Scheduling (production processes); Conjecture; Matching (statistics); Algorithm; Class (philosophy); Job shop scheduling; Mathematics; Discrete mathematics","score_opus":0.16732274216625714,"score_gpt":0.4248170278948427,"score_spread":0.25749428572858557,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128419582","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21020073,0.00032150955,0.779496,0.00044991737,0.00005131587,0.0002381341,0.000093735514,0.0004831079,0.008665527],"genre_scores_gemma":[0.6809807,0.00021181582,0.31627485,0.00009556925,0.000034423014,0.00029097247,0.00023628725,0.00014007222,0.0017353299],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9968677,0.001297665,0.00019470832,0.00047700902,0.0007162116,0.00044668364],"domain_scores_gemma":[0.9914723,0.005099679,0.00079248246,0.0014211091,0.00067713734,0.0005373661],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039980104,0.0006505,0.00094209344,0.0005138306,0.0006864484,0.0012456586,0.0019381526,0.00075913395,0.0026613707],"category_scores_gemma":[0.018252674,0.0005276876,0.0006326866,0.0010448502,0.001488133,0.0021006884,0.001087332,0.0014635873,0.0003630437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007493928,0.00033536772,0.0019053649,0.00016000918,0.000056847894,0.00006327499,0.00028515173,0.8087904,0.0033577126,0.12058194,0.0017798764,0.06193465],"study_design_scores_gemma":[0.000056854667,0.00008613116,0.00020715377,0.0000057178936,0.000009354991,0.000014892428,0.00002654875,0.9585398,0.0012506661,0.039063506,0.0007331275,0.000006318215],"about_ca_topic_score_codex":0.00294739,"about_ca_topic_score_gemma":0.003226121,"teacher_disagreement_score":0.0039980104,"about_ca_system_score_codex":0.0022538772,"about_ca_system_score_gemma":0.003800858,"threshold_uncertainty_score":0.021143734},"labels":[],"label_agreement":null},{"id":"W2128513449","doi":"","title":"Curves of Width One and the River Shore Problem","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Polygon (computer graphics); Shore; Unit (ring theory); Plane (geometry); Mathematics; Exploit; Line (geometry); Computer science; Mathematical optimization; Algorithm; Geometry; Geology; Telecommunications","score_opus":0.01789507405513871,"score_gpt":0.22693721706937725,"score_spread":0.20904214301423854,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128513449","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33986163,0.01168424,0.49839193,0.0064595956,0.00052183965,0.00022428617,0.0013774438,0.0005115754,0.14096749],"genre_scores_gemma":[0.76276016,0.010959558,0.16724613,0.00047798836,0.000658055,0.00017286018,0.001971527,0.0003324039,0.055421427],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99950695,0.00010564549,0.000021861892,0.00013153262,0.00011606706,0.0001180241],"domain_scores_gemma":[0.9986985,0.00065050216,0.00024566535,0.000082375125,0.0000788454,0.00024418213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000492544,0.0013004595,0.0011006533,0.0012257985,0.0014730014,0.0018079722,0.0013452113,0.002729553,0.010888084],"category_scores_gemma":[0.0036985485,0.0005153951,0.0008446871,0.003014707,0.0023278377,0.0050676744,0.0024279002,0.0026451729,0.001118436],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020499079,0.00019296812,0.0015039447,0.0004556689,0.000039662835,0.0006189082,0.0003324904,0.22320111,0.0017062532,0.6817591,0.011719729,0.078265205],"study_design_scores_gemma":[0.000111553134,0.00017437777,0.00072732766,0.00009980608,0.000036293102,0.0005553316,0.0003917437,0.19783346,0.0015312755,0.7569611,0.04151326,0.00006446258],"about_ca_topic_score_codex":0.0027771827,"about_ca_topic_score_gemma":0.0017626456,"teacher_disagreement_score":0.010888084,"about_ca_system_score_codex":0.0010257991,"about_ca_system_score_gemma":0.0006706384,"threshold_uncertainty_score":0.03642422},"labels":[],"label_agreement":null},{"id":"W2128634904","doi":"10.1145/2629656","title":"Gathering Despite Mischief","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":74,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Israeli Centers for Research Excellence; Natural Sciences and Engineering Research Council of Canada; Israel Science Foundation; United States-Israel Binational Science Foundation","keywords":"Byzantine architecture; Computer science; Node (physics); Upper and lower bounds; Matching (statistics); Combinatorics; Theoretical computer science; Mathematics; Discrete mathematics; Physics; Geography","score_opus":0.020241239274524116,"score_gpt":0.2543549482875596,"score_spread":0.2341137090130355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2128634904","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1466503,0.00051456544,0.82250994,0.0034576666,0.00015293785,0.00030095686,0.00045689737,0.0023824703,0.02357423],"genre_scores_gemma":[0.72804177,0.00034537955,0.25427026,0.0006365247,0.00010296075,0.00032149302,0.0006896717,0.00045083655,0.015141106],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99659497,0.00087086635,0.00019786716,0.0011892518,0.00052620756,0.0006207973],"domain_scores_gemma":[0.98257357,0.0068355277,0.0017034264,0.0066044503,0.0014135988,0.00086942327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030382844,0.0013374316,0.0013256448,0.00064144545,0.0033112469,0.0021421085,0.0031191558,0.00217349,0.006486794],"category_scores_gemma":[0.020331351,0.0009184172,0.0010355257,0.0009222307,0.0024277212,0.0052226274,0.0051773423,0.0022858917,0.0017303481],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020064847,0.0003331543,0.013062502,0.0015770494,0.00036783633,0.002061824,0.0062922277,0.28804287,0.04537805,0.3169556,0.026936661,0.29698572],"study_design_scores_gemma":[0.00017986551,0.0005942662,0.0026777196,0.00018706979,0.00018906833,0.001401202,0.0012928629,0.65804726,0.024167817,0.25053656,0.060641762,0.00008455909],"about_ca_topic_score_codex":0.002734772,"about_ca_topic_score_gemma":0.0038515327,"teacher_disagreement_score":0.006486794,"about_ca_system_score_codex":0.0014490375,"about_ca_system_score_gemma":0.0017909986,"threshold_uncertainty_score":0.021700501},"labels":[],"label_agreement":null},{"id":"W2130941032","doi":"10.1109/crv.2007.5","title":"A non-myopic approach to visual search","year":2007,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Object (grammar); Computer science; Artificial intelligence; Object detection; Computer vision; Visual search; Prior probability; Greedy algorithm; Pattern recognition (psychology); Algorithm; Bayesian probability","score_opus":0.02985815868770078,"score_gpt":0.3199826247710285,"score_spread":0.29012446608332776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2130941032","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02642063,0.0004731727,0.9507664,0.0009925799,0.000059234277,0.000069014,0.000092004775,0.00023905587,0.02088794],"genre_scores_gemma":[0.79855114,0.00035703296,0.18812783,0.00034596623,0.000045911227,0.0001929927,0.00006686488,0.00009083421,0.012221467],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99927944,0.00031553887,0.000024400293,0.00014548915,0.00014319134,0.00009192991],"domain_scores_gemma":[0.99878067,0.0007859812,0.00010792803,0.00012883951,0.00011047439,0.00008612522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001012713,0.0009530886,0.00086406583,0.0005405147,0.0007340942,0.0013153922,0.0017665606,0.0017796414,0.005755827],"category_scores_gemma":[0.004472633,0.00064112124,0.00066397665,0.0006342312,0.0015871957,0.0018775798,0.0018941317,0.0012197293,0.0005857607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011011369,0.00006270087,0.00034338952,0.00010187786,0.00005143742,0.0001343857,0.00015003793,0.85776687,0.002659197,0.1184434,0.0018245447,0.018352062],"study_design_scores_gemma":[0.000025013005,0.000039810282,0.000089374145,0.000008485334,0.000007764637,0.000043639557,0.000020615322,0.9438947,0.00033390577,0.054594625,0.0009316229,0.000010387291],"about_ca_topic_score_codex":0.0054198084,"about_ca_topic_score_gemma":0.004531429,"teacher_disagreement_score":0.005755827,"about_ca_system_score_codex":0.0012182246,"about_ca_system_score_gemma":0.001572025,"threshold_uncertainty_score":0.019255102},"labels":[],"label_agreement":null},{"id":"W2131679923","doi":"10.1109/spdp.1991.218285","title":"Boolean theory of coteries","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Boolean function; Boolean data type; Set (abstract data type); Computer science; Function (biology); Decomposition; Theoretical computer science; True quantified Boolean formula; Variable (mathematics); Combinatorics; Discrete mathematics; Mathematics; Algorithm; Biology; Programming language","score_opus":0.03830592162255064,"score_gpt":0.22619755261733668,"score_spread":0.18789163099478604,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2131679923","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09686793,0.0056652073,0.7086361,0.0033428324,0.00043959878,0.00014549296,0.0012804632,0.0003718667,0.18325044],"genre_scores_gemma":[0.80800176,0.003522469,0.14050867,0.0010492243,0.0006232556,0.0003696686,0.0013776565,0.00015880547,0.044388384],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980794,0.00052496133,0.00014711263,0.00045185024,0.0004984907,0.00029812605],"domain_scores_gemma":[0.9976562,0.0013049,0.00022960284,0.00019621318,0.00041840688,0.00019456688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018424909,0.0007723104,0.00070837274,0.0023666709,0.0014694968,0.004398114,0.0011871872,0.001257098,0.0093300715],"category_scores_gemma":[0.0045766025,0.00046607465,0.0011346282,0.0027540878,0.0034179986,0.0071456437,0.0017983555,0.0020816787,0.0012616256],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000012468942,0.0000050227964,0.000092107184,0.000033287888,0.0000056942886,0.000023895147,0.000092211165,0.0010693662,0.0002607886,0.9927832,0.001003979,0.004617922],"study_design_scores_gemma":[0.000014935236,0.000022606915,0.00018199702,0.00004161452,0.000015744603,0.000109674904,0.000116511415,0.015792614,0.00050955586,0.96598744,0.017195903,0.000011490286],"about_ca_topic_score_codex":0.0031273882,"about_ca_topic_score_gemma":0.00238947,"teacher_disagreement_score":0.0093300715,"about_ca_system_score_codex":0.0030150611,"about_ca_system_score_gemma":0.00058564625,"threshold_uncertainty_score":0.031212151},"labels":[],"label_agreement":null},{"id":"W2132813033","doi":"10.1016/j.dam.2013.03.004","title":"Three-fast-searchable graphs","year":2013,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Ministerstwo Edukacji i Nauki; Fundacja na rzecz Nauki Polskiej","keywords":"Mathematics; Combinatorics","score_opus":0.019420457476262504,"score_gpt":0.2452834164866836,"score_spread":0.22586295901042108,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2132813033","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20608316,0.00075152924,0.698744,0.0038096912,0.00028768086,0.00038075662,0.0031244217,0.002102045,0.08471672],"genre_scores_gemma":[0.64758396,0.0007766387,0.30611548,0.0009013769,0.00012383476,0.00036388138,0.0029954328,0.00076443685,0.040374964],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99932647,0.00018135818,0.00003654057,0.00015058655,0.00015130344,0.00015379637],"domain_scores_gemma":[0.9957747,0.0017878035,0.00034355547,0.0009244382,0.0006073575,0.0005621811],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084898714,0.0008354313,0.000991604,0.0011968954,0.001947985,0.0024727855,0.002332579,0.002002182,0.018906958],"category_scores_gemma":[0.00571579,0.00061092386,0.0014303487,0.0015677282,0.0018604038,0.0040839757,0.0021731341,0.0030510197,0.002285297],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00053025474,0.00014190616,0.00065179204,0.00036473846,0.00006151394,0.00030859496,0.00031160566,0.046724964,0.0061761853,0.8836957,0.015797349,0.045235354],"study_design_scores_gemma":[0.00013048969,0.000053691965,0.00040082767,0.00003620556,0.000039452778,0.00020742377,0.00015216648,0.081467204,0.0025455754,0.90532875,0.009610406,0.000027802951],"about_ca_topic_score_codex":0.0038231835,"about_ca_topic_score_gemma":0.0059054145,"teacher_disagreement_score":0.018906958,"about_ca_system_score_codex":0.0018625967,"about_ca_system_score_gemma":0.0017227886,"threshold_uncertainty_score":0.063250065},"labels":[],"label_agreement":null},{"id":"W2133402615","doi":"10.1007/978-3-319-03089-0_21","title":"Gathering Asynchronous Oblivious Agents with Restricted Vision in an Infinite Line","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Asynchronous communication; Computer science; Line (geometry); Mathematics; Telecommunications; Geometry","score_opus":0.023383649100682028,"score_gpt":0.268899586946496,"score_spread":0.245515937845814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133402615","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08632514,0.00018112025,0.899206,0.0004942355,0.000047716214,0.00010458303,0.00006825281,0.00076413836,0.012808783],"genre_scores_gemma":[0.80766773,0.00018944536,0.18022811,0.00017443157,0.000052704454,0.00031193718,0.00012695929,0.00015570203,0.011093073],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989416,0.00037098984,0.0000669363,0.00022759348,0.00022617796,0.00016679925],"domain_scores_gemma":[0.9958125,0.0026385807,0.0003674002,0.0005524016,0.00031660945,0.00031247264],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013414896,0.00074456556,0.0012256725,0.0006609988,0.0012934795,0.002328683,0.0023815813,0.0014675718,0.0044602887],"category_scores_gemma":[0.0061960607,0.0006970539,0.00086349226,0.00075836247,0.0018369429,0.004357123,0.0038196777,0.002006582,0.0006982553],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007533221,0.0002277206,0.0007689525,0.00034453877,0.00013173418,0.00048022266,0.00089337426,0.5524508,0.010931335,0.38095233,0.003477942,0.048587713],"study_design_scores_gemma":[0.00005836604,0.00007008141,0.00004939527,0.000014402286,0.000016875098,0.00004715672,0.00006940148,0.84354186,0.0010868192,0.15402275,0.0010076298,0.00001531207],"about_ca_topic_score_codex":0.0013671181,"about_ca_topic_score_gemma":0.0014394769,"teacher_disagreement_score":0.0044602887,"about_ca_system_score_codex":0.0011825102,"about_ca_system_score_gemma":0.0009445133,"threshold_uncertainty_score":0.014921129},"labels":[],"label_agreement":null},{"id":"W2136642745","doi":"10.1287/trsc.1050.0139","title":"Dispatching Buses in a Depot Using Block Patterns","year":2006,"lang":"en","type":"article","venue":"Transportation Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec à Montréal; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Depot; Transport engineering; Block (permutation group theory); Computer science; Operations research; Engineering; Geography; Mathematics","score_opus":0.02247243372626171,"score_gpt":0.28256554367405795,"score_spread":0.2600931099477962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136642745","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4217841,0.00029600048,0.56173116,0.00042872116,0.00007691687,0.00031265532,0.0007856437,0.00075819157,0.013826654],"genre_scores_gemma":[0.8427993,0.0004072713,0.14318717,0.000063928535,0.000021463224,0.00020469564,0.0007388796,0.00013517459,0.012442058],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996917,0.00009232639,0.000016691838,0.000066576285,0.0000581,0.00007451911],"domain_scores_gemma":[0.9996094,0.00011852282,0.000089198125,0.00007296425,0.000040496085,0.00006934776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003294726,0.0005847305,0.0006518172,0.00030641453,0.0003921552,0.0009582069,0.0008164898,0.0006286866,0.0054421676],"category_scores_gemma":[0.0008520891,0.00049349916,0.0004834037,0.00096142764,0.00034839712,0.0015256092,0.00066825515,0.00054669473,0.00079133466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044130927,0.000122571,0.0019098717,0.00013945017,0.000053042557,0.00026563802,0.00013662495,0.91875994,0.008710053,0.032903355,0.0020722577,0.034485955],"study_design_scores_gemma":[0.000060002025,0.00016762587,0.0005201116,0.000007913016,0.000015309603,0.0000699891,0.000072354866,0.9755039,0.0023195297,0.015625253,0.005624389,0.000013636472],"about_ca_topic_score_codex":0.00819703,"about_ca_topic_score_gemma":0.01071904,"teacher_disagreement_score":0.00819703,"about_ca_system_score_codex":0.00067902834,"about_ca_system_score_gemma":0.0010725096,"threshold_uncertainty_score":0.018205881},"labels":[],"label_agreement":null},{"id":"W2136868932","doi":"10.1109/iccis.2004.1460420","title":"Generalized TSE: a new generalized estimator-based learning automaton","year":2005,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Estimator; Learning automata; Representation (politics); Computer science; Algorithm; Automaton; Artificial intelligence; Scheme (mathematics); Mathematics; Theoretical computer science; Statistics","score_opus":0.024473304481145253,"score_gpt":0.28528604330927665,"score_spread":0.2608127388281314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136868932","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007757585,0.00018581882,0.9895739,0.00014129397,0.000057415575,0.000037220518,0.00006212457,0.00069856364,0.0014860603],"genre_scores_gemma":[0.47699788,0.00045834377,0.51473874,0.0003794484,0.00009847751,0.00031767355,0.00036836247,0.00024341201,0.006397668],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99902296,0.00024094009,0.00008187714,0.00026033036,0.00031906104,0.00007475445],"domain_scores_gemma":[0.99749315,0.0012482072,0.00019586312,0.0004859008,0.00048111656,0.00009579466],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001232507,0.0005401933,0.0012566969,0.0005460599,0.0004552536,0.001320445,0.0020136577,0.0012410833,0.0034755275],"category_scores_gemma":[0.0060426826,0.0003055388,0.00074310286,0.00059123733,0.0014219575,0.002028108,0.0014827804,0.0016037105,0.0007943359],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019970568,0.00007389787,0.0018565624,0.00019180213,0.00010097116,0.00013107402,0.00020543403,0.6355699,0.0067029493,0.12641813,0.0030874407,0.22546223],"study_design_scores_gemma":[0.000010780549,0.000055883997,0.00009791853,0.000010849663,0.000011152554,0.000045751032,0.000008566126,0.9752704,0.0011331186,0.021108143,0.0022359814,0.000011478024],"about_ca_topic_score_codex":0.0025812748,"about_ca_topic_score_gemma":0.0025444576,"teacher_disagreement_score":0.0034755275,"about_ca_system_score_codex":0.0006755328,"about_ca_system_score_gemma":0.0013125507,"threshold_uncertainty_score":0.01162678},"labels":[],"label_agreement":null},{"id":"W2138178581","doi":"10.1007/978-3-642-29344-3_31","title":"Decidability Classes for Mobile Agents Computing","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Decidability; Computer science; Certificate; Decision problem; Focus (optics); Protocol (science); Mobile agent; Existential quantification; Theoretical computer science; Artificial intelligence; Algorithm; Distributed computing; Mathematics; Discrete mathematics","score_opus":0.03967317163642082,"score_gpt":0.3066049741150857,"score_spread":0.2669318024786649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138178581","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047607318,0.006250636,0.80860484,0.010983906,0.0006625011,0.00035700592,0.0015559315,0.001912213,0.12206563],"genre_scores_gemma":[0.641069,0.0041774805,0.2925222,0.0021580714,0.0016700069,0.0013730546,0.0042555635,0.001156828,0.051617846],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979506,0.0004960572,0.00016748776,0.0005277408,0.0005510817,0.00030711052],"domain_scores_gemma":[0.9932433,0.005624638,0.00015783707,0.0005660767,0.00024382996,0.0001643553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021145572,0.0011083839,0.0010012047,0.001115572,0.002225636,0.0049934704,0.0030763377,0.0021856616,0.009392852],"category_scores_gemma":[0.008638226,0.0010346663,0.00270039,0.0012864402,0.0034617174,0.010485553,0.0027617838,0.00818779,0.0011560897],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004458862,0.00006783493,0.00021602289,0.00019601005,0.000023011367,0.00006323442,0.00039204644,0.005957787,0.00056019786,0.95807964,0.0071155047,0.027284054],"study_design_scores_gemma":[0.000020627545,0.000005246089,0.00007330109,0.000031376672,0.0000126775285,0.00003365898,0.00005233999,0.015353518,0.0004616625,0.97709787,0.0068499832,0.0000077023515],"about_ca_topic_score_codex":0.0036965373,"about_ca_topic_score_gemma":0.0036421176,"teacher_disagreement_score":0.009392852,"about_ca_system_score_codex":0.003912054,"about_ca_system_score_gemma":0.001913314,"threshold_uncertainty_score":0.031422257},"labels":[],"label_agreement":null},{"id":"W2140995153","doi":"10.1115/imece2010-38914","title":"An Optimal Orthogonal Recharging Route Planner: A Multi-Robots, Multi-Rendezvous Recharging Scheme","year":2010,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Rendezvous; Robot; Tree traversal; Planner; Computer science; Scheme (mathematics); Orthogonal array; Work (physics); Real-time computing; Simulation; Mathematical optimization; Engineering; Mathematics; Artificial intelligence; Algorithm","score_opus":0.04297016576045565,"score_gpt":0.3196854649808724,"score_spread":0.27671529922041677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140995153","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021981757,0.000096856245,0.97461873,0.00008428686,0.000017349459,0.00006657085,0.000049656646,0.00046934027,0.002615388],"genre_scores_gemma":[0.51107883,0.00011033785,0.48323083,0.00003421215,0.000011564767,0.000120923825,0.00010195099,0.000052918018,0.005258328],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973685,0.0000658502,0.000011041581,0.00007647365,0.000063438616,0.000046359866],"domain_scores_gemma":[0.9998054,0.000049922484,0.000047753176,0.000039280538,0.000033480497,0.000024094386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004628007,0.00048045794,0.0006145296,0.0003516142,0.0003478205,0.0004253498,0.0011041851,0.000639607,0.0019695433],"category_scores_gemma":[0.00069142523,0.00022462402,0.00029335858,0.000434915,0.00040835247,0.0005426544,0.0007859115,0.00042357272,0.00037239105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002554674,0.00008784104,0.00048609238,0.00014002451,0.00003220057,0.00014627929,0.00013626395,0.8045198,0.016041584,0.015760656,0.0019726332,0.16042121],"study_design_scores_gemma":[0.000035415174,0.00011081474,0.00015891246,0.0000049365144,0.000008837555,0.00006659092,0.00003230923,0.992554,0.0026546076,0.002355332,0.0020042616,0.000013831217],"about_ca_topic_score_codex":0.002924292,"about_ca_topic_score_gemma":0.0038578822,"teacher_disagreement_score":0.002924292,"about_ca_system_score_codex":0.0004368671,"about_ca_system_score_gemma":0.0011752622,"threshold_uncertainty_score":0.0065888166},"labels":[],"label_agreement":null},{"id":"W2141168954","doi":"10.1109/cimca.2005.1631525","title":"A General Cache Partition Model for Multiple QoS Classes: Algorithm and Simulation","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Trent University","funders":"","keywords":"Computer science; Cache; Partition (number theory); Quality of service; Cache algorithms; Popularity; Algorithm; Parallel computing; CPU cache; Distributed computing; Computer network; Mathematics","score_opus":0.038482076230223934,"score_gpt":0.2908025213047491,"score_spread":0.25232044507452517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141168954","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.051527943,0.00036091398,0.9438065,0.0002104448,0.000029065668,0.000115018345,0.000093969385,0.0003562391,0.0034998653],"genre_scores_gemma":[0.590576,0.00062976166,0.40137175,0.00011493914,0.000049580314,0.0006987422,0.00026687616,0.00013784543,0.0061545293],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996952,0.00011021086,0.00001242769,0.0000572223,0.00007114324,0.000053875778],"domain_scores_gemma":[0.9991948,0.00049370667,0.000072953175,0.00005170906,0.00015102432,0.000035877372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095003593,0.0006084765,0.0010172215,0.00056868617,0.00056782877,0.0009248265,0.00165412,0.0015935752,0.002129143],"category_scores_gemma":[0.0023593274,0.00040791422,0.00073896354,0.0010904948,0.0007424867,0.0015413213,0.0007548551,0.00083540543,0.0003497202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023700928,0.000016794169,0.00024260838,0.000017915394,0.000011952906,0.000018395967,0.000021620874,0.9905686,0.00046492316,0.004435761,0.00020734442,0.003970374],"study_design_scores_gemma":[0.0000062320273,0.0000041837857,0.000021928141,0.0000013756851,0.0000025686334,0.0000061880182,0.0000021014455,0.99904543,0.00006408131,0.00073972903,0.000104445724,0.0000017385363],"about_ca_topic_score_codex":0.012292371,"about_ca_topic_score_gemma":0.006682278,"teacher_disagreement_score":0.012292371,"about_ca_system_score_codex":0.0014347538,"about_ca_system_score_gemma":0.0014015116,"threshold_uncertainty_score":0.02444166},"labels":[],"label_agreement":null},{"id":"W2142094448","doi":"10.1007/s00453-009-9311-6","title":"Stochastic Models for Budget Optimization in Search-Based Advertising","year":2009,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Theory of computation; Probabilistic logic; Stochastic optimization; Mathematical optimization; Simple (philosophy); Budget constraint; Online advertising; Prefix; The Internet; Operations research; Mathematics; Algorithm; Economics; World Wide Web; Artificial intelligence","score_opus":0.021913556786185527,"score_gpt":0.2746936839958445,"score_spread":0.252780127209659,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142094448","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02598305,0.0057259155,0.9444538,0.006508125,0.00038301657,0.0001559685,0.0006503812,0.00027016978,0.015869623],"genre_scores_gemma":[0.7961712,0.011037118,0.12851828,0.0013325271,0.0014170797,0.0011371429,0.0010830296,0.0004554442,0.05884806],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99543446,0.0027881193,0.00019526269,0.0004806846,0.00059615914,0.00050537236],"domain_scores_gemma":[0.97843987,0.018240117,0.001354486,0.000584255,0.0008106442,0.0005706581],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008679903,0.0023546473,0.0048352,0.0024171867,0.0013457374,0.0058700056,0.004310869,0.0056151166,0.011418797],"category_scores_gemma":[0.041111816,0.003253408,0.00245367,0.003449525,0.003943408,0.0074273287,0.00258332,0.006468094,0.0011941645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006865385,0.00006580331,0.0003749043,0.00013030299,0.00007150631,0.0000534407,0.00009915575,0.41684273,0.00015978185,0.5731094,0.003777923,0.005246485],"study_design_scores_gemma":[0.000038197242,0.000017204815,0.00013793686,0.000028334745,0.000031500844,0.000020615931,0.000024392693,0.74604154,0.00004488266,0.25230965,0.0012823791,0.000023469682],"about_ca_topic_score_codex":0.012698665,"about_ca_topic_score_gemma":0.01158927,"teacher_disagreement_score":0.012698665,"about_ca_system_score_codex":0.0063108113,"about_ca_system_score_gemma":0.0030053642,"threshold_uncertainty_score":0.04590422},"labels":[],"label_agreement":null},{"id":"W2143059072","doi":"10.1109/icmlc.2006.259048","title":"Competitive Analysis for the On-Line Fuzzy Most Connective Path Problem","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China; Ontario Federation for Cerebral Palsy","keywords":"Fuzzy logic; Path (computing); Line (geometry); Mathematical proof; Computer science; Competitive analysis; Domain (mathematical analysis); Mathematical optimization; Fuzzy set; Mathematics; Algorithm; Artificial intelligence","score_opus":0.02605275785397674,"score_gpt":0.27363436764726834,"score_spread":0.2475816097932916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2143059072","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048506837,0.00068125804,0.9249153,0.00095126434,0.000084893436,0.00013757861,0.00014159981,0.000063474654,0.024517843],"genre_scores_gemma":[0.80266994,0.00152864,0.18294266,0.00038615236,0.00023645611,0.00036304572,0.00029541837,0.000095140575,0.01148256],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979309,0.00097596337,0.000058694866,0.000296604,0.00051407417,0.00022380988],"domain_scores_gemma":[0.9944119,0.004139902,0.0004736279,0.00018042103,0.00050345075,0.00029071822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002590638,0.0009829772,0.001076917,0.0009972516,0.0010503418,0.0025096042,0.0016711083,0.0020248285,0.009397237],"category_scores_gemma":[0.010187775,0.00031402873,0.0008986374,0.0013377647,0.0016123349,0.0040570055,0.0015878334,0.0017597049,0.0005208721],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002035338,0.00012771144,0.0006843634,0.00031160886,0.00008960873,0.0001611876,0.00020637986,0.2752771,0.0014527148,0.68072516,0.00364291,0.03711775],"study_design_scores_gemma":[0.00003430031,0.00012684928,0.0002264289,0.000025189234,0.000021939097,0.00010598492,0.000101679834,0.78358394,0.00059743464,0.21179041,0.003362197,0.000023618093],"about_ca_topic_score_codex":0.002329536,"about_ca_topic_score_gemma":0.0012574705,"teacher_disagreement_score":0.009397237,"about_ca_system_score_codex":0.0024268772,"about_ca_system_score_gemma":0.0016814291,"threshold_uncertainty_score":0.03143692},"labels":[],"label_agreement":null},{"id":"W2144182788","doi":"10.1016/j.tcs.2007.09.032","title":"Gathering asynchronous oblivious mobile robots in a ring","year":2007,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":191,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Snapshot (computer storage); Robot; Asynchronous communication; Computer science; Mobile robot; Node (physics); Ring (chemistry); Algorithm; Topology (electrical circuits); Mathematics; Combinatorics; Computer network; Artificial intelligence; Engineering; Operating system","score_opus":0.009868126200166685,"score_gpt":0.26984641937393045,"score_spread":0.25997829317376375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144182788","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3239764,0.00035349224,0.6653677,0.00086316303,0.00010484595,0.00018555603,0.00014255922,0.00061717373,0.008389221],"genre_scores_gemma":[0.9026564,0.00023552414,0.08685754,0.000079692865,0.00007364582,0.00020776532,0.00008067811,0.00007383189,0.00973498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99911016,0.00028796672,0.000054711945,0.00019590635,0.00016394522,0.00018735885],"domain_scores_gemma":[0.99468285,0.00306725,0.00071977417,0.0007898108,0.000294697,0.00044564044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016351538,0.0006313457,0.0013362564,0.00084195693,0.0015717504,0.0013381081,0.0018839362,0.001102525,0.004044795],"category_scores_gemma":[0.006606077,0.00059233274,0.000592298,0.00091843464,0.0012867312,0.0036670784,0.0038792843,0.0011145714,0.0007695107],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024904492,0.00034080274,0.0026890673,0.0006353147,0.00017791387,0.0006582446,0.0009722957,0.67916137,0.0334267,0.21913776,0.004123767,0.05618636],"study_design_scores_gemma":[0.00012891498,0.00036248006,0.0002649779,0.000018020815,0.000050339986,0.0001287076,0.0002026789,0.9247347,0.005638298,0.06632079,0.0021251438,0.000025025412],"about_ca_topic_score_codex":0.00047599833,"about_ca_topic_score_gemma":0.0006236786,"teacher_disagreement_score":0.004044795,"about_ca_system_score_codex":0.0006270033,"about_ca_system_score_gemma":0.000665208,"threshold_uncertainty_score":0.013531208},"labels":[],"label_agreement":null},{"id":"W2144303191","doi":"10.1109/tsmcb.2002.1049616","title":"Discretized learning automata solutions to the capacity assignment problem for prioritized networks","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Discretization; Learning automata; Computer science; Heuristic; Mathematical optimization; Simulated annealing; Network packet; Genetic algorithm; Set (abstract data type); Automaton; Class (philosophy); Focus (optics); Theoretical computer science; Artificial intelligence; Algorithm; Mathematics","score_opus":0.0454457620888802,"score_gpt":0.24205965216824274,"score_spread":0.19661389007936253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144303191","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04544496,0.00043044504,0.94387,0.0005481622,0.00006802149,0.00004806057,0.00015194365,0.00030415537,0.0091341995],"genre_scores_gemma":[0.7702318,0.00029189495,0.22444996,0.00015372441,0.000036644506,0.00021743528,0.00020306645,0.000054237542,0.0043612714],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999684,0.000108291235,0.000016920869,0.0000620345,0.00007454049,0.0000543201],"domain_scores_gemma":[0.9990096,0.00064812193,0.00009222425,0.000075722885,0.000111089525,0.000063228785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003636287,0.00053414935,0.0007808298,0.00036662628,0.00042339548,0.0009231046,0.0009945438,0.0012413493,0.0035384798],"category_scores_gemma":[0.0021630072,0.00033780822,0.0005541782,0.00044879084,0.0010044139,0.00078521646,0.0007872558,0.0011585982,0.00025229086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023690009,0.000020957903,0.00015717484,0.000036120196,0.000012262105,0.00003512651,0.000044631422,0.96803635,0.00062271603,0.023267118,0.00039882932,0.007345009],"study_design_scores_gemma":[0.000009391079,0.000010076522,0.000021304064,0.0000029005967,0.0000022936201,0.0000065207996,0.0000076007414,0.98775524,0.00013466523,0.011717047,0.00033032132,0.0000026428577],"about_ca_topic_score_codex":0.004625055,"about_ca_topic_score_gemma":0.004972913,"teacher_disagreement_score":0.004625055,"about_ca_system_score_codex":0.0010988531,"about_ca_system_score_gemma":0.0011646581,"threshold_uncertainty_score":0.011837423},"labels":[],"label_agreement":null},{"id":"W2146625634","doi":"10.1007/978-3-540-24698-5_59","title":"On the Competitiveness of AIMD-TCP within a General Network","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Bottleneck; Computer science; Multiplicative function; Scheduling (production processes); Distributed computing; Mathematical optimization; Mathematics","score_opus":0.019571879034526476,"score_gpt":0.24416942167640399,"score_spread":0.2245975426418775,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146625634","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5217091,0.008925768,0.18671167,0.01795994,0.0009894101,0.0003525721,0.0015515948,0.0019319166,0.25986812],"genre_scores_gemma":[0.9595906,0.002140601,0.026822455,0.0007249848,0.00069442,0.0001892997,0.00052946334,0.00077301805,0.008535042],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99373335,0.0023816412,0.00014983516,0.00077267905,0.0011930661,0.0017694348],"domain_scores_gemma":[0.93864053,0.048797984,0.0017360469,0.0040019215,0.0031949524,0.0036286092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009805538,0.0015554345,0.0036464026,0.002476862,0.0034112954,0.0075814375,0.004810444,0.003238068,0.019478546],"category_scores_gemma":[0.051844954,0.0009055915,0.001546982,0.0031262834,0.0051201642,0.01218823,0.0059696897,0.0061182505,0.0018201502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032795386,0.00040876825,0.0041675176,0.0006580988,0.00019377467,0.00028601932,0.0005662537,0.30735433,0.005991944,0.59267837,0.031121153,0.05329427],"study_design_scores_gemma":[0.00021846818,0.00035173888,0.001463888,0.00011584249,0.0001594021,0.0002686259,0.00042780317,0.6682829,0.0025247864,0.31996813,0.006157285,0.000061114835],"about_ca_topic_score_codex":0.0054185134,"about_ca_topic_score_gemma":0.0051508658,"teacher_disagreement_score":0.019478546,"about_ca_system_score_codex":0.0047338274,"about_ca_system_score_gemma":0.005147038,"threshold_uncertainty_score":0.0651623},"labels":[],"label_agreement":null},{"id":"W2149450544","doi":"10.1109/crv.2011.18","title":"Combining Multi-robot Exploration and Rendezvous","year":2011,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Rendezvous; Computer science; Robot; Ranking (information retrieval); Probabilistic logic; Task (project management); Mobile robot; Constraint (computer-aided design); Set (abstract data type); Uniqueness; Distributed computing; Artificial intelligence; Engineering; Mathematics; Spacecraft","score_opus":0.1897041099319295,"score_gpt":0.2846901288087703,"score_spread":0.09498601887684083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149450544","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1086947,0.00060972566,0.8861399,0.00018728957,0.00003611091,0.000106444415,0.000033816694,0.0005831113,0.0036088633],"genre_scores_gemma":[0.86009747,0.000259121,0.13648224,0.000042816882,0.000027375037,0.00015625586,0.00006948653,0.00008620056,0.002778983],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988444,0.0003693069,0.000051890467,0.00028345545,0.00029100658,0.00015991836],"domain_scores_gemma":[0.9980934,0.0009900223,0.00024075678,0.00036132397,0.00013376243,0.0001808146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013973941,0.0016917106,0.002014182,0.0007272405,0.000833054,0.00096693385,0.0021025774,0.0012589007,0.0012803607],"category_scores_gemma":[0.0038328131,0.00086172874,0.0009975344,0.00096712506,0.0013213444,0.0025593804,0.003136596,0.00095373887,0.0003716238],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027502596,0.00009646718,0.00090064184,0.000109444525,0.00008874531,0.00022151077,0.00009281485,0.9507365,0.005041189,0.0054139434,0.00022554214,0.036798175],"study_design_scores_gemma":[0.000037482157,0.0003455031,0.00042602402,0.000008312382,0.00003319538,0.00013478613,0.000047691155,0.9814378,0.0039005212,0.012632448,0.0009692286,0.000027010057],"about_ca_topic_score_codex":0.0018812438,"about_ca_topic_score_gemma":0.0022249117,"teacher_disagreement_score":0.0021025774,"about_ca_system_score_codex":0.0005633587,"about_ca_system_score_gemma":0.0008624397,"threshold_uncertainty_score":0.0073902607},"labels":[],"label_agreement":null},{"id":"W2149929647","doi":"10.1109/focs.2006.15","title":"Approximation Algorithms for Non-Uniform Buy-at-Bulk Network Design","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":67,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Combinatorics; Binary logarithm; Logarithm; Approximation algorithm; Algorithm; Embedding; Vertex (graph theory); Discrete mathematics; Mathematics; Graph; Computer science; Artificial intelligence; Mathematical analysis","score_opus":0.03388222873633773,"score_gpt":0.2617209479277961,"score_spread":0.22783871919145837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2149929647","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028669879,0.0012940113,0.9594544,0.0011645319,0.000116640746,0.00018725138,0.00045261695,0.0015191995,0.0071414164],"genre_scores_gemma":[0.45479667,0.0012394727,0.5279004,0.0008161186,0.00028794835,0.0005368032,0.0019139296,0.0007334397,0.011775279],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964366,0.0011681273,0.00017767449,0.0008699983,0.0006839991,0.00066364155],"domain_scores_gemma":[0.99298495,0.0044867247,0.0006129191,0.0012300404,0.0004027234,0.0002826496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003546741,0.0023355903,0.0025805125,0.0013111082,0.0011195744,0.0027079838,0.0040293997,0.0029251669,0.011198542],"category_scores_gemma":[0.014583169,0.0011323661,0.0019073235,0.0032677602,0.001448174,0.007781372,0.0027135166,0.0034153278,0.0022246216],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009454484,0.0004884095,0.0014631604,0.0005763792,0.00015935427,0.00015058064,0.00022746195,0.76387024,0.0026047684,0.058531355,0.015345167,0.15563773],"study_design_scores_gemma":[0.00008794154,0.000105524414,0.00016218267,0.000021662127,0.000027359167,0.00009486855,0.00004267359,0.93265593,0.0008386612,0.064190775,0.0017584718,0.000013948039],"about_ca_topic_score_codex":0.003067707,"about_ca_topic_score_gemma":0.003898341,"teacher_disagreement_score":0.011198542,"about_ca_system_score_codex":0.0031233174,"about_ca_system_score_gemma":0.0015959821,"threshold_uncertainty_score":0.03746289},"labels":[],"label_agreement":null},{"id":"W2150541902","doi":"10.1145/336154.336225","title":"Optimal robot localization in trees","year":2000,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Robot; Artificial intelligence; Computer vision","score_opus":0.016562985999989604,"score_gpt":0.2554649911040864,"score_spread":0.2389020051040968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2150541902","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021560421,0.00548285,0.9432507,0.0006459692,0.00031153474,0.000053582255,0.0003211154,0.0008972616,0.027476478],"genre_scores_gemma":[0.6363659,0.010346805,0.31589743,0.00033016095,0.00036551864,0.00025801008,0.0014554408,0.00065319677,0.034327608],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997416,0.0000683989,0.000009074731,0.00005699822,0.00008018521,0.00004377563],"domain_scores_gemma":[0.99961877,0.0002200404,0.00003665647,0.000040771487,0.00004912884,0.000034538647],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026824797,0.00051633036,0.0010798331,0.00075781817,0.00046012778,0.0005966287,0.0005596427,0.0006122677,0.010803884],"category_scores_gemma":[0.0019791995,0.00029326743,0.0003620856,0.0014621157,0.0007682222,0.0013576173,0.0011254551,0.0008246267,0.002770507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003299569,0.000070018716,0.00047935385,0.00080403197,0.00007886039,0.00015760769,0.0001527708,0.45792755,0.0102118235,0.18258777,0.03976396,0.3074363],"study_design_scores_gemma":[0.00007486563,0.00010685835,0.00044313146,0.00010816417,0.0000412874,0.00012562648,0.000050004663,0.66579455,0.0021717926,0.311633,0.019426364,0.00002434895],"about_ca_topic_score_codex":0.0018697502,"about_ca_topic_score_gemma":0.002432892,"teacher_disagreement_score":0.010803884,"about_ca_system_score_codex":0.00047897844,"about_ca_system_score_gemma":0.0005214946,"threshold_uncertainty_score":0.036142588},"labels":[],"label_agreement":null},{"id":"W2152324445","doi":"10.1109/tsmcb.2005.850180","title":"Dynamic Algorithms for the Shortest Path Routing Problem: Learning Automata-Based Solutions","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":77,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Shortest path problem; Shortest Path Faster Algorithm; K shortest path routing; Algorithm; Widest path problem; Computer science; Yen's algorithm; Euclidean shortest path; Distance; Graph; Mathematics; Dijkstra's algorithm; Theoretical computer science","score_opus":0.031070097432292325,"score_gpt":0.26320034852747093,"score_spread":0.2321302510951786,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152324445","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0086804265,0.00021596001,0.98861176,0.0001987975,0.000041666954,0.000044245833,0.000042227806,0.00037635118,0.0017886708],"genre_scores_gemma":[0.48933607,0.0005671738,0.5046515,0.0002331528,0.00011112357,0.000529384,0.00043048698,0.00018967476,0.0039514424],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921405,0.00018618559,0.00005511861,0.00026301062,0.0001862607,0.000095335105],"domain_scores_gemma":[0.9976816,0.0015997542,0.00017336615,0.00016499402,0.00029743396,0.00008280817],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093820586,0.0011225315,0.0011048034,0.0010380514,0.00070198474,0.0012698541,0.0021026933,0.0018188087,0.0025404994],"category_scores_gemma":[0.005828621,0.00055277,0.0008876421,0.0010434894,0.0009978956,0.0019433905,0.0015423328,0.0019249072,0.00046076573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003886647,0.00004600386,0.00046859946,0.00007574627,0.000034308992,0.00003494976,0.00007831598,0.91648906,0.0007479797,0.026068458,0.0010341619,0.054883506],"study_design_scores_gemma":[0.000006557857,0.000011474995,0.000024689332,0.00000482132,0.0000033476215,0.000009413714,0.000009399691,0.98798335,0.00017530558,0.01136198,0.00040570262,0.0000038730714],"about_ca_topic_score_codex":0.004993409,"about_ca_topic_score_gemma":0.0040946486,"teacher_disagreement_score":0.004993409,"about_ca_system_score_codex":0.0012681361,"about_ca_system_score_gemma":0.0017249582,"threshold_uncertainty_score":0.009928703},"labels":[],"label_agreement":null},{"id":"W2152623377","doi":"10.1145/1921659.1921663","title":"Tree exploration with logarithmic memory","year":2011,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Engineering and Physical Sciences Research Council; Royal Society","keywords":"Tree traversal; Node (physics); Traverse; Binary logarithm; Computer science; Tree (set theory); Logarithm; Graph; Upper and lower bounds; Mathematics; Theoretical computer science; Combinatorics; Discrete mathematics; Algorithm","score_opus":0.0695535220691234,"score_gpt":0.2535367779472618,"score_spread":0.1839832558781384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152623377","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17720032,0.0020350348,0.7905157,0.0014887241,0.00014648547,0.00013967388,0.0007438735,0.0030792851,0.024650862],"genre_scores_gemma":[0.70611423,0.00090936286,0.27837467,0.00035662443,0.00006529933,0.00030857153,0.00080904324,0.00042841895,0.012633816],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99947006,0.000112140886,0.00003061478,0.000117918265,0.000103760656,0.00016551142],"domain_scores_gemma":[0.99790716,0.0012403404,0.00017331044,0.0004219531,0.00013257921,0.0001247592],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047681187,0.000664183,0.00081012986,0.0005319755,0.0007569289,0.0014241936,0.0017594133,0.0011576324,0.00890852],"category_scores_gemma":[0.004698718,0.00034160735,0.0006814786,0.0012157619,0.0008332919,0.0053413706,0.0021351816,0.0009566001,0.001580247],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021724878,0.00024522573,0.0022858176,0.00068373693,0.000106464795,0.00050831976,0.00051459717,0.690487,0.013928359,0.11853664,0.01355054,0.15698077],"study_design_scores_gemma":[0.00010583289,0.00013820679,0.00019161505,0.000025272944,0.000032882224,0.00013777893,0.00007026217,0.8732919,0.0035672325,0.11807931,0.0043428373,0.00001689732],"about_ca_topic_score_codex":0.0020949566,"about_ca_topic_score_gemma":0.0023959111,"teacher_disagreement_score":0.00890852,"about_ca_system_score_codex":0.0008616146,"about_ca_system_score_gemma":0.0008052894,"threshold_uncertainty_score":0.029801965},"labels":[],"label_agreement":null},{"id":"W2152948384","doi":"10.1109/tro.2008.2007459","title":"A Distributed Heuristic for Energy-Efficient Multirobot Multiplace Rendezvous","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Rendezvous; Heuristic; Mobile robot; Robot; Computer science; Set (abstract data type); Bounded function; Mathematical optimization; Population; Controller (irrigation); Quality of service; Simple (philosophy); Distributed computing; Artificial intelligence; Mathematics; Engineering; Computer network","score_opus":0.036768076272069655,"score_gpt":0.2553220708945491,"score_spread":0.21855399462247946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152948384","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07458334,0.0003716265,0.91879874,0.0002871904,0.00007910197,0.00014044934,0.00007794166,0.00079365727,0.004867908],"genre_scores_gemma":[0.80558366,0.000087610366,0.19058746,0.00010145182,0.000024800032,0.00023611436,0.00010432145,0.00009211755,0.0031824412],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996569,0.00008623432,0.000013920395,0.00007442305,0.00008888392,0.00007960956],"domain_scores_gemma":[0.9992292,0.00042304146,0.00010085403,0.00006653889,0.00009318493,0.00008721333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084838265,0.00083195063,0.0010860726,0.00065074954,0.0006708113,0.00068977685,0.0019577146,0.0012123493,0.00266403],"category_scores_gemma":[0.0017300337,0.00042988142,0.00044528762,0.0005386565,0.00088980986,0.0008272432,0.0012028986,0.0006235841,0.00040309093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013959176,0.000064571046,0.00020727866,0.000033690227,0.00002468438,0.00005256753,0.000041449763,0.9770632,0.0010773159,0.0024612932,0.0006118976,0.018222481],"study_design_scores_gemma":[0.000045638557,0.00003231478,0.0000408307,0.0000026921907,0.0000044885105,0.000008871737,0.000013296671,0.99848676,0.0002982201,0.00086557673,0.00019762815,0.0000036659037],"about_ca_topic_score_codex":0.0061648972,"about_ca_topic_score_gemma":0.006412562,"teacher_disagreement_score":0.0061648972,"about_ca_system_score_codex":0.0011258015,"about_ca_system_score_gemma":0.0014551642,"threshold_uncertainty_score":0.012258053},"labels":[],"label_agreement":null},{"id":"W2154244688","doi":"10.1007/978-3-540-77120-3_43","title":"On the Relative Dominance of Paging Algorithms","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Paging; Computer science; Algorithm; Demand paging; Thrashing; Interval (graph theory); Virtual memory; Mathematics; Parallel computing; Operating system; Combinatorics; Memory management","score_opus":0.03338256575521329,"score_gpt":0.2782120725851762,"score_spread":0.24482950682996293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154244688","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.057404887,0.010725468,0.75397646,0.0043212613,0.00087139953,0.00023108318,0.0005200968,0.00064064306,0.17130865],"genre_scores_gemma":[0.65690196,0.011662528,0.25655785,0.0021746857,0.0027578496,0.00068697316,0.00095719035,0.0012530783,0.06704785],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99286324,0.0032302663,0.00027653217,0.0005692544,0.0021357294,0.0009250297],"domain_scores_gemma":[0.9730075,0.021408899,0.0008029171,0.0021243358,0.0017720134,0.0008843248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0066263354,0.0021953646,0.003379263,0.0024744903,0.0023343263,0.0061196364,0.004285509,0.002458247,0.014017683],"category_scores_gemma":[0.037508182,0.0012957081,0.0016340299,0.005668349,0.0038638297,0.012091793,0.0039769285,0.0065326667,0.002563603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038700926,0.00016043008,0.00047115466,0.00037030602,0.000058754755,0.00007720759,0.0003055364,0.048917543,0.0017604571,0.83203536,0.017626133,0.09783023],"study_design_scores_gemma":[0.0000827804,0.0001233536,0.00026446712,0.00010797515,0.00005564805,0.0002134966,0.000078008394,0.121773615,0.0008834011,0.86494476,0.0114442995,0.000028197883],"about_ca_topic_score_codex":0.0023439038,"about_ca_topic_score_gemma":0.0020764195,"teacher_disagreement_score":0.014017683,"about_ca_system_score_codex":0.0031431543,"about_ca_system_score_gemma":0.00277664,"threshold_uncertainty_score":0.046893775},"labels":[],"label_agreement":null},{"id":"W2154430520","doi":"10.5267/j.ijiec.2012.05.006","title":"Introducing mass balancing theorem for network flow maximization","year":2012,"lang":"en","type":"article","venue":"International Journal of Industrial Engineering Computations","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"Leverhulme Trust","keywords":"Maximization; Flow (mathematics); Flow network; Computer science; Mathematical optimization; Mathematics; Mathematical economics; Geometry","score_opus":0.025559305693846873,"score_gpt":0.2647144740999841,"score_spread":0.23915516840613724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154430520","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0022476253,0.0007370326,0.98288935,0.00044874594,0.00019486055,0.00003449068,0.0000832472,0.00015421708,0.013210463],"genre_scores_gemma":[0.39104146,0.00508925,0.57096326,0.001411673,0.0020018746,0.0006838218,0.00036258224,0.0006654067,0.027780619],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99933225,0.0001806241,0.000027099415,0.00014424759,0.00024635397,0.00006947037],"domain_scores_gemma":[0.9991066,0.00054117496,0.000068888956,0.00006432029,0.00018388333,0.000035112425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018801776,0.0010621368,0.00075600116,0.0011389344,0.00067830324,0.0013527961,0.0011200348,0.0009941047,0.0053520924],"category_scores_gemma":[0.003630237,0.00033858107,0.00093804626,0.0011974204,0.001350081,0.0029973714,0.0012385685,0.0015997955,0.0016529993],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007824168,0.000037250542,0.00036824727,0.00028271278,0.00004436294,0.00016565471,0.00016529443,0.15938838,0.009899009,0.7394929,0.012342258,0.077735625],"study_design_scores_gemma":[0.00003654455,0.000099722514,0.00030699885,0.000056495977,0.000025778641,0.0002471583,0.000031128027,0.5328054,0.004338639,0.42427328,0.037749633,0.00002920217],"about_ca_topic_score_codex":0.0011337402,"about_ca_topic_score_gemma":0.0008342643,"teacher_disagreement_score":0.0053520924,"about_ca_system_score_codex":0.0010990498,"about_ca_system_score_gemma":0.000727715,"threshold_uncertainty_score":0.01790452},"labels":[],"label_agreement":null},{"id":"W2154903757","doi":"10.5555/2095116.2095161","title":"Gathering despite mischief","year":2012,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Byzantine architecture; Computer science; Node (physics); Upper and lower bounds; Matching (statistics); Byzantine fault tolerance; Theoretical computer science; Combinatorics; Mathematics; Distributed computing; Fault tolerance; Physics","score_opus":0.018282125697853154,"score_gpt":0.2676465739180216,"score_spread":0.24936444822016846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2154903757","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14746135,0.0005210744,0.8219665,0.0035111979,0.00015282545,0.00030448727,0.00045631864,0.0023312056,0.02329505],"genre_scores_gemma":[0.7301435,0.0003503804,0.25227585,0.0006318966,0.000106548956,0.00032865713,0.00068899576,0.00044688967,0.015027352],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99648416,0.00090784475,0.00020629264,0.0012217651,0.0005384692,0.000641406],"domain_scores_gemma":[0.9819641,0.007132697,0.0017531957,0.006802524,0.0014438856,0.0009035899],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031173518,0.0013535041,0.001363854,0.0006527484,0.0033294174,0.0021787372,0.0031384306,0.0021796653,0.006499572],"category_scores_gemma":[0.020853413,0.0009223937,0.0010596702,0.00094169634,0.0024656972,0.0052553103,0.005333432,0.0023203294,0.0017436751],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002038427,0.00033915363,0.013095159,0.0016241492,0.00038103788,0.0019971565,0.0064050276,0.2808651,0.045264877,0.32389924,0.026682647,0.29740804],"study_design_scores_gemma":[0.00018400111,0.0006146212,0.0027524035,0.0001912497,0.00019486932,0.0014116747,0.001303713,0.64783883,0.024271479,0.26084614,0.060305543,0.00008545243],"about_ca_topic_score_codex":0.0026400052,"about_ca_topic_score_gemma":0.0036170613,"teacher_disagreement_score":0.006499572,"about_ca_system_score_codex":0.0014401211,"about_ca_system_score_gemma":0.0017936417,"threshold_uncertainty_score":0.021743178},"labels":[],"label_agreement":null},{"id":"W2155019050","doi":"10.5555/1070432.1070485","title":"Sharing the cost more efficiently: improved approximation for multicommodity rent-or-buy","year":2005,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Approximation algorithm; Steiner tree problem; Mathematical optimization; Computer science; Provisioning; Terminal (telecommunication); Facility location problem; Mathematics; Computer network","score_opus":0.05440469364136382,"score_gpt":0.3212056976264048,"score_spread":0.266801003985041,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155019050","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06303345,0.0021833517,0.91719836,0.0012544548,0.00015433376,0.00022043311,0.0003449152,0.0016835743,0.013927019],"genre_scores_gemma":[0.49345985,0.00075635285,0.49642068,0.00050425035,0.00014224065,0.0002635179,0.0005908021,0.0005089293,0.0073534115],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981736,0.0005458724,0.000057175377,0.00022550159,0.00047891992,0.00051894377],"domain_scores_gemma":[0.9980956,0.001126501,0.00014557061,0.00037564393,0.00014498856,0.00011169538],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022201175,0.0017567212,0.002786242,0.00089534174,0.0007308456,0.0018134871,0.0029803554,0.0017668608,0.006785599],"category_scores_gemma":[0.0062770634,0.0008135104,0.0012429814,0.0018508249,0.0008089762,0.0044562803,0.0021776345,0.0028864283,0.0012570891],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00067107845,0.0004160156,0.0010252044,0.00023632855,0.00007681103,0.00014472757,0.00016331142,0.8532783,0.0025707271,0.039492603,0.009157102,0.09276773],"study_design_scores_gemma":[0.000033434022,0.000048568156,0.00007321595,0.000011763901,0.000011604935,0.00004159396,0.000024813095,0.98478794,0.00037882497,0.013310372,0.0012721358,0.00000577048],"about_ca_topic_score_codex":0.006904064,"about_ca_topic_score_gemma":0.009194554,"teacher_disagreement_score":0.006904064,"about_ca_system_score_codex":0.0024656304,"about_ca_system_score_gemma":0.0020639356,"threshold_uncertainty_score":0.022700071},"labels":[],"label_agreement":null},{"id":"W2156452360","doi":"10.1109/iccis.2006.252228","title":"Determining Optimal Polling Frequency Using a Learning Automata-based Solution to the Fractional Knapsack Problem","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Knapsack problem; Mathematical optimization; Discretization; Learning automata; Computer science; Function (biology); Resource allocation; Polling; Mathematics; Automaton; Theoretical computer science","score_opus":0.027641683471281864,"score_gpt":0.27590614067623437,"score_spread":0.2482644572049525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156452360","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.044656925,0.00008498951,0.9520726,0.00015773733,0.000035346857,0.00008499364,0.00003183519,0.00034604757,0.0025296698],"genre_scores_gemma":[0.8332139,0.000062025094,0.16493031,0.00008250976,0.000018197265,0.00015541946,0.00004648097,0.000038954637,0.001452185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994105,0.00013111105,0.00004688432,0.00016261809,0.00015204202,0.00009676572],"domain_scores_gemma":[0.9977203,0.0013695443,0.00028453834,0.00021644161,0.00026511188,0.0001441317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010431644,0.0006377809,0.0010968684,0.00052797486,0.0006328108,0.0011346661,0.0015724188,0.0014413099,0.0020220976],"category_scores_gemma":[0.0053902734,0.00036267753,0.00054116297,0.0003767672,0.0010069204,0.0009494147,0.001177767,0.0011713018,0.00026581914],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00004924883,0.000037987073,0.00062378275,0.000028166989,0.00001425809,0.000041471038,0.00006587293,0.9745404,0.0018584923,0.0056658923,0.00020378236,0.016870564],"study_design_scores_gemma":[0.0000051355005,0.000009094852,0.000027967244,0.0000019984227,0.0000019676822,0.0000056829417,0.0000047837825,0.99867487,0.0002610139,0.0009269918,0.00007822273,0.0000023339944],"about_ca_topic_score_codex":0.005589906,"about_ca_topic_score_gemma":0.0053783273,"teacher_disagreement_score":0.005589906,"about_ca_system_score_codex":0.0009524867,"about_ca_system_score_gemma":0.0015296995,"threshold_uncertainty_score":0.0111147165},"labels":[],"label_agreement":null},{"id":"W2156655069","doi":"10.1109/icra.2013.6630995","title":"Fair subdivision of multi-robot tasks","year":2013,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Task (project management); Robot; Subdivision; Computer science; Fair division; Function (biology); Division (mathematics); Motion planning; Preference; Task analysis; Robot kinematics; Mathematical optimization; Artificial intelligence; Mobile robot; Mathematics; Engineering","score_opus":0.03386560444709738,"score_gpt":0.2758191579590691,"score_spread":0.2419535535119717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156655069","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07529944,0.00025306328,0.9207942,0.0002986555,0.000041297262,0.00014270065,0.00004304092,0.00014478568,0.0029828919],"genre_scores_gemma":[0.8835375,0.00017960141,0.1100838,0.0000657111,0.00005278706,0.0002764776,0.00007036479,0.00007640124,0.005657395],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99709916,0.001265396,0.00009423163,0.0005020329,0.0004678633,0.0005712947],"domain_scores_gemma":[0.9936539,0.004201961,0.0004676198,0.00078967505,0.00033255355,0.00055430166],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052011213,0.0010737773,0.0019129061,0.00075327855,0.0011471289,0.0015421764,0.0023402828,0.0012360075,0.0038916976],"category_scores_gemma":[0.012076485,0.00054865936,0.0009180803,0.0009162513,0.0025981066,0.0038357999,0.0022320142,0.0014411076,0.0004040312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004364764,0.00012336498,0.00072099554,0.00008466469,0.00004369772,0.000119743345,0.00031139285,0.8680772,0.00263079,0.0891503,0.00087913213,0.03742234],"study_design_scores_gemma":[0.000044528137,0.00007819875,0.00015931942,0.0000073615806,0.0000115364055,0.0000283536,0.000057440495,0.9162909,0.0010247973,0.0814765,0.0008124806,0.000008535016],"about_ca_topic_score_codex":0.0035592166,"about_ca_topic_score_gemma":0.0022761542,"teacher_disagreement_score":0.0052011213,"about_ca_system_score_codex":0.0022510504,"about_ca_system_score_gemma":0.0015506654,"threshold_uncertainty_score":0.02750647},"labels":[],"label_agreement":null},{"id":"W2156885983","doi":"10.1007/978-3-319-18263-6_22","title":"Primal-Dual Algorithms for Precedence Constrained Covering Problems","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Knapsack problem; Combinatorics; Mathematics; Cover (algebra); Bounded function; Upper and lower bounds; Antichain; Order (exchange); Discrete mathematics; Integer (computer science); Algorithm; Partially ordered set; Computer science","score_opus":0.05693307988904808,"score_gpt":0.29515101427188606,"score_spread":0.23821793438283798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156885983","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0071708243,0.0020420845,0.9732945,0.00039781607,0.00020337613,0.000073197734,0.0001385901,0.0002834957,0.016396258],"genre_scores_gemma":[0.19056149,0.003231777,0.78674066,0.0003238733,0.00039855263,0.00043676552,0.00056147657,0.00060730363,0.017138168],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992155,0.00031136285,0.000031443564,0.00009520404,0.00023733363,0.000109261855],"domain_scores_gemma":[0.998582,0.000963368,0.00007733947,0.00012921967,0.00015003518,0.00009802018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018470823,0.001829199,0.0016354799,0.00097249437,0.00073281646,0.0022814146,0.002062033,0.0016725216,0.009753322],"category_scores_gemma":[0.0050988146,0.001255418,0.00115256,0.0024233414,0.0010505214,0.0023018639,0.0024996353,0.004444253,0.0015390143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001773292,0.0002876475,0.00030191377,0.00044576684,0.000064504406,0.0000805611,0.000119347154,0.608785,0.0011805109,0.18539898,0.016212089,0.18694642],"study_design_scores_gemma":[0.000038361326,0.00002611902,0.00006632827,0.000046017743,0.000011742053,0.00004599721,0.00002231772,0.89799184,0.00036179507,0.09767019,0.0037116099,0.000007571889],"about_ca_topic_score_codex":0.002004451,"about_ca_topic_score_gemma":0.0023128528,"teacher_disagreement_score":0.009753322,"about_ca_system_score_codex":0.0015023636,"about_ca_system_score_gemma":0.0015006614,"threshold_uncertainty_score":0.03262812},"labels":[],"label_agreement":null},{"id":"W2157076224","doi":"10.5555/1661445.1661506","title":"Interruptible algorithms for multiproblem solving","year":2009,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Schedule; Foreknowledge; Scheduling (production processes); Computation; Algorithm; Processor scheduling; Job shop scheduling; Quality (philosophy); Mathematical optimization; Mathematics","score_opus":0.024700001194537267,"score_gpt":0.2634747051448908,"score_spread":0.23877470395035352,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157076224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0070781973,0.0014263975,0.9784532,0.0005950623,0.00040954287,0.00006326013,0.00007851481,0.0009652722,0.010930517],"genre_scores_gemma":[0.2524591,0.0018074557,0.7137537,0.00051744614,0.0008336667,0.0005720981,0.00053088344,0.00085250544,0.028673185],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99844754,0.0005437342,0.00009215073,0.00024741143,0.0004663445,0.00020283964],"domain_scores_gemma":[0.99345136,0.0047260113,0.000317278,0.00080226146,0.00041223023,0.00029088426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027491343,0.0018191783,0.0020887593,0.000919923,0.0011183514,0.0023192975,0.0030670073,0.0016178349,0.015402857],"category_scores_gemma":[0.013692846,0.0007858348,0.0014018655,0.0016314128,0.0021041639,0.002886401,0.0022553082,0.0063385074,0.0022560281],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011213605,0.0003648134,0.00062344817,0.0010502299,0.0001165035,0.00016035227,0.00040025057,0.39509407,0.002568965,0.3556384,0.022731023,0.2201306],"study_design_scores_gemma":[0.00019849844,0.00008500322,0.00011834485,0.00006162086,0.000028176433,0.000051582047,0.000031901964,0.7114957,0.0006798607,0.2776162,0.009617252,0.000015931699],"about_ca_topic_score_codex":0.0026873401,"about_ca_topic_score_gemma":0.0029559743,"teacher_disagreement_score":0.015402857,"about_ca_system_score_codex":0.0017596605,"about_ca_system_score_gemma":0.001344238,"threshold_uncertainty_score":0.05152768},"labels":[],"label_agreement":null},{"id":"W2157321916","doi":"10.1109/tsmcb.2005.863379","title":"Parameter learning from stochastic teachers and stochastic compulsive liars","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Oracle; Learning automata; Computer science; Point (geometry); Artificial intelligence; Interval (graph theory); Mechanism (biology); Automaton; Machine learning; Mathematics; Epistemology","score_opus":0.0175080524577038,"score_gpt":0.22762643723040316,"score_spread":0.21011838477269934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157321916","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17057656,0.0001749049,0.82359004,0.0005611221,0.000029724288,0.0000828858,0.000035251338,0.00037999405,0.004569519],"genre_scores_gemma":[0.9654256,0.000067032306,0.031643912,0.000111991736,0.000025011335,0.00007226249,0.000028770633,0.000024469211,0.002600993],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982016,0.00077332056,0.00011921969,0.00036972115,0.0003356399,0.00020035563],"domain_scores_gemma":[0.992359,0.0043007615,0.0012865594,0.0011024474,0.00047008198,0.00048105596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023240724,0.00067735335,0.0009546498,0.00044522394,0.00051412504,0.0011749314,0.0015883656,0.0017652644,0.0016772345],"category_scores_gemma":[0.013625398,0.00043980248,0.0006074358,0.00032146904,0.0025593548,0.002706354,0.0025601683,0.0016167253,0.00032149538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036993707,0.000118310956,0.003929607,0.00014304792,0.00008607157,0.00041702567,0.0006805609,0.80982876,0.0060071,0.13639578,0.00050458615,0.041519273],"study_design_scores_gemma":[0.000031880696,0.00014312784,0.00029211506,0.000012532603,0.000013918987,0.00008184544,0.000049543163,0.9572766,0.001617071,0.039854188,0.0006038883,0.000023253675],"about_ca_topic_score_codex":0.0010897845,"about_ca_topic_score_gemma":0.00084021816,"teacher_disagreement_score":0.0023240724,"about_ca_system_score_codex":0.0008170113,"about_ca_system_score_gemma":0.0008591164,"threshold_uncertainty_score":0.012291014},"labels":[],"label_agreement":null},{"id":"W2157761976","doi":"10.1016/j.ejor.2004.01.049","title":"Data dependent worst case bounds for weighted set packing","year":2004,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of New Brunswick","funders":"","keywords":"Set (abstract data type); Computer science; Mathematical optimization; Set packing; Combinatorics; Mathematics; Algorithm","score_opus":0.28979600900726327,"score_gpt":0.4341920657037415,"score_spread":0.14439605669647826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2157761976","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042728893,0.0063247387,0.92246026,0.0027803201,0.0007384968,0.00030121458,0.0021258325,0.002011884,0.020528372],"genre_scores_gemma":[0.5665932,0.007265119,0.3949328,0.0013612293,0.0017573542,0.0013419727,0.005414968,0.0032974787,0.018035758],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97639287,0.0054414347,0.0013069547,0.002352017,0.009923524,0.0045832093],"domain_scores_gemma":[0.8969759,0.07210405,0.005101367,0.016557213,0.0066298298,0.002631657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017708357,0.006639587,0.0053013344,0.0052146884,0.0024522254,0.011715862,0.011809486,0.0038339093,0.015762849],"category_scores_gemma":[0.08146263,0.0035197136,0.0029846134,0.009810497,0.0036971522,0.023360027,0.010730854,0.009676977,0.004039347],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024774084,0.00063553336,0.0016125316,0.0009572562,0.0002742543,0.00022482287,0.000361604,0.77370936,0.006882399,0.087320134,0.016334346,0.10921033],"study_design_scores_gemma":[0.000046701505,0.00019711388,0.00031147627,0.000111142705,0.000099591685,0.0001591343,0.000095133786,0.89701587,0.003606114,0.09552557,0.0027837718,0.00004844203],"about_ca_topic_score_codex":0.0027875924,"about_ca_topic_score_gemma":0.0033883,"teacher_disagreement_score":0.017708357,"about_ca_system_score_codex":0.00593103,"about_ca_system_score_gemma":0.004238696,"threshold_uncertainty_score":0.09365189},"labels":[],"label_agreement":null},{"id":"W2160650170","doi":"","title":"Cache-Oblivious Output-Sensitive Two-Dimensional Convex Hull","year":2007,"lang":"en","type":"article","venue":"Canadian Conference on Computational Geometry","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Convex hull; Cache; Cache-oblivious algorithm; Parallel computing; Combinatorics; Computer science; Cache algorithms; Block size; CPU cache; Algorithm; Mathematics; Regular polygon; Geometry; Key (lock)","score_opus":0.03535666633472642,"score_gpt":0.27830733210590486,"score_spread":0.24295066577117844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2160650170","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08008767,0.00014066827,0.9168314,0.00024198793,0.00002188466,0.000046613022,0.000243264,0.00033865529,0.0020479574],"genre_scores_gemma":[0.82863945,0.00018324144,0.1666007,0.00008625216,0.000043586755,0.00011845172,0.00075850677,0.00020963665,0.0033601637],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989384,0.00027493146,0.00005169766,0.00017810376,0.00040506994,0.00015178973],"domain_scores_gemma":[0.99706227,0.0015299078,0.0003074766,0.00063301943,0.00033801148,0.00012931447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011190397,0.0010227116,0.0015689363,0.00052146974,0.0005576568,0.0015738396,0.001698255,0.00096514873,0.0016037204],"category_scores_gemma":[0.005621097,0.00054467487,0.0011322761,0.0012846647,0.0014288116,0.0022240935,0.0021842895,0.001500252,0.00027885204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000104160914,0.000024769852,0.00038861358,0.000050110633,0.000025925674,0.00009482196,0.00005162623,0.97904474,0.0017812153,0.0067463038,0.00061168463,0.0110761],"study_design_scores_gemma":[0.0000069879347,0.000028803566,0.00009822522,0.0000031994625,0.0000037937893,0.00002399867,0.000013414921,0.9907562,0.001495992,0.0074083568,0.00015579644,0.0000051543],"about_ca_topic_score_codex":0.0029198257,"about_ca_topic_score_gemma":0.001605226,"teacher_disagreement_score":0.0029198257,"about_ca_system_score_codex":0.0013328482,"about_ca_system_score_gemma":0.00077979284,"threshold_uncertainty_score":0.009670556},"labels":[],"label_agreement":null},{"id":"W2161327891","doi":"10.1109/mass.2011.90","title":"On the Complexity of the Multi-Robot, Multi-Depot Map Visitation Problem","year":2011,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Robot; Computer science; Focus (optics); Variety (cybernetics); Graph; Boundary (topology); Mobile robot; Artificial intelligence; Computational complexity theory; Theoretical computer science; Algorithm; Mathematics","score_opus":0.20354168223318253,"score_gpt":0.2978061462751105,"score_spread":0.09426446404192795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161327891","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2551503,0.0030244014,0.6768614,0.015170122,0.0002772298,0.0003892925,0.0021327552,0.0008279861,0.046166528],"genre_scores_gemma":[0.76820403,0.0028530427,0.21378022,0.00096401694,0.0004649753,0.0005934768,0.002223861,0.0004565171,0.010459919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977235,0.0008116552,0.00009428776,0.000465344,0.000525074,0.00038007172],"domain_scores_gemma":[0.98066026,0.016693972,0.00077330077,0.00080859027,0.0005402957,0.00052354945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019452798,0.0010275289,0.0016220934,0.00094021705,0.0017838242,0.004308919,0.0018828829,0.0021606188,0.006486625],"category_scores_gemma":[0.014867748,0.0007311371,0.0013989432,0.0018777739,0.0019376932,0.008282855,0.0027127515,0.0035447364,0.0007142894],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061649963,0.0003578817,0.003469458,0.0006737439,0.00015244017,0.00047560324,0.00074886816,0.6406766,0.0024619405,0.27475062,0.020420844,0.05519553],"study_design_scores_gemma":[0.00010140973,0.000045022793,0.00091517693,0.000042482363,0.000044359116,0.0001770399,0.0002734661,0.65083474,0.000629613,0.34255475,0.0043534623,0.000028484807],"about_ca_topic_score_codex":0.005045852,"about_ca_topic_score_gemma":0.0047625373,"teacher_disagreement_score":0.006486625,"about_ca_system_score_codex":0.0029256202,"about_ca_system_score_gemma":0.0022723458,"threshold_uncertainty_score":0.021699905},"labels":[],"label_agreement":null},{"id":"W2161493293","doi":"10.1109/crv.2009.30","title":"Optimal Online Data Sampling or How to Hire the Best Secretaries","year":2009,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Generalization; Sampling (signal processing); Sample (material); Selection (genetic algorithm); Secretary problem; Simple (philosophy); Artificial intelligence; Machine learning; Online algorithm; Sequence (biology); Data mining; Mathematical optimization; Algorithm; Mathematics; Computer vision","score_opus":0.17328021812413524,"score_gpt":0.3577267200153544,"score_spread":0.18444650189121914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161493293","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02962643,0.0007478544,0.96575904,0.0014983623,0.00008583643,0.00019656494,0.00023210939,0.00047890737,0.0013749652],"genre_scores_gemma":[0.49573737,0.0007241078,0.4970505,0.00069909514,0.0004026838,0.000483256,0.00073863746,0.00023747924,0.003926909],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961862,0.0019180208,0.00020660418,0.00094022293,0.00043642774,0.00031246446],"domain_scores_gemma":[0.98111355,0.013835106,0.001190564,0.002825391,0.0004985011,0.0005369722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005829754,0.00094144914,0.0025199002,0.0008053941,0.0010019434,0.00212548,0.0023802083,0.0024766098,0.0038592736],"category_scores_gemma":[0.025137128,0.0007365036,0.0011837251,0.0013479064,0.0029486935,0.0048410287,0.0022156686,0.0021638914,0.0010353506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028454405,0.0010082552,0.009353417,0.0010951136,0.00042542888,0.000326164,0.00075413927,0.30352923,0.015139609,0.11814174,0.015813472,0.53156793],"study_design_scores_gemma":[0.00024516985,0.00038184726,0.001370951,0.00007079265,0.0000923474,0.000312124,0.0002656895,0.77472526,0.010181288,0.20729117,0.004991399,0.00007196949],"about_ca_topic_score_codex":0.0010527546,"about_ca_topic_score_gemma":0.0014149279,"teacher_disagreement_score":0.005829754,"about_ca_system_score_codex":0.0009378644,"about_ca_system_score_gemma":0.0022342901,"threshold_uncertainty_score":0.030831039},"labels":[],"label_agreement":null},{"id":"W2162964807","doi":"10.1109/tsmcb.2006.879012","title":"Learning Automata-Based Solutions to the Nonlinear Fractional Knapsack Problem With Applications to Optimal Resource Allocation","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":99,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Knapsack problem; Computer science; Learning automata; Discretization; Resource allocation; Scheme (mathematics); Mathematical optimization; Polling; Theoretical computer science; Automaton; Algorithm; Mathematics","score_opus":0.02106864386116119,"score_gpt":0.2554649759567687,"score_spread":0.2343963320956075,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2162964807","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008990971,0.0002800403,0.9866736,0.00022614922,0.000054588625,0.00003995854,0.00002773946,0.000176855,0.0035301328],"genre_scores_gemma":[0.61304426,0.0005710667,0.38049147,0.00022427923,0.00008593276,0.0003724389,0.000110954395,0.00010206022,0.0049975286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995036,0.00015658388,0.000040596122,0.00010666449,0.00011863489,0.00007377977],"domain_scores_gemma":[0.9976107,0.0017133552,0.00019567688,0.00013617317,0.00024950484,0.00009465998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011348088,0.0008083358,0.0009844978,0.000620897,0.0006644397,0.0012698832,0.0012830488,0.0015509304,0.0031332162],"category_scores_gemma":[0.005410684,0.00042746353,0.0007701335,0.0005911478,0.0013184022,0.0010654574,0.0016752221,0.0017947645,0.00039042777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019607674,0.000022430928,0.0002605983,0.000047785925,0.0000130960025,0.000031930827,0.00005376965,0.96179765,0.00054477353,0.020772576,0.00029934384,0.016136536],"study_design_scores_gemma":[0.0000031814147,0.000010051888,0.000019998766,0.000004968392,0.000002140244,0.0000057718457,0.000007516758,0.9924314,0.00015449907,0.0070512677,0.00030594144,0.0000033320089],"about_ca_topic_score_codex":0.0054399306,"about_ca_topic_score_gemma":0.0053209276,"teacher_disagreement_score":0.0054399306,"about_ca_system_score_codex":0.000985288,"about_ca_system_score_gemma":0.0013049273,"threshold_uncertainty_score":0.010816574},"labels":[],"label_agreement":null},{"id":"W2163134916","doi":"10.1016/j.tcs.2015.09.025","title":"Fast rendezvous with advice","year":2015,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rendezvous; Computer science; Oracle; Advice (programming); Set (abstract data type); Node (physics); Upper and lower bounds; Integer (computer science); String (physics); Algorithm; Mathematics","score_opus":0.01677587884675006,"score_gpt":0.25703540298749517,"score_spread":0.2402595241407451,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163134916","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.107675426,0.0008272554,0.8055499,0.0012774038,0.00073822035,0.0002494312,0.00089314533,0.03579978,0.046989396],"genre_scores_gemma":[0.6306136,0.00028979796,0.32826447,0.00032674687,0.00014302925,0.00017351923,0.0009591762,0.0031083534,0.036121305],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99851245,0.0002659301,0.00006198094,0.00027023954,0.0005636225,0.00032579582],"domain_scores_gemma":[0.9951821,0.0018855343,0.000118496995,0.0020731029,0.0005746955,0.00016610877],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012673059,0.0012059882,0.0013567874,0.0011076359,0.0014430027,0.0012907246,0.0016659494,0.001693833,0.023292786],"category_scores_gemma":[0.011450511,0.00062237616,0.000739351,0.00095638825,0.0012971183,0.0024104468,0.0035954795,0.0018565429,0.005891641],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0042210105,0.00020572162,0.003943278,0.0006989734,0.00021642026,0.0009663183,0.0011791522,0.08708825,0.032357726,0.12817308,0.0713514,0.6695986],"study_design_scores_gemma":[0.000584448,0.00026299758,0.0010247726,0.00014497619,0.00014680254,0.0006349189,0.00049151195,0.67394555,0.038315095,0.22874932,0.055607144,0.000092493385],"about_ca_topic_score_codex":0.006025072,"about_ca_topic_score_gemma":0.008573192,"teacher_disagreement_score":0.023292786,"about_ca_system_score_codex":0.00065608294,"about_ca_system_score_gemma":0.0012495434,"threshold_uncertainty_score":0.077922106},"labels":[],"label_agreement":null},{"id":"W2164204765","doi":"10.1108/17563780911005881","title":"Graph exploration with robot swarms","year":2009,"lang":"en","type":"article","venue":"International Journal of Intelligent Computing and Cybernetics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Swarm behaviour; Swarm robotics; Computer science; Robot; Correctness; Ant robotics; Graph; Simultaneous localization and mapping; Artificial intelligence; Robotics; Theoretical computer science; Algorithm; Mobile robot; Robot control","score_opus":0.021746895593147433,"score_gpt":0.2855692519064286,"score_spread":0.2638223563132812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164204765","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12334792,0.0005369224,0.86228335,0.0007589369,0.00009659269,0.00015807312,0.00011433085,0.00088344625,0.011820408],"genre_scores_gemma":[0.81969726,0.00032269245,0.17518738,0.00010065864,0.00003446487,0.00015228816,0.00015767546,0.00008541387,0.0042621735],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994918,0.00021732917,0.000016895141,0.000102195634,0.000114945266,0.000056786666],"domain_scores_gemma":[0.9985728,0.00082640897,0.00013932797,0.00020810949,0.00013779027,0.000115552895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006759849,0.00048030983,0.00062834757,0.0006303612,0.00058014534,0.0011650743,0.0009963029,0.0006217824,0.0023547357],"category_scores_gemma":[0.0029586116,0.00030066108,0.0006526072,0.0005972184,0.0010448631,0.001608863,0.001514229,0.00062832783,0.0003064595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000982157,0.000043085714,0.0010719202,0.000117105585,0.000056377514,0.00010333418,0.00025893646,0.9082984,0.0028807588,0.05576892,0.0011718782,0.03013116],"study_design_scores_gemma":[0.000023756835,0.00005912475,0.0001835792,0.000010803035,0.000009519955,0.00004076689,0.00008698089,0.96008146,0.0007164019,0.035938412,0.0028412326,0.000007917355],"about_ca_topic_score_codex":0.0030216977,"about_ca_topic_score_gemma":0.0021168867,"teacher_disagreement_score":0.0030216977,"about_ca_system_score_codex":0.00079500914,"about_ca_system_score_gemma":0.0008009517,"threshold_uncertainty_score":0.007877409},"labels":[],"label_agreement":null},{"id":"W2164399703","doi":"10.1007/978-3-540-92862-1_11","title":"Deployment of Asynchronous Robotic Sensors in Unknown Orthogonal Environments","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Asynchronous communication; Visibility; Computer science; RADIUS; Software deployment; Mobile robot; Space (punctuation); Distributed computing; Real-time computing; Robot; Artificial intelligence; Computer network; Physics; Operating system","score_opus":0.018289782234800583,"score_gpt":0.23551771006421018,"score_spread":0.2172279278294096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164399703","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08753444,0.0002908151,0.9049108,0.00017610354,0.00012423373,0.00003884656,0.00006787079,0.0003285811,0.00652844],"genre_scores_gemma":[0.8231354,0.00047860475,0.16961177,0.000058146346,0.000094635274,0.000088616776,0.00013254199,0.000049892453,0.0063504167],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958795,0.00010561235,0.000020075551,0.00011157973,0.00011554841,0.000059309525],"domain_scores_gemma":[0.99935824,0.00025915145,0.00010448601,0.0001106216,0.00009001761,0.00007750743],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004935688,0.00064404367,0.00062113645,0.00031339496,0.00040583464,0.0006804772,0.00090947445,0.0006021463,0.0010512026],"category_scores_gemma":[0.0018926564,0.00046976286,0.0002401249,0.00058004056,0.0006374017,0.0013492152,0.0017679073,0.00057567545,0.0004048188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010015895,0.00017020419,0.0017722665,0.00021027136,0.00005299711,0.00029983016,0.000245377,0.73589116,0.054011006,0.04229393,0.002713363,0.16133809],"study_design_scores_gemma":[0.000045080065,0.00019944432,0.00045400998,0.000010309756,0.000014933294,0.00007671567,0.00005779812,0.98019284,0.0071227276,0.009929923,0.0018814664,0.000014639319],"about_ca_topic_score_codex":0.00071292586,"about_ca_topic_score_gemma":0.0012368131,"teacher_disagreement_score":0.0010512026,"about_ca_system_score_codex":0.00032389996,"about_ca_system_score_gemma":0.0004041974,"threshold_uncertainty_score":0.003516674},"labels":[],"label_agreement":null},{"id":"W2165056932","doi":"10.1109/tsmcb.2007.912744","title":"Video-on-Demand Network Design and Maintenance Using Fuzzy Optimization","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Research Manitoba","funders":"","keywords":"Computer science; Problem statement; Fuzzy logic; Process (computing); Function (biology); Heuristic; Bundle; Cache; Mathematical optimization; Statement (logic); Optimization problem; Order (exchange); Operations research; Algorithm; Artificial intelligence; Computer network; Mathematics; Engineering; Management science","score_opus":0.042047637074989576,"score_gpt":0.24412478032640683,"score_spread":0.20207714325141726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165056932","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022195023,0.00040249046,0.9702612,0.00017251799,0.000039286824,0.00009397037,0.000044564527,0.00014014075,0.0066508376],"genre_scores_gemma":[0.8111324,0.0005824911,0.18300454,0.00008297517,0.000042236945,0.00021874874,0.00009196242,0.000054852553,0.004789748],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971586,0.0000690789,0.000013220048,0.00006624443,0.00008817632,0.00004742053],"domain_scores_gemma":[0.9995926,0.00019206759,0.000054979497,0.00001723165,0.00011412993,0.000029070467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00075738603,0.0007450525,0.00082189596,0.00070816255,0.0005961126,0.0011623224,0.0014927036,0.0012793641,0.0021587177],"category_scores_gemma":[0.0013059083,0.00047290878,0.00067648693,0.00060308486,0.00049762265,0.0008209391,0.00065552513,0.00069597823,0.00020419204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002875261,0.000028352772,0.00021757296,0.000042285574,0.000012453188,0.000036838544,0.000026926939,0.97754467,0.0018158125,0.0032398896,0.00040405823,0.016602335],"study_design_scores_gemma":[0.0000027406586,0.000013436173,0.00003055113,0.0000021941228,0.0000036765746,0.000006720089,0.000006038763,0.99909997,0.00018911979,0.0005040216,0.0001398536,0.0000017520186],"about_ca_topic_score_codex":0.009100775,"about_ca_topic_score_gemma":0.0068028807,"teacher_disagreement_score":0.009100775,"about_ca_system_score_codex":0.0015243915,"about_ca_system_score_gemma":0.0010380282,"threshold_uncertainty_score":0.018095613},"labels":[],"label_agreement":null},{"id":"W2165265954","doi":"10.1109/ccc.1997.612318","title":"On randomization in online computation","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Randomized algorithm; Bounding overwatch; Online algorithm; Computer science; Maximization; Bounded function; Equivalence (formal languages); Competitive analysis; Randomized experiment; Computation; Theoretical computer science; Algorithm; Mathematics; Mathematical optimization; Artificial intelligence; Discrete mathematics; Upper and lower bounds; Statistics","score_opus":0.033799906852864846,"score_gpt":0.27200543788645154,"score_spread":0.2382055310335867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2165265954","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0148041975,0.0046867067,0.93482393,0.008837201,0.00062925194,0.00017885045,0.00020891198,0.00081354484,0.035017334],"genre_scores_gemma":[0.64878446,0.007410424,0.30977803,0.0063383807,0.0035862846,0.0016360374,0.0004652273,0.00095133256,0.021049824],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98610467,0.007435249,0.0005559196,0.002012125,0.002789926,0.0011021252],"domain_scores_gemma":[0.95416313,0.037526134,0.001165934,0.0051308507,0.0014233204,0.0005906801],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010172653,0.0012272332,0.0019304134,0.0014046445,0.0018577697,0.0043416996,0.0029042775,0.003156661,0.007570292],"category_scores_gemma":[0.04884364,0.0008329208,0.0017354725,0.002475271,0.009509353,0.013889775,0.0043125437,0.00733359,0.0016766303],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000066377186,0.000034610133,0.00020794378,0.00008974875,0.00001856319,0.000027768654,0.000057460722,0.014285704,0.0002910703,0.9713997,0.0020105331,0.011510462],"study_design_scores_gemma":[0.000046443296,0.000039282204,0.00009430629,0.00003540485,0.0000126095,0.00003203,0.0000147009905,0.060060594,0.0004290042,0.93415934,0.005060782,0.000015331449],"about_ca_topic_score_codex":0.0013327014,"about_ca_topic_score_gemma":0.00088955555,"teacher_disagreement_score":0.010172653,"about_ca_system_score_codex":0.0035255873,"about_ca_system_score_gemma":0.0029874695,"threshold_uncertainty_score":0.053798735},"labels":[],"label_agreement":null},{"id":"W2168718726","doi":"10.1109/spdp.1995.530717","title":"Competitive dynamic multiprocessor allocation for parallel applications","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Preemption; Multiprocessor scheduling; Multiprocessing; Computer science; Parallel computing; Scheduling (production processes); Job shop scheduling; Competitive analysis; Processor scheduling; Execution time; Distributed computing; Upper and lower bounds; Flow shop scheduling; Mathematical optimization; Operating system; Schedule; Mathematics","score_opus":0.026572515656617446,"score_gpt":0.27737270082422893,"score_spread":0.2508001851676115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168718726","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04620285,0.00559586,0.9144027,0.0011957485,0.00023965289,0.0001276061,0.000091512666,0.0003277607,0.03181622],"genre_scores_gemma":[0.8665449,0.0031010457,0.12233134,0.00029437043,0.0002434091,0.0002772763,0.00012516526,0.00015269182,0.0069297994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985511,0.0005184251,0.000035089022,0.00011637227,0.00056603434,0.00021294964],"domain_scores_gemma":[0.9974853,0.0018167312,0.0001660576,0.00010422794,0.0003226604,0.00010506886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016184049,0.0008768924,0.0010018498,0.00082823506,0.0010258313,0.0019962178,0.00105882,0.0009821741,0.0026642694],"category_scores_gemma":[0.0061307983,0.0004156758,0.00047765166,0.0012753918,0.0011402587,0.001421288,0.0009680723,0.0011086051,0.0005782948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001183432,0.00006866091,0.00047980316,0.0002337482,0.00004993945,0.00014424573,0.00009914233,0.56885445,0.002871391,0.37983188,0.0049665263,0.04228188],"study_design_scores_gemma":[0.000012459278,0.000029298872,0.00011019256,0.000007724419,0.000008418334,0.000053207637,0.000019759187,0.9251347,0.00040056833,0.07050706,0.003708878,0.0000076635615],"about_ca_topic_score_codex":0.0045184707,"about_ca_topic_score_gemma":0.0035654828,"teacher_disagreement_score":0.0045184707,"about_ca_system_score_codex":0.0025627716,"about_ca_system_score_gemma":0.0020416016,"threshold_uncertainty_score":0.018594325},"labels":[],"label_agreement":null},{"id":"W2168975199","doi":"10.5555/1898699.1898769","title":"Optimal map construction of an unknown torus","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Torus; Security token; Node (physics); Enhanced Data Rates for GSM Evolution; Computer science; Multi-agent system; Mathematics; Algorithm; Combinatorics; Topology (electrical circuits); Discrete mathematics; Artificial intelligence; Geometry; Computer network; Physics","score_opus":0.009185106305420774,"score_gpt":0.23622643331773757,"score_spread":0.2270413270123168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168975199","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23784812,0.00022616594,0.74581414,0.00052004255,0.00007424395,0.00015745562,0.00027179281,0.00076469046,0.014323314],"genre_scores_gemma":[0.6634723,0.00021189966,0.32618892,0.000047898615,0.000030347304,0.00016342837,0.00042272455,0.00017030985,0.009292241],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995167,0.0001299638,0.000020002191,0.00013176694,0.000081105114,0.000120347824],"domain_scores_gemma":[0.99894625,0.0005683413,0.00011847537,0.0001849519,0.00008653464,0.000095439435],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052502076,0.0005378351,0.00079761795,0.000395378,0.00097361516,0.0009519355,0.0011486312,0.0008792455,0.0044076955],"category_scores_gemma":[0.0028468557,0.00045326498,0.00068558514,0.0005414728,0.0011696345,0.002522559,0.0015700362,0.0007678589,0.0006198833],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035019417,0.00009609854,0.0009098179,0.0002819369,0.000042897827,0.0007174624,0.00035369117,0.8488031,0.005684283,0.09204428,0.0036893059,0.04702692],"study_design_scores_gemma":[0.00005144015,0.00011956021,0.00026483732,0.000014134997,0.000021810003,0.00016451589,0.0002749398,0.9212644,0.0037708543,0.06960897,0.0044224923,0.000021969641],"about_ca_topic_score_codex":0.002952905,"about_ca_topic_score_gemma":0.0022665714,"teacher_disagreement_score":0.0044076955,"about_ca_system_score_codex":0.0009633482,"about_ca_system_score_gemma":0.0011452307,"threshold_uncertainty_score":0.014745235},"labels":[],"label_agreement":null},{"id":"W2170631384","doi":"10.1007/978-3-642-17461-2_5","title":"Time Optimal Algorithms for Black Hole Search in Rings","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University; University of Ottawa","funders":"","keywords":"Asynchronous communication; Computer science; Focus (optics); Black hole (networking); Ring (chemistry); Algorithm; Upper and lower bounds; Search problem; Ring network; Asymptotically optimal algorithm; Time complexity; Mathematics; Physics; Routing (electronic design automation); Network topology; Computer network","score_opus":0.02585653393387138,"score_gpt":0.28064994063781584,"score_spread":0.25479340670394446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170631384","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04464845,0.0020706854,0.91604644,0.0010774682,0.0002854492,0.00024591095,0.00044581623,0.002253914,0.032925848],"genre_scores_gemma":[0.29287606,0.0011786622,0.68529546,0.00036829416,0.00024897847,0.00043354314,0.00077941973,0.0008172908,0.018002344],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99854386,0.00045060305,0.00007974724,0.00027595717,0.00036181914,0.0002879979],"domain_scores_gemma":[0.99642533,0.0024554124,0.00016675114,0.0005993422,0.0001785263,0.00017459044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018090095,0.001574682,0.0018249864,0.0012117173,0.001293267,0.0028950365,0.0031591181,0.0020815728,0.012409109],"category_scores_gemma":[0.0086091235,0.000829407,0.0013179384,0.002199504,0.0021239188,0.006271385,0.0026733023,0.0030112178,0.002085348],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010013068,0.000333743,0.00052828353,0.00064027467,0.00012271281,0.00006662782,0.00046048322,0.21932182,0.0037411074,0.55320185,0.027049063,0.19353268],"study_design_scores_gemma":[0.00025221953,0.00007952343,0.00013866196,0.000046713045,0.000047517948,0.00004949121,0.000101395315,0.41111422,0.0013569092,0.58221555,0.0045743287,0.000023362034],"about_ca_topic_score_codex":0.002245314,"about_ca_topic_score_gemma":0.0033876994,"teacher_disagreement_score":0.012409109,"about_ca_system_score_codex":0.0021278365,"about_ca_system_score_gemma":0.002087127,"threshold_uncertainty_score":0.041512668},"labels":[],"label_agreement":null},{"id":"W2171151410","doi":"10.1142/s021819590200089x","title":"ONLINE ROUTING IN CONVEX SUBDIVISIONS","year":2002,"lang":"en","type":"article","venue":"International Journal of Computational Geometry & Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Carleton University","funders":"","keywords":"Delaunay triangulation; Mathematics; Combinatorics; Destination-Sequenced Distance Vector routing; Discrete mathematics; Computer science; Mathematical optimization; Link-state routing protocol; Routing (electronic design automation); Computer network","score_opus":0.030471045598837843,"score_gpt":0.3160281218117496,"score_spread":0.28555707621291176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2171151410","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14399546,0.00059974845,0.8355576,0.00094530074,0.000111756955,0.00016863053,0.00026947155,0.00090756826,0.017444469],"genre_scores_gemma":[0.7442155,0.0006537161,0.24399143,0.00028810304,0.00008704552,0.00017415687,0.0007331432,0.00021087236,0.009646043],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99887544,0.0002926744,0.000043874395,0.00023176863,0.0003081724,0.00024814045],"domain_scores_gemma":[0.9975183,0.001210169,0.0002869354,0.0006065618,0.00020407593,0.00017395715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00068915397,0.0007537984,0.0012766764,0.00047662336,0.0009516389,0.0016390396,0.0020502722,0.0013533932,0.006324033],"category_scores_gemma":[0.005175292,0.00045186377,0.00072742725,0.0013212438,0.0013218272,0.0038924594,0.0020143115,0.0012498022,0.0009825897],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004249297,0.00020481426,0.0007686151,0.00014597183,0.00004264649,0.00024805535,0.00020071954,0.75900567,0.00573207,0.13366619,0.005470956,0.0940894],"study_design_scores_gemma":[0.00003042125,0.00005796987,0.000114800605,0.000007549381,0.0000113333845,0.00007322951,0.00005352376,0.9157707,0.0015837407,0.07900921,0.0032792066,0.000008306505],"about_ca_topic_score_codex":0.0037184355,"about_ca_topic_score_gemma":0.0034788654,"teacher_disagreement_score":0.006324033,"about_ca_system_score_codex":0.0014395041,"about_ca_system_score_gemma":0.0007526073,"threshold_uncertainty_score":0.021155953},"labels":[],"label_agreement":null},{"id":"W2172011606","doi":"10.1109/tencon.1990.152584","title":"The ship model-a new computational model for distributed systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"University of Washington","keywords":"Computer science; Locality; Code (set theory); Computation; Distributed computing; Telecommunications network; Work (physics); Computer network; Programming language; Engineering","score_opus":0.09684850345121622,"score_gpt":0.2785134781629585,"score_spread":0.1816649747117423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2172011606","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014177852,0.00054086954,0.98047286,0.0012954841,0.00025898614,0.0000827127,0.00026198052,0.00070701697,0.014962376],"genre_scores_gemma":[0.14453185,0.0040644966,0.79900813,0.0012885439,0.0008965519,0.0011860529,0.0014605725,0.0010931987,0.046470594],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849033,0.00034627668,0.000119862016,0.00024842785,0.00064161065,0.00015350891],"domain_scores_gemma":[0.99893934,0.00029886534,0.00007262219,0.00037006408,0.00020486348,0.000114246825],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014037357,0.0009901635,0.0011485661,0.00079960685,0.0011327671,0.0042207735,0.0032011776,0.0018900756,0.008065764],"category_scores_gemma":[0.0028683846,0.00072966743,0.0018178333,0.0015524043,0.0020433764,0.007236976,0.003064837,0.003162724,0.0031457085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035689547,0.00002506537,0.0002542667,0.000123949,0.00003003181,0.00013075178,0.00021230982,0.10629211,0.0009186496,0.8553938,0.014909314,0.021673981],"study_design_scores_gemma":[0.00005927388,0.00003318998,0.00007911053,0.000052466738,0.000029708544,0.0001345528,0.00005759608,0.41906565,0.00109033,0.38919762,0.1901737,0.000026761407],"about_ca_topic_score_codex":0.004315739,"about_ca_topic_score_gemma":0.0036512287,"teacher_disagreement_score":0.008065764,"about_ca_system_score_codex":0.0016734678,"about_ca_system_score_gemma":0.003099361,"threshold_uncertainty_score":0.026982665},"labels":[],"label_agreement":null},{"id":"W2174619083","doi":"10.1016/j.tcs.2012.07.033","title":"On the competitiveness of AIMD-TCP within a general network","year":2012,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bottleneck; Computer science; Router; Competitive analysis; Scheduling (production processes); Multiplicative function; Computer network; Distributed computing; Set (abstract data type); Mathematical optimization; Upper and lower bounds; Mathematics","score_opus":0.016616668126334232,"score_gpt":0.2587536619840035,"score_spread":0.2421369938576693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2174619083","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6866076,0.006484038,0.14860597,0.014485009,0.00072027766,0.00029511517,0.0012985291,0.0011631706,0.1403403],"genre_scores_gemma":[0.97589386,0.0011620522,0.017587274,0.0004429083,0.00035114368,0.000110732035,0.00035819778,0.00033670836,0.0037571364],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9940813,0.0026636808,0.00014506647,0.0006955554,0.00089819613,0.0015161983],"domain_scores_gemma":[0.9186272,0.06747824,0.0023300431,0.003785927,0.0036543577,0.004124267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01143976,0.001273027,0.0032811002,0.0027450884,0.0030102432,0.006268224,0.0041194004,0.0031606006,0.0136747025],"category_scores_gemma":[0.061300695,0.00068223465,0.0013242005,0.0027603328,0.0043527167,0.008601524,0.0054697283,0.004653493,0.0011249305],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003971361,0.000495386,0.0066799386,0.0006899657,0.00022750592,0.00031586914,0.0005242729,0.52105474,0.0046573356,0.40389138,0.019327208,0.038165007],"study_design_scores_gemma":[0.00018789421,0.00033893107,0.0012633312,0.00007634317,0.000112525624,0.00019453293,0.0003512506,0.848144,0.0014579678,0.14484861,0.0029856584,0.00003901824],"about_ca_topic_score_codex":0.005054626,"about_ca_topic_score_gemma":0.004612284,"teacher_disagreement_score":0.0136747025,"about_ca_system_score_codex":0.0039381,"about_ca_system_score_gemma":0.0052536484,"threshold_uncertainty_score":0.060499907},"labels":[],"label_agreement":null},{"id":"W2174851824","doi":"10.1016/j.tcs.2012.01.035","title":"More efficient periodic traversal in anonymous undirected graphs","year":2012,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Tree traversal; Undirected graph; Combinatorics; Graph; Set (abstract data type); Node (physics); Computer science; Mathematics; Period length; Discrete mathematics; Time complexity; Integer (computer science); Binary logarithm; Algorithm","score_opus":0.010685658302965768,"score_gpt":0.2572362291670868,"score_spread":0.24655057086412105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2174851824","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55093354,0.0004992486,0.41277155,0.0016356289,0.00029374694,0.00021979702,0.0010804951,0.0033638082,0.029202059],"genre_scores_gemma":[0.7578777,0.00020888784,0.22653846,0.00028298175,0.00009862975,0.00011157377,0.0014339881,0.0004637224,0.012983971],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895084,0.00028117764,0.00006488503,0.0002151889,0.00024576398,0.00024202738],"domain_scores_gemma":[0.99599046,0.001480084,0.0002973611,0.0017390742,0.00027297824,0.00022010924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010975339,0.00041788546,0.0009583073,0.0009493311,0.0009943661,0.0017427324,0.001498418,0.001009336,0.0097468775],"category_scores_gemma":[0.006227811,0.00042569847,0.0006778377,0.0016248572,0.0005696551,0.00366213,0.0014568336,0.0011212165,0.0010965221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020801432,0.0012422336,0.0047670933,0.0006115383,0.00013911838,0.0008042407,0.000990949,0.29860687,0.030374356,0.31245005,0.036978174,0.31095526],"study_design_scores_gemma":[0.00021114075,0.00020464347,0.00071860495,0.00003637081,0.000069799025,0.00034051848,0.000264194,0.78399223,0.007293672,0.19742595,0.009407923,0.000034963756],"about_ca_topic_score_codex":0.0029030377,"about_ca_topic_score_gemma":0.0077554155,"teacher_disagreement_score":0.0097468775,"about_ca_system_score_codex":0.001018125,"about_ca_system_score_gemma":0.0016133814,"threshold_uncertainty_score":0.032606542},"labels":[],"label_agreement":null},{"id":"W2177060007","doi":"10.1609/icaps.v21i1.13467","title":"Closing the Gap: Improved Bounds on Optimal POMDP Solutions","year":2011,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Automated Planning and Scheduling","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":50,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology; University of Waterloo","funders":"","keywords":"Upper and lower bounds; Sawtooth wave; Benchmark (surveying); Partially observable Markov decision process; Mathematical optimization; Bellman equation; Function (biology); Interpolation (computer graphics); Computer science; Grid; Linear programming; Mathematics; Markov decision process; Markov process; Artificial intelligence","score_opus":0.11260743891545368,"score_gpt":0.30147540917280535,"score_spread":0.1888679702573517,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2177060007","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014042606,0.001251603,0.9737225,0.00060793664,0.00012912869,0.00008317846,0.00023467324,0.0008081527,0.00912012],"genre_scores_gemma":[0.45404533,0.001729639,0.5380231,0.00053872255,0.00020898234,0.0005931359,0.0006994277,0.000750541,0.0034112243],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99484444,0.0014693796,0.00025791058,0.00073463697,0.0020697708,0.000623869],"domain_scores_gemma":[0.98378515,0.012635459,0.0007268854,0.0015244492,0.0010208387,0.00030718505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006392614,0.0025299124,0.0023678006,0.002145246,0.0010541485,0.0035089166,0.002879291,0.002346559,0.007614249],"category_scores_gemma":[0.032973014,0.0015874532,0.0019756265,0.0021858998,0.0026656014,0.0070765126,0.0048034503,0.0061255298,0.00090796524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015132762,0.000055456137,0.00030975466,0.00018308306,0.00003564066,0.000056685225,0.00014958771,0.8976502,0.00069089147,0.06732286,0.001785608,0.03160899],"study_design_scores_gemma":[0.000020088155,0.000034403754,0.000056008033,0.00006820095,0.00001164463,0.0000095942805,0.00002224099,0.9470762,0.00048191668,0.051063206,0.0011482851,0.000008235039],"about_ca_topic_score_codex":0.005978278,"about_ca_topic_score_gemma":0.0060312664,"teacher_disagreement_score":0.007614249,"about_ca_system_score_codex":0.003056564,"about_ca_system_score_gemma":0.0033632051,"threshold_uncertainty_score":0.033807755},"labels":[],"label_agreement":null},{"id":"W2179376195","doi":"10.1016/j.tcs.2012.07.004","title":"Gathering asynchronous oblivious agents with local vision in regular bipartite graphs","year":2012,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Computer science; Snapshot (computer storage); Asynchronous communication; Bipartite graph; Existential quantification; Theoretical computer science; Graph; Algorithm; Mathematics; Combinatorics; Computer network","score_opus":0.010246317737841494,"score_gpt":0.2581444462834714,"score_spread":0.2478981285456299,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2179376195","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2141423,0.00017084672,0.7765846,0.0007429762,0.00004861025,0.00019000309,0.00011216492,0.00056850177,0.007440015],"genre_scores_gemma":[0.92086685,0.00010750242,0.073549576,0.00015854937,0.00004328781,0.00020154918,0.00012519318,0.00009780593,0.0048497026],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99871314,0.00053137314,0.000051898987,0.00028238757,0.00018537683,0.00023581227],"domain_scores_gemma":[0.99334407,0.0042779986,0.0007306016,0.0006601651,0.00041172802,0.00057538686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018746858,0.00083318393,0.0018082528,0.0010253296,0.0015032334,0.0018534572,0.0027075512,0.0019184356,0.0026689528],"category_scores_gemma":[0.010467876,0.00091611425,0.00084418623,0.0011109832,0.0017971275,0.003264669,0.003656932,0.0015328191,0.00044776895],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000970403,0.00033814058,0.0016131086,0.00031828837,0.00017356008,0.00036786043,0.0006531538,0.8060565,0.00818641,0.14469267,0.003223827,0.033406094],"study_design_scores_gemma":[0.000053754404,0.0000599879,0.000114817434,0.000006885276,0.000017931185,0.000027275926,0.000058089,0.93779045,0.0006915818,0.060895372,0.00027358104,0.000010359678],"about_ca_topic_score_codex":0.0031364905,"about_ca_topic_score_gemma":0.0037455661,"teacher_disagreement_score":0.0031364905,"about_ca_system_score_codex":0.0012591921,"about_ca_system_score_gemma":0.0012472116,"threshold_uncertainty_score":0.009914398},"labels":[],"label_agreement":null},{"id":"W2180374207","doi":"","title":"Competitive Online Routing in Geometric Graphs.","year":2001,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Delaunay triangulation; Combinatorics; Mathematics; Discrete mathematics","score_opus":0.03010317574189894,"score_gpt":0.2796664929349582,"score_spread":0.24956331719305927,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2180374207","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053259317,0.0014292719,0.92232835,0.0010163405,0.00015016363,0.00017806796,0.00021771865,0.0004543869,0.020966377],"genre_scores_gemma":[0.72029406,0.0016360452,0.26813108,0.0005370244,0.00028117088,0.00026956003,0.00037718235,0.00012644131,0.008347352],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99883085,0.0003779767,0.000034445296,0.0002180902,0.000323428,0.00021523715],"domain_scores_gemma":[0.9972656,0.0017136488,0.00030759003,0.00033829617,0.00021364535,0.00016134228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008554852,0.0008607595,0.0008467242,0.0005358625,0.0009008466,0.0017264023,0.0024130624,0.0017441174,0.0054799607],"category_scores_gemma":[0.0051233014,0.0003865024,0.0005753131,0.0012276267,0.0011373075,0.0036141083,0.0012539404,0.0009842804,0.0008326208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034473723,0.0002906469,0.0011283321,0.00043587014,0.00010376121,0.00045184966,0.00020520148,0.44786993,0.0055865813,0.4346119,0.011298269,0.09767297],"study_design_scores_gemma":[0.000051806892,0.00013298381,0.00020439221,0.00001322931,0.000032841832,0.00032323282,0.00007674392,0.819167,0.0016204786,0.16879696,0.009563495,0.000016730926],"about_ca_topic_score_codex":0.0034774425,"about_ca_topic_score_gemma":0.0034341314,"teacher_disagreement_score":0.0054799607,"about_ca_system_score_codex":0.0015317533,"about_ca_system_score_gemma":0.0008472585,"threshold_uncertainty_score":0.018332303},"labels":[],"label_agreement":null},{"id":"W2184486309","doi":"10.1109/trustcom-bigdatase-ispa.2015.436","title":"RLTE: A Reinforcement Learning Based Trust Establishment Model","year":2015,"lang":"en","type":"article","venue":"Trust, Security And Privacy In Computing And Communications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Honesty; Reputation; Reinforcement learning; Computer science; Trustworthiness; Order (exchange); Reinforcement; Work (physics); Artificial intelligence; Psychology; Social psychology; Computer security; Business; Law; Political science; Engineering; Finance","score_opus":0.07272068516223065,"score_gpt":0.32425605605119723,"score_spread":0.2515353708889666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2184486309","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03641086,0.00046747454,0.9505129,0.0010221713,0.00012441627,0.0001571153,0.00024309602,0.000762102,0.010299943],"genre_scores_gemma":[0.92929804,0.0003930205,0.060340382,0.00015871167,0.00005135791,0.00029131555,0.00022363839,0.000042282947,0.009201163],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988518,0.00039562877,0.00007945408,0.00027400223,0.0002440792,0.0001550499],"domain_scores_gemma":[0.99828136,0.00082899764,0.0002758712,0.000087779816,0.00037422212,0.0001517537],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013147778,0.0007734387,0.001006508,0.00043691523,0.00057504314,0.0013157611,0.0021724622,0.0012688598,0.004456678],"category_scores_gemma":[0.004084887,0.00036248725,0.0006918224,0.0003943532,0.0007136158,0.0017174785,0.0013082598,0.0018159222,0.00073983165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017776029,0.00014333356,0.001981267,0.000111738525,0.00008723534,0.00036727733,0.00019285706,0.9222893,0.0014016769,0.03331407,0.002197601,0.037735824],"study_design_scores_gemma":[0.00001799634,0.000040748488,0.000120194636,0.000006226336,0.000014878797,0.000033121556,0.0000103701295,0.9933774,0.00014467178,0.005452262,0.0007745018,0.0000076502465],"about_ca_topic_score_codex":0.010327017,"about_ca_topic_score_gemma":0.007483251,"teacher_disagreement_score":0.010327017,"about_ca_system_score_codex":0.0014362412,"about_ca_system_score_gemma":0.0016835773,"threshold_uncertainty_score":0.0205338},"labels":[],"label_agreement":null},{"id":"W2187039192","doi":"10.1007/978-3-642-40450-4_54","title":"Better Approximation Algorithms for Technology Diffusion","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Rounding; Cascade; Algorithm; Computer science; Vertex (graph theory); Graph; Upgrade; Approximation algorithm; Combinatorics; Binary logarithm; Discrete mathematics; Mathematics; Theoretical computer science","score_opus":0.020519532145419746,"score_gpt":0.2565089051580965,"score_spread":0.23598937301267675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2187039192","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006686496,0.0038309474,0.9717747,0.0020580855,0.00058922364,0.000059227346,0.00025235472,0.00070474506,0.014044351],"genre_scores_gemma":[0.1969434,0.006667522,0.7493474,0.0011559877,0.0011608637,0.00036286502,0.0010390979,0.00095723086,0.04236567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99791926,0.0008368856,0.000116691815,0.00031716222,0.0005866067,0.00022337718],"domain_scores_gemma":[0.9942075,0.003488728,0.00027969683,0.0012724542,0.0005568566,0.00019477053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035902334,0.001858112,0.0025591918,0.001928619,0.0009157142,0.003374787,0.0033632815,0.0029627488,0.014445972],"category_scores_gemma":[0.017687742,0.0008741706,0.0021327252,0.004249935,0.001750066,0.008464339,0.0023310683,0.0065187677,0.0024611696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018389722,0.00014236657,0.00042502402,0.00026782573,0.00009512608,0.000044212386,0.00014963349,0.17812756,0.0008596864,0.62880987,0.027146196,0.16374853],"study_design_scores_gemma":[0.000058418434,0.00002577986,0.00014226507,0.000044125118,0.00003540724,0.00005245877,0.000031977925,0.50265616,0.00036898025,0.48607072,0.010499257,0.00001446424],"about_ca_topic_score_codex":0.004208432,"about_ca_topic_score_gemma":0.0036502834,"teacher_disagreement_score":0.014445972,"about_ca_system_score_codex":0.0032200774,"about_ca_system_score_gemma":0.0017660555,"threshold_uncertainty_score":0.048326552},"labels":[],"label_agreement":null},{"id":"W2188070220","doi":"10.22215/etd/2014-10430","title":"Swarms of Bouncing Robots","year":2014,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Mobile robot; Task (project management); Visibility; Computer science; Position (finance); Collision; Simulation; Real-time computing; Artificial intelligence; Engineering; Geography; Computer security","score_opus":0.013545356539366601,"score_gpt":0.2669274243338533,"score_spread":0.2533820677944867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2188070220","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39999992,0.0034047775,0.5610225,0.002324224,0.0007267059,0.00023049525,0.0005235434,0.00042054817,0.031347297],"genre_scores_gemma":[0.9498443,0.0015982783,0.028710343,0.00025035083,0.00029534765,0.0002321075,0.0004703081,0.00006483183,0.01853415],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995641,0.00010487694,0.000023075701,0.00011904453,0.00009269598,0.00009617187],"domain_scores_gemma":[0.99862516,0.00055424194,0.00034193072,0.00009154883,0.00013395616,0.00025320775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044123485,0.001451932,0.0012901938,0.0007759417,0.0009922751,0.0020088062,0.0024680651,0.0021123164,0.0028869582],"category_scores_gemma":[0.003687895,0.00073305017,0.00082624506,0.00067955395,0.0017696281,0.0019523565,0.0015901566,0.0012471064,0.0004572028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018225101,0.00010951837,0.0037635977,0.00018359495,0.0001693015,0.00062749546,0.0003689415,0.8653478,0.0030574908,0.11465235,0.0033042163,0.008233482],"study_design_scores_gemma":[0.000059749094,0.00009005056,0.0005054591,0.000020465568,0.00002816126,0.000064050575,0.00011054184,0.96815854,0.00020190857,0.028386202,0.002356975,0.000017951057],"about_ca_topic_score_codex":0.0067781596,"about_ca_topic_score_gemma":0.0036460112,"teacher_disagreement_score":0.0067781596,"about_ca_system_score_codex":0.0007868475,"about_ca_system_score_gemma":0.00051105494,"threshold_uncertainty_score":0.013477385},"labels":[],"label_agreement":null},{"id":"W2202720387","doi":"10.1007/978-3-662-46078-8_16","title":"Deterministic Rendezvous in Restricted Graphs","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Rendezvous; Traverse; Robot; Computer science; Asynchronous communication; Graph; Discrete mathematics; Topology (electrical circuits); Mobile robot; Theoretical computer science; Node (physics); Combinatorics; Reachability; Algorithm; Mathematics; Artificial intelligence; Computer network; Physics","score_opus":0.03973797012185137,"score_gpt":0.28057701449587374,"score_spread":0.24083904437402237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2202720387","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23615289,0.002293593,0.62568206,0.00118706,0.00031705253,0.00018722731,0.00096655305,0.0024679492,0.13074557],"genre_scores_gemma":[0.8773852,0.0016660198,0.06875574,0.00018294368,0.00011228391,0.00020965177,0.0008060414,0.0008101715,0.05007196],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99929595,0.00015851654,0.000027920447,0.00020530574,0.0001533283,0.00015899588],"domain_scores_gemma":[0.9978855,0.0012131657,0.00012872736,0.0005299585,0.00010783767,0.00013475197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047935755,0.00065822556,0.0011513836,0.00070451945,0.0012759757,0.0014782773,0.0019015807,0.001049485,0.009027622],"category_scores_gemma":[0.0036063278,0.0007424166,0.0007469901,0.0010808649,0.0018693694,0.0031218494,0.0025814774,0.0018516505,0.0017903493],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032782674,0.000044382312,0.00030004795,0.0003576121,0.000046153342,0.00019776337,0.00034908493,0.13788722,0.0055064904,0.80329144,0.007850004,0.043842074],"study_design_scores_gemma":[0.000055297976,0.0000336052,0.00016382344,0.000054061475,0.000024277742,0.00016157841,0.00013781693,0.18885946,0.0031275302,0.79695123,0.01040152,0.000029749426],"about_ca_topic_score_codex":0.0025260001,"about_ca_topic_score_gemma":0.0029526073,"teacher_disagreement_score":0.009027622,"about_ca_system_score_codex":0.0010687648,"about_ca_system_score_gemma":0.00062191446,"threshold_uncertainty_score":0.030200422},"labels":[],"label_agreement":null},{"id":"W2207300025","doi":"10.1016/j.comgeo.2010.04.003","title":"A general approach for cache-oblivious range reporting and approximate range counting","year":2010,"lang":"en","type":"article","venue":"Computational Geometry","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Range (aeronautics); Range query (database); Cache; Upper and lower bounds; Computer science; Mathematics; Linear space; Corollary; Data structure; Block (permutation group theory); Combinatorics; Web search query; Parallel computing; Sargable; Search engine; Information retrieval","score_opus":0.03599642114052546,"score_gpt":0.29118629184087824,"score_spread":0.25518987070035276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2207300025","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0017332417,0.00047792896,0.9907506,0.0006874682,0.00014747687,0.00012093355,0.0002025967,0.0005451339,0.005334681],"genre_scores_gemma":[0.16217595,0.0018752973,0.81357664,0.001215013,0.0010438706,0.0010710331,0.0008232243,0.00091404543,0.017304989],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.990854,0.0022713002,0.00059405604,0.0018378804,0.0034797837,0.00096296804],"domain_scores_gemma":[0.9863929,0.0047942325,0.0005579686,0.006498261,0.0014336355,0.0003229597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048296894,0.0024204738,0.0039602234,0.0035351017,0.0026996918,0.007298486,0.010538022,0.0041841688,0.011527764],"category_scores_gemma":[0.025619164,0.0016087336,0.0037246908,0.00880075,0.0039893496,0.018729974,0.010476978,0.008456079,0.0031024683],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001299552,0.00011910413,0.0002693276,0.00026987348,0.00008343517,0.000075438445,0.00017896743,0.055467412,0.0020279184,0.8584455,0.013056428,0.0698766],"study_design_scores_gemma":[0.00003217019,0.00004656079,0.00009862494,0.000046491037,0.00006964929,0.00017974363,0.000051297622,0.29143965,0.0019519046,0.69497365,0.011061684,0.00004853678],"about_ca_topic_score_codex":0.002989659,"about_ca_topic_score_gemma":0.003674965,"teacher_disagreement_score":0.011527764,"about_ca_system_score_codex":0.0038507732,"about_ca_system_score_gemma":0.0045901695,"threshold_uncertainty_score":0.038564265},"labels":[],"label_agreement":null},{"id":"W2211969678","doi":"10.1007/s10878-015-9915-5","title":"Towards the price of leasing online","year":2015,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Deutsche Forschungsgemeinschaft; Deutscher Akademischer Austauschdienst","keywords":"Theory of computation; Order (exchange); Set cover problem; Integer programming; Online algorithm; Computer science; Integer (computer science); Randomized rounding; Operations research; Set (abstract data type); Mathematical economics; Facility location problem; Service (business); Mathematics; Combinatorics; Approximation algorithm; Economics; Algorithm; Business; Marketing; Finance","score_opus":0.04894002924072742,"score_gpt":0.2914331280640873,"score_spread":0.24249309882335984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2211969678","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1294422,0.0037865818,0.4425961,0.031517062,0.0012966064,0.00014410206,0.000418396,0.00051062607,0.39028832],"genre_scores_gemma":[0.9083461,0.0012889764,0.0405599,0.0010589098,0.00087128556,0.00007869653,0.00011926473,0.0002771111,0.047399785],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99771035,0.000995782,0.00006813175,0.00027853012,0.0007235568,0.00022354095],"domain_scores_gemma":[0.98801184,0.00883919,0.00056310644,0.00095598,0.0011349219,0.0004949223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032359445,0.0006716554,0.0015336842,0.0012808692,0.0015646637,0.008378579,0.0027420437,0.0055369916,0.028529994],"category_scores_gemma":[0.033686616,0.0010434501,0.0006803948,0.0017024535,0.0031009363,0.017318336,0.00238316,0.006656217,0.0024737301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020639817,0.00013652445,0.00096936576,0.000114609116,0.000025226032,0.0001368866,0.00012987386,0.018766785,0.0006723924,0.93330073,0.01081001,0.034731247],"study_design_scores_gemma":[0.00003025756,0.000037688624,0.00030053162,0.000045638128,0.000017793644,0.00012165677,0.0001543126,0.10837405,0.00042606104,0.8839855,0.0064843525,0.000022172993],"about_ca_topic_score_codex":0.0017040953,"about_ca_topic_score_gemma":0.0021421167,"teacher_disagreement_score":0.028529994,"about_ca_system_score_codex":0.0030604154,"about_ca_system_score_gemma":0.001608916,"threshold_uncertainty_score":0.095442355},"labels":[],"label_agreement":null},{"id":"W2216175676","doi":"10.1109/cit/iucc/dasc/picom.2015.254","title":"Distributed Black Virus Decontamination and Rooted Acyclic Orientations","year":2015,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Carleton University","funders":"","keywords":"Asynchronous communication; Network topology; Computer science; Topology (electrical circuits); Graph; Distributed computing; Computer network; Mathematics; Theoretical computer science; Combinatorics","score_opus":0.03641267515240541,"score_gpt":0.2880084743089313,"score_spread":0.25159579915652586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2216175676","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1248978,0.00027334903,0.8681553,0.0003700527,0.00003586355,0.00013964577,0.00012132253,0.00046248714,0.0055442196],"genre_scores_gemma":[0.7848598,0.000321448,0.20995824,0.00010374701,0.000026906011,0.00013098975,0.00026878095,0.00009724209,0.0042328937],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916875,0.00027835715,0.000030795978,0.0001833771,0.00018581316,0.0001528163],"domain_scores_gemma":[0.99777347,0.0009855228,0.0005435423,0.00033636205,0.00017208372,0.00018896599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000778558,0.0005078965,0.0005079369,0.0005835993,0.0007151605,0.00097426755,0.0010721637,0.0006548991,0.0017947091],"category_scores_gemma":[0.0036874516,0.00032135533,0.00039175505,0.00069680024,0.0013126532,0.0016946234,0.0014015897,0.0008463721,0.00024971846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003108412,0.00016545186,0.0020759408,0.00019240213,0.00004522063,0.00017993848,0.00036676024,0.7306358,0.01689911,0.16476664,0.0023458009,0.082016155],"study_design_scores_gemma":[0.000045178378,0.00009406064,0.00055163883,0.000019882456,0.000019604548,0.00008488575,0.0001714038,0.89683324,0.006601015,0.09138501,0.004176114,0.00001801315],"about_ca_topic_score_codex":0.0034263183,"about_ca_topic_score_gemma":0.0047399485,"teacher_disagreement_score":0.0034263183,"about_ca_system_score_codex":0.0012548023,"about_ca_system_score_gemma":0.001115918,"threshold_uncertainty_score":0.009104252},"labels":[],"label_agreement":null},{"id":"W2231632241","doi":"10.1145/2611462.2611473","title":"Time versus cost tradeoffs for deterministic rendezvous in networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Computer science; Node (physics); Idle; Set (abstract data type); Integer (computer science); Distributed computing; Computer network; Integer programming; Algorithm; Engineering","score_opus":0.03129674999225843,"score_gpt":0.2795022712355432,"score_spread":0.2482055212432848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2231632241","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.473587,0.0076968754,0.45410976,0.005906413,0.00039365832,0.00031286842,0.00072796975,0.00070224045,0.056563154],"genre_scores_gemma":[0.9584228,0.0015485116,0.03368145,0.0001667419,0.00011985574,0.00014080902,0.00015023747,0.00021355187,0.005556073],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996792,0.0014063513,0.00010265089,0.00034583805,0.0007611925,0.0005919284],"domain_scores_gemma":[0.9751251,0.021270571,0.0010159378,0.0010238882,0.00071496237,0.0008495167],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005549104,0.0012717878,0.001246172,0.0014583603,0.001396115,0.0026791503,0.0017751211,0.0019190793,0.007447411],"category_scores_gemma":[0.027195605,0.0007472887,0.00058573834,0.0013989,0.0020391808,0.005200953,0.0018778918,0.0013044967,0.0006549394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013488687,0.00012501859,0.00079186965,0.00025160308,0.00006316617,0.000086654516,0.00018858457,0.8768,0.0037502123,0.08169035,0.0026469298,0.032256704],"study_design_scores_gemma":[0.00010065125,0.00029179367,0.00055709505,0.00004518223,0.00004704885,0.00011179744,0.00016621289,0.9172779,0.0013620049,0.07823117,0.0017739176,0.000035216322],"about_ca_topic_score_codex":0.0023855735,"about_ca_topic_score_gemma":0.0026802183,"teacher_disagreement_score":0.007447411,"about_ca_system_score_codex":0.0031339107,"about_ca_system_score_gemma":0.0016934098,"threshold_uncertainty_score":0.029346824},"labels":[],"label_agreement":null},{"id":"W2245527669","doi":"10.1007/978-3-319-19662-6_14","title":"Rendezvous of Many Agents with Different Speeds in a Cycle","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Rendezvous; Generalization; Combinatorics; Domain (mathematical analysis); Mathematics; Computer science; Discrete mathematics; Algorithm; Physics; Mathematical analysis","score_opus":0.03558802351668162,"score_gpt":0.27119062136414945,"score_spread":0.23560259784746784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2245527669","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43654165,0.001273772,0.46396,0.0007507862,0.00059941807,0.00035549587,0.00029868825,0.0019656187,0.09425463],"genre_scores_gemma":[0.8580254,0.00044765553,0.09770635,0.00011925447,0.00007064225,0.00022983109,0.00028500697,0.00034366696,0.04277213],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994375,0.00008994203,0.000026627513,0.00017717907,0.00014311365,0.00012563218],"domain_scores_gemma":[0.99913967,0.00022367382,0.00006931716,0.00031561448,0.000105383326,0.00014627677],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050804485,0.0007379885,0.0009184854,0.0008644892,0.0018586232,0.0014094635,0.0020100838,0.001331223,0.011030967],"category_scores_gemma":[0.0027376371,0.00065564323,0.00081006426,0.00081767444,0.0013382521,0.0025416648,0.0031587789,0.0010648181,0.0019746546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002663201,0.00026877577,0.003318851,0.00053785695,0.00047347732,0.001378472,0.0017248748,0.23681028,0.05497944,0.47348464,0.008582156,0.21577802],"study_design_scores_gemma":[0.00043869813,0.0006752221,0.0014820995,0.00014548948,0.00021726402,0.0010963271,0.0012762436,0.5671646,0.034671336,0.3160198,0.0766195,0.00019352668],"about_ca_topic_score_codex":0.0019396704,"about_ca_topic_score_gemma":0.0020705163,"teacher_disagreement_score":0.011030967,"about_ca_system_score_codex":0.0005690031,"about_ca_system_score_gemma":0.00062843144,"threshold_uncertainty_score":0.03690225},"labels":[],"label_agreement":null},{"id":"W2267848830","doi":"10.1287/ijoc.2015.0668","title":"An AO<sup>*</sup> Based Exact Algorithm for the Canadian Traveler Problem","year":2016,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tree traversal; Vertex (graph theory); Computer science; Pruning; Mathematical optimization; Algorithm; Markov decision process; Vertex cover; Graph; Graph traversal; Time complexity; Markov process; Theoretical computer science; Mathematics","score_opus":0.025870594288043298,"score_gpt":0.2749130858102049,"score_spread":0.2490424915221616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2267848830","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05225732,0.00047988733,0.8978487,0.002613666,0.0002464923,0.00078708684,0.001797959,0.0054065282,0.03856234],"genre_scores_gemma":[0.24579512,0.00021798069,0.73828804,0.00056628475,0.00007037862,0.0003847366,0.0023025721,0.0005320362,0.011842836],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991947,0.000092140566,0.000036715322,0.00018565715,0.00023031003,0.00026047198],"domain_scores_gemma":[0.99878305,0.00057056284,0.000113197,0.00017381016,0.00024399633,0.000115429495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009295439,0.0010173363,0.0008591269,0.0008523863,0.0010408801,0.0012689818,0.0020515868,0.0011916142,0.011907366],"category_scores_gemma":[0.0039892723,0.00051672646,0.000857276,0.0017005387,0.00082637375,0.0015727122,0.0017292809,0.0015045152,0.0013349099],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046361508,0.00029794298,0.00227559,0.00022894451,0.00005811657,0.00014129514,0.00013328056,0.4911267,0.0023575528,0.059565593,0.04732005,0.3960313],"study_design_scores_gemma":[0.0001066682,0.000043268225,0.00035588568,0.00001840947,0.00001753529,0.00004750639,0.00006211597,0.9661194,0.00092084537,0.026217727,0.0060766786,0.000013955083],"about_ca_topic_score_codex":0.16562338,"about_ca_topic_score_gemma":0.23467684,"teacher_disagreement_score":0.16562338,"about_ca_system_score_codex":0.003582331,"about_ca_system_score_gemma":0.013902706,"threshold_uncertainty_score":0.32931864},"labels":[],"label_agreement":null},{"id":"W2273888011","doi":"10.1007/s13675-015-0059-2","title":"Models for video-on-demand scheduling with costs","year":2016,"lang":"en","type":"article","venue":"EURO Journal on Computational Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Video on demand; Flexibility (engineering); Server; Scheduling (production processes); On demand; Service provider; Bandwidth (computing); Duration (music); Computer network; Service (business); Multimedia; Operations management","score_opus":0.02936711467459411,"score_gpt":0.2708885565075921,"score_spread":0.24152144183299798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2273888011","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034620617,0.0034381307,0.8996765,0.005127135,0.00063195213,0.0003571374,0.0027036793,0.0005487355,0.05289611],"genre_scores_gemma":[0.7236654,0.005597062,0.15986578,0.0009444754,0.0009286292,0.0015127128,0.0025203913,0.0006872502,0.10427829],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985141,0.0005750546,0.00007012397,0.00024054469,0.00028740408,0.00031273736],"domain_scores_gemma":[0.99677557,0.0021066456,0.00032099924,0.00016349973,0.00033532968,0.00029807663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024350062,0.0026960187,0.0019935102,0.0012707508,0.00094717543,0.0032771418,0.004814866,0.003628061,0.015816802],"category_scores_gemma":[0.0078089735,0.0012001472,0.0015217722,0.002292676,0.0013544958,0.0036255952,0.0017596822,0.0029790578,0.002066474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000061963074,0.000054165477,0.00027851184,0.00010301491,0.00002695446,0.00010154052,0.000057467758,0.853755,0.00026275488,0.13608046,0.0043179686,0.00490022],"study_design_scores_gemma":[0.000020828013,0.000013796929,0.00013194981,0.000014417928,0.000010159382,0.000022044947,0.000019462059,0.9434554,0.00005028662,0.053441662,0.0028082887,0.000011767625],"about_ca_topic_score_codex":0.015086608,"about_ca_topic_score_gemma":0.011098626,"teacher_disagreement_score":0.015816802,"about_ca_system_score_codex":0.004138857,"about_ca_system_score_gemma":0.0019072826,"threshold_uncertainty_score":0.052912474},"labels":[],"label_agreement":null},{"id":"W2274293958","doi":"10.1142/s0129054116500313","title":"Exploration of Faulty Hamiltonian Graphs","year":2016,"lang":"en","type":"preprint","venue":"International Journal of Foundations of Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Computer science; Node (physics); Overhead (engineering); Competitive analysis; Situated; Hamiltonian path; Algorithm; Mathematics; Theoretical computer science; Graph; Engineering; Upper and lower bounds; Artificial intelligence","score_opus":0.05308547114641386,"score_gpt":0.3491501009345286,"score_spread":0.2960646297881147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274293958","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55812174,0.0008135163,0.43230975,0.0007823604,0.000047818867,0.00007620206,0.0003598969,0.0004046715,0.0070840437],"genre_scores_gemma":[0.92746764,0.0004556145,0.06876537,0.00008146301,0.00002190545,0.00006025783,0.0002753307,0.00007525917,0.0027972353],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99948895,0.00020291685,0.000019303561,0.0000929528,0.00009514849,0.00010060807],"domain_scores_gemma":[0.9968821,0.0021123057,0.0003634378,0.0003265394,0.00014332816,0.00017235025],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006260868,0.00043046128,0.00054611434,0.0005127337,0.000526532,0.0007038909,0.0009326915,0.0007390283,0.0024359736],"category_scores_gemma":[0.005525019,0.00037933065,0.00049139553,0.0006778916,0.0010494696,0.002014994,0.001312407,0.00052681944,0.00017715328],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023876614,0.00004087125,0.0018134296,0.00016139832,0.00006243442,0.0004886827,0.00023671515,0.92398304,0.004041276,0.04765027,0.0010557047,0.020227516],"study_design_scores_gemma":[0.000030563973,0.000044147393,0.00034373617,0.000011577929,0.000015667238,0.00014485384,0.00011164621,0.8900798,0.001656708,0.1061261,0.0014258336,0.000009317245],"about_ca_topic_score_codex":0.0016115828,"about_ca_topic_score_gemma":0.0013626368,"teacher_disagreement_score":0.0024359736,"about_ca_system_score_codex":0.0007179429,"about_ca_system_score_gemma":0.00044762678,"threshold_uncertainty_score":0.008149147},"labels":[],"label_agreement":null},{"id":"W2274319803","doi":"10.48550/arxiv.1602.05546","title":"Fault and Byzantine Tolerant Self-stabilizing Mobile Robots Gathering - Feasibility Study -","year":2016,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Robot; Stateless protocol; Distributed computing; Probabilistic logic; Scheduling (production processes); Robotics; Fault tolerance; Byzantine fault tolerance; Mobile robot; Set (abstract data type); Bounded function; Swarm robotics; Crash; Artificial intelligence; Algorithm; Mathematical optimization; Mathematics","score_opus":0.08451719605257647,"score_gpt":0.22370100604437393,"score_spread":0.13918380999179747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2274319803","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2093028,0.0019462324,0.76922524,0.0028542222,0.00012535328,0.00035970722,0.0003581839,0.00013129723,0.01569698],"genre_scores_gemma":[0.9511317,0.0010018133,0.044088915,0.000094064235,0.000107873464,0.00021761238,0.00015016091,0.000042085867,0.003165766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977336,0.0013143123,0.0000844823,0.00024896243,0.00038811003,0.00023059653],"domain_scores_gemma":[0.9793099,0.01722114,0.0015587668,0.0004694184,0.0009872038,0.0004535818],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034535893,0.001070999,0.0009303662,0.0011612335,0.00072535925,0.0011828301,0.0014070355,0.0011517495,0.0025729672],"category_scores_gemma":[0.017762952,0.00047873287,0.00096482283,0.0010593584,0.0019319545,0.002793978,0.0016146632,0.0017065121,0.000189406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041557112,0.00020285987,0.003618699,0.00068303867,0.00011665739,0.00060342485,0.0004474375,0.8098722,0.004320253,0.1568575,0.0028474634,0.020014914],"study_design_scores_gemma":[0.000026395774,0.00019275727,0.0007126499,0.000052480245,0.00002492228,0.00012788878,0.00020498993,0.9545328,0.0014141144,0.041119855,0.0015745892,0.000016526468],"about_ca_topic_score_codex":0.0015095077,"about_ca_topic_score_gemma":0.0008585852,"teacher_disagreement_score":0.0034535893,"about_ca_system_score_codex":0.0011847618,"about_ca_system_score_gemma":0.0010576784,"threshold_uncertainty_score":0.018264532},"labels":[],"label_agreement":null},{"id":"W2283577276","doi":"10.1007/978-3-642-35261-4_38","title":"The Canadian Traveller Problem Revisited","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science","score_opus":0.02169896923223257,"score_gpt":0.2440577603377054,"score_spread":0.22235879110547283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2283577276","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042294662,0.008545713,0.02577106,0.031346336,0.0012791828,0.00008838795,0.0012289064,0.00013969389,0.8893062],"genre_scores_gemma":[0.6516061,0.013530682,0.016289983,0.0026535455,0.0008323634,0.00014867124,0.001181959,0.00019667398,0.31356004],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999178,0.00018958496,0.00001869235,0.000114069204,0.00022675552,0.00027285732],"domain_scores_gemma":[0.9990903,0.0003196448,0.000056014436,0.0000802976,0.00023408004,0.0002197094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079800724,0.0008757089,0.0011180722,0.0013610318,0.005393521,0.005663014,0.0029583783,0.0042519355,0.039467186],"category_scores_gemma":[0.0046636905,0.00038215998,0.0007776001,0.0050044563,0.0040976945,0.0040634978,0.0018781474,0.004011524,0.0016536226],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000032362674,0.0000163623,0.00011547398,0.000050951327,0.00001117697,0.00007712823,0.00011357189,0.0037374897,0.000033860724,0.9448184,0.041417476,0.009575732],"study_design_scores_gemma":[0.000058595917,0.000017243357,0.0006242451,0.000146246,0.000030226782,0.0002802213,0.0015970514,0.013504672,0.00013163629,0.80816203,0.17539324,0.00005457351],"about_ca_topic_score_codex":0.5202329,"about_ca_topic_score_gemma":0.51376337,"teacher_disagreement_score":0.5202329,"about_ca_system_score_codex":0.014297226,"about_ca_system_score_gemma":0.015566276,"threshold_uncertainty_score":0.96518505},"labels":[],"label_agreement":null},{"id":"W2284684210","doi":"10.1016/j.tcs.2020.01.031","title":"Paid exchanges are worth the price","year":2020,"lang":"en","type":"preprint","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Agence Nationale de la Recherche","keywords":"Business; Economics","score_opus":0.03455886438842057,"score_gpt":0.2758827443001755,"score_spread":0.24132387991175494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2284684210","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0040079923,0.0064843493,0.011456538,0.09320297,0.08851812,0.00021416227,0.0024469262,0.003158416,0.7905106],"genre_scores_gemma":[0.016092626,0.0011681598,0.0014776334,0.004147741,0.0058046607,0.0000720061,0.0008112813,0.0009202227,0.96950555],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971999,0.0004081712,0.00012625323,0.00055394514,0.0013334396,0.00037832707],"domain_scores_gemma":[0.9905764,0.0019320779,0.000608965,0.002034271,0.0029883941,0.0018599051],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001970466,0.0013468817,0.002289493,0.0016659239,0.0024660644,0.009940402,0.001742301,0.009459159,0.4553242],"category_scores_gemma":[0.025930136,0.000968159,0.0010563838,0.0023532363,0.0017346357,0.012210518,0.0027639198,0.00742276,0.35860902],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003389779,0.00010429097,0.00036755597,0.00008739995,0.000027787715,0.00017868399,0.0000736659,0.00036327814,0.00054329046,0.09074823,0.8052277,0.10193911],"study_design_scores_gemma":[0.00005214059,0.000031893884,0.00043526242,0.000059930226,0.000012049504,0.0001679953,0.00008314151,0.0005533802,0.00012693269,0.019164734,0.97928977,0.000022866314],"about_ca_topic_score_codex":0.0018908071,"about_ca_topic_score_gemma":0.0025187992,"teacher_disagreement_score":0.4553242,"about_ca_system_score_codex":0.0020162745,"about_ca_system_score_gemma":0.0020543311,"threshold_uncertainty_score":0.7769139},"labels":[],"label_agreement":null},{"id":"W2288393983","doi":"10.1016/j.tcs.2016.01.025","title":"Rendezvous with constant memory","year":2016,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education, Culture, Sports, Science and Technology","keywords":"Rendezvous; Constant (computer programming); Robot; Computer science; Asynchronous communication; Transmission (telecommunications); State (computer science); Mobile robot; Theoretical computer science; Algorithm; Artificial intelligence; Computer network; Telecommunications; Programming language","score_opus":0.009871011720561236,"score_gpt":0.23466240848243702,"score_spread":0.2247913967618758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2288393983","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29180777,0.0016228774,0.6158201,0.0010725516,0.00035563973,0.00018174782,0.0006893448,0.0040818243,0.08436816],"genre_scores_gemma":[0.92159414,0.0003362064,0.050677862,0.0001245089,0.00008113183,0.0001152987,0.00028870496,0.000493377,0.026288807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99917585,0.00012341373,0.0000391291,0.00023977025,0.00017359153,0.0002482487],"domain_scores_gemma":[0.99745935,0.0010043897,0.00015976514,0.001091398,0.00014159012,0.00014344849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005430715,0.00095921935,0.0012948064,0.0008146367,0.0014855766,0.0019949917,0.002226249,0.0010840193,0.015808076],"category_scores_gemma":[0.005889114,0.00051902997,0.00055905886,0.0011069187,0.0018425453,0.004582848,0.004169286,0.0014158316,0.0024462533],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037202856,0.00018912402,0.0014598973,0.0004588556,0.00020617204,0.0005191765,0.00063456217,0.35706806,0.015162268,0.43051702,0.016898377,0.1731662],"study_design_scores_gemma":[0.0003038713,0.00014843595,0.00032838338,0.00004399944,0.00006932243,0.00024524538,0.00022820274,0.55749345,0.012347771,0.4202055,0.008538838,0.000047049896],"about_ca_topic_score_codex":0.0029324775,"about_ca_topic_score_gemma":0.0024330565,"teacher_disagreement_score":0.015808076,"about_ca_system_score_codex":0.000723809,"about_ca_system_score_gemma":0.00086602475,"threshold_uncertainty_score":0.052883267},"labels":[],"label_agreement":null},{"id":"W2290715051","doi":"10.1007/978-3-642-45346-5_17","title":"Uniform Dispersal of Asynchronous Finite-State Mobile Robots in Presence of Holes","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Asynchronous communication; Mobile robot; Computer science; Visibility; State space; RADIUS; Point (geometry); State (computer science); Space (punctuation); Distributed computing; Topology (electrical circuits); Algorithm; Artificial intelligence; Mathematics; Computer network; Geometry; Combinatorics; Physics","score_opus":0.014945474727716263,"score_gpt":0.2465486846677044,"score_spread":0.23160320993998815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2290715051","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2637039,0.0014106358,0.7176241,0.0007733247,0.0003606402,0.00009786892,0.00021837663,0.00036573195,0.015445346],"genre_scores_gemma":[0.97003704,0.00060637825,0.01927173,0.00009628239,0.0001363345,0.000091755704,0.0001227361,0.0000698307,0.009567833],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996043,0.00010545606,0.000028655202,0.000109165085,0.00007746576,0.00007501926],"domain_scores_gemma":[0.9967109,0.0018501815,0.0005662119,0.0003137476,0.0002481758,0.0003108381],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008045799,0.0006431999,0.0010712143,0.00093165325,0.0007330351,0.0012345256,0.0020297552,0.0015624675,0.0021285343],"category_scores_gemma":[0.006764043,0.0005842959,0.000801472,0.0006362673,0.002092887,0.0024351242,0.0026019253,0.00093393517,0.00030740554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028007713,0.000055054454,0.0012388659,0.00025633397,0.00007275565,0.00058677443,0.00033230468,0.61267114,0.007011445,0.3630555,0.0022943963,0.012145356],"study_design_scores_gemma":[0.000052938154,0.000060103885,0.0003148858,0.000017382541,0.00001760654,0.00009536231,0.000047126035,0.92234796,0.00053152547,0.075752705,0.00074385485,0.000018521627],"about_ca_topic_score_codex":0.002113859,"about_ca_topic_score_gemma":0.0011360754,"teacher_disagreement_score":0.0021285343,"about_ca_system_score_codex":0.0007847609,"about_ca_system_score_gemma":0.00046906527,"threshold_uncertainty_score":0.007120669},"labels":[],"label_agreement":null},{"id":"W2293590087","doi":"10.1007/978-3-319-30303-1_1","title":"Optimization Problems in Infrastructure Security","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Task (project management); Critical infrastructure; Computer security; Process (computing); Order (exchange); Risk analysis (engineering); Management science; Systems engineering","score_opus":0.011637329829563964,"score_gpt":0.237086179571458,"score_spread":0.22544884974189403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293590087","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010380725,0.03012878,0.6376781,0.011801995,0.0017920256,0.00011173147,0.00047062783,0.0002211973,0.3074149],"genre_scores_gemma":[0.42581517,0.058649033,0.20035852,0.0030177657,0.0059836125,0.00068760075,0.00094361807,0.0008600528,0.30368462],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999281,0.000311282,0.000028365952,0.000110056615,0.00019766034,0.00007166112],"domain_scores_gemma":[0.9990563,0.000675681,0.00008305745,0.00006855909,0.00006791323,0.00004858546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011657597,0.0017271669,0.0015508247,0.0007877691,0.000628082,0.0029103223,0.0012536197,0.002208788,0.015438202],"category_scores_gemma":[0.003625759,0.0007265322,0.00096336973,0.0019897853,0.002037566,0.003233783,0.0013449768,0.00405147,0.0022808004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000028861956,0.000054583794,0.0001187146,0.00027724498,0.00005135376,0.000051372077,0.00006184777,0.08621959,0.00024220109,0.8233558,0.03526004,0.054278433],"study_design_scores_gemma":[0.000018112458,0.000022416167,0.00013228637,0.00014579004,0.000019821857,0.000051313564,0.0000472812,0.07529022,0.00014491231,0.8904611,0.03365331,0.0000135704695],"about_ca_topic_score_codex":0.0012068277,"about_ca_topic_score_gemma":0.00093842985,"teacher_disagreement_score":0.015438202,"about_ca_system_score_codex":0.0019515017,"about_ca_system_score_gemma":0.0009751855,"threshold_uncertainty_score":0.051645935},"labels":[],"label_agreement":null},{"id":"W2293719789","doi":"10.1145/2733693.2733713","title":"A Relaxed Algorithm for Online Matrix Inversion","year":2015,"lang":"en","type":"article","venue":"ACM communications in computer algebra","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Inversion (geology); Algorithm; Computer science; Matrix (chemical analysis); Geology; Chemistry","score_opus":0.1002151269805669,"score_gpt":0.3613357831181379,"score_spread":0.261120656137571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293719789","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020606476,0.00010882554,0.9888101,0.0002763597,0.00014545908,0.00010749073,0.00020127601,0.0011604427,0.0071294326],"genre_scores_gemma":[0.059095807,0.00019307242,0.9223318,0.0004285154,0.00028616094,0.00043621578,0.0011728731,0.0009130988,0.015142504],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99669194,0.0010611201,0.00018556249,0.0004935836,0.0011747578,0.0003930565],"domain_scores_gemma":[0.99418277,0.0026669952,0.00019827385,0.0017019638,0.001017214,0.0002327446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002550916,0.0019409392,0.001415148,0.0014343604,0.001144807,0.0022573445,0.0032098151,0.0019073407,0.03701497],"category_scores_gemma":[0.014150264,0.0011154541,0.001988621,0.002042932,0.0013829916,0.00413105,0.005007708,0.004827403,0.015317362],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00081917085,0.00044229845,0.0005930283,0.0004171431,0.00013756352,0.00032042392,0.00033053255,0.13523363,0.009232668,0.15816589,0.07186604,0.62244165],"study_design_scores_gemma":[0.00020760969,0.0001971201,0.00025676817,0.000062250714,0.00003757578,0.0002917841,0.00012274568,0.74588966,0.0044122986,0.22436091,0.024094792,0.00006646985],"about_ca_topic_score_codex":0.0039061494,"about_ca_topic_score_gemma":0.0049716365,"teacher_disagreement_score":0.03701497,"about_ca_system_score_codex":0.00086173986,"about_ca_system_score_gemma":0.002685646,"threshold_uncertainty_score":0.1238274},"labels":[],"label_agreement":null},{"id":"W2294012348","doi":"","title":"Almost Online Square Packing","year":2014,"lang":"en","type":"article","venue":"Canadian Conference on Computational Geometry","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Logarithm; Square (algebra); Online algorithm; Advice (programming); Oracle; Packing problems; Computer science; Algorithm; Sequence (biology); Mathematics; Mathematical optimization; Upper and lower bounds","score_opus":0.039339746340765196,"score_gpt":0.2710083307283992,"score_spread":0.231668584387634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2294012348","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058567844,0.0009944744,0.9218136,0.0005070148,0.00019629564,0.0001371103,0.0004429074,0.003234904,0.014105865],"genre_scores_gemma":[0.45273888,0.0007268763,0.5286656,0.0004892232,0.00022305184,0.0002053314,0.0014028329,0.0005500699,0.014998124],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986426,0.00026892545,0.000088903296,0.00031053595,0.00047379293,0.00021516457],"domain_scores_gemma":[0.99708587,0.0010209791,0.0002631986,0.001132475,0.0003116034,0.00018581066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061100593,0.00091416144,0.0014399689,0.0004206151,0.00065450754,0.0014360647,0.002277441,0.0013596617,0.008988945],"category_scores_gemma":[0.0041801454,0.00047813088,0.0006245429,0.0017451606,0.00089270325,0.003613195,0.0021730163,0.0011576384,0.0025341685],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012493444,0.000496963,0.0021736135,0.00062027725,0.00008924649,0.00039120807,0.0002654962,0.2666479,0.023421949,0.08088178,0.025150979,0.59861124],"study_design_scores_gemma":[0.00008208506,0.00034681824,0.0005677747,0.000028765062,0.000025462765,0.00053968147,0.00008743986,0.8825554,0.011729511,0.08974824,0.014259628,0.000029187442],"about_ca_topic_score_codex":0.0012480891,"about_ca_topic_score_gemma":0.0014115564,"teacher_disagreement_score":0.008988945,"about_ca_system_score_codex":0.00072738813,"about_ca_system_score_gemma":0.00083660876,"threshold_uncertainty_score":0.03007102},"labels":[],"label_agreement":null},{"id":"W2294592207","doi":"","title":"ONLINE COLORING CO-INTERVAL GRAPHS","year":2009,"lang":"en","type":"article","venue":"Scientia Iranica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Interval (graph theory); Combinatorics; Competitive analysis; Interval graph; Mathematics; Unit interval; Online algorithm; Indifference graph; Upper and lower bounds; Class (philosophy); Chordal graph; Discrete mathematics; Unit (ring theory); Complete coloring; Graph coloring; Algorithm; Computer science; Graph; Line graph; 1-planar graph; Artificial intelligence","score_opus":0.031509720431470045,"score_gpt":0.3059202773334071,"score_spread":0.27441055690193705,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2294592207","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.267312,0.00087155914,0.7140889,0.0011897775,0.0002488941,0.00025982715,0.0005907731,0.0017873438,0.013650943],"genre_scores_gemma":[0.8445958,0.00026654877,0.14931747,0.0002432701,0.00013606127,0.00017685773,0.00052168703,0.00018006857,0.0045622736],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975091,0.00090721034,0.0000861858,0.000651511,0.0004188646,0.00042713693],"domain_scores_gemma":[0.9895527,0.006183335,0.0011520624,0.001889711,0.0006055561,0.0006168022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014160317,0.00078299164,0.0012694256,0.00048757307,0.0009104915,0.0017215549,0.0028991096,0.0014198296,0.0068138666],"category_scores_gemma":[0.009523834,0.0004663999,0.00058307254,0.0015001299,0.0010140308,0.0034495022,0.0012672517,0.0016994026,0.0006994924],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00266251,0.0013439339,0.0062646423,0.0008482417,0.00022366688,0.00049099297,0.00034639606,0.6390466,0.017644227,0.108375914,0.016019851,0.20673297],"study_design_scores_gemma":[0.00013375466,0.00018756218,0.00075123174,0.000022175036,0.00003916679,0.0002989037,0.000101307436,0.93738055,0.0058979224,0.050105933,0.005059048,0.00002236979],"about_ca_topic_score_codex":0.0018731055,"about_ca_topic_score_gemma":0.0018159904,"teacher_disagreement_score":0.0068138666,"about_ca_system_score_codex":0.0015465328,"about_ca_system_score_gemma":0.0012256707,"threshold_uncertainty_score":0.022794604},"labels":[],"label_agreement":null},{"id":"W2295522973","doi":"10.1007/s00446-015-0259-2","title":"Rendezvous in networks in spite of delay faults","year":2015,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche; Université du Québec en Outaouais","keywords":"Rendezvous; Computer science; Upper and lower bounds; Bounded function; Node (physics); Leader election; Algorithm; Mathematics; Computer network","score_opus":0.029227116691228003,"score_gpt":0.27477104107005124,"score_spread":0.24554392437882322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2295522973","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6943711,0.0017327195,0.28771076,0.0023173385,0.00023877893,0.00008695403,0.0001818812,0.00040321032,0.012957204],"genre_scores_gemma":[0.9901163,0.00027510335,0.006629485,0.00004571904,0.000039216036,0.000026604504,0.000045508237,0.00005666412,0.0027653114],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994029,0.00017125302,0.000030457104,0.00011793891,0.00010110117,0.00017627918],"domain_scores_gemma":[0.9947018,0.003676208,0.0006188253,0.0002697111,0.0003469857,0.00038645093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014125232,0.000650195,0.0013746278,0.0011785524,0.0013962461,0.0016517617,0.0013637202,0.0013162225,0.0019904352],"category_scores_gemma":[0.008680195,0.00049445545,0.0004229943,0.0013451017,0.001817605,0.0026217739,0.0015321589,0.000915244,0.00024257165],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006980222,0.000039265302,0.0009998039,0.000095308875,0.000054610427,0.00028380667,0.0001736105,0.9290594,0.0032100158,0.053684335,0.0011889043,0.010512858],"study_design_scores_gemma":[0.00004864267,0.000051877916,0.00022894195,0.000007985069,0.00002085042,0.000061550934,0.00013132657,0.9608059,0.0012686126,0.036858514,0.0005059885,0.000009786795],"about_ca_topic_score_codex":0.005702813,"about_ca_topic_score_gemma":0.0036008921,"teacher_disagreement_score":0.005702813,"about_ca_system_score_codex":0.0016149568,"about_ca_system_score_gemma":0.00084399513,"threshold_uncertainty_score":0.011717379},"labels":[],"label_agreement":null},{"id":"W2304936616","doi":"10.1137/16m1107899","title":"The Matroid Secretary Problem for Minor-Closed Classes and Random Matroids","year":2020,"lang":"en","type":"preprint","venue":"SIAM Journal on Discrete Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Seventh Framework Programme","keywords":"Matroid; Minor (academic); Combinatorics; Graphic matroid; Matroid partitioning; Mathematics; Conjecture; Prime (order theory); Constant (computer programming); Discrete mathematics; Oriented matroid; Computer science; Law; Political science","score_opus":0.03167635855695254,"score_gpt":0.28859968637436695,"score_spread":0.2569233278174144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2304936616","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4785857,0.00057314086,0.498091,0.0024589705,0.00010793088,0.00024011347,0.0006184694,0.00087211584,0.018452503],"genre_scores_gemma":[0.8557271,0.00045133333,0.13043739,0.00036131844,0.00022224779,0.0002404023,0.0009644847,0.0002527415,0.011342893],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99800116,0.0006094479,0.000087094195,0.00057738554,0.00037731102,0.00034761243],"domain_scores_gemma":[0.98964185,0.0064120004,0.0008203984,0.0016063086,0.00048654113,0.0010329824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018163379,0.0005922257,0.0013129395,0.000777553,0.0014380867,0.0037040224,0.0019223528,0.001159313,0.005758133],"category_scores_gemma":[0.011417828,0.00065799686,0.0011884425,0.001269084,0.0016574836,0.0051528746,0.0017585652,0.0025656961,0.00083708117],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014024411,0.00091793033,0.0074760243,0.00046542846,0.00017489376,0.00028230526,0.001087853,0.11153461,0.018250536,0.71827626,0.019917814,0.12021391],"study_design_scores_gemma":[0.00019215536,0.00022705224,0.0012399835,0.000028954817,0.000059886825,0.0005431429,0.0002882094,0.594531,0.0092705535,0.37963787,0.013941182,0.00003996992],"about_ca_topic_score_codex":0.0017406159,"about_ca_topic_score_gemma":0.0015269768,"teacher_disagreement_score":0.005758133,"about_ca_system_score_codex":0.0015809805,"about_ca_system_score_gemma":0.0012949766,"threshold_uncertainty_score":0.01926291},"labels":[],"label_agreement":null},{"id":"W2309145395","doi":"10.1007/978-3-319-24729-8_5","title":"The Rendezvous Problem: Limited Camera Range","year":2015,"lang":"en","type":"book-chapter","venue":"Springer briefs in electrical and computer engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rendezvous; Visibility; Computer science; Range (aeronautics); Computer vision; Graph; Lipschitz continuity; Artificial intelligence; Mathematics; Theoretical computer science; Engineering; Physics; Mathematical analysis; Optics","score_opus":0.016221490765313106,"score_gpt":0.20912155345327896,"score_spread":0.19290006268796586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2309145395","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055870976,0.018069841,0.8192434,0.0031658374,0.00055269734,0.000116676914,0.00081680797,0.00050785305,0.101655886],"genre_scores_gemma":[0.78364027,0.015240816,0.12255562,0.0004964736,0.0010237495,0.00028497688,0.0008315249,0.0006416436,0.075284965],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992174,0.00020243943,0.000025718025,0.00028428857,0.00017481788,0.000095253265],"domain_scores_gemma":[0.99902856,0.00063891424,0.000095595606,0.00011081091,0.00005202675,0.000074089134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070746266,0.0013387009,0.0023755762,0.00069286383,0.00089418143,0.0027339815,0.0027304606,0.0031244727,0.008513275],"category_scores_gemma":[0.0033066391,0.0009790312,0.00079667004,0.0014097213,0.0022743326,0.004637127,0.0028735853,0.0022686666,0.0013894778],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000560767,0.00008764856,0.0004761397,0.0012244622,0.00016440956,0.0008491055,0.00041643466,0.44038397,0.010824402,0.4278659,0.019258803,0.09788808],"study_design_scores_gemma":[0.00013651347,0.00012216081,0.0006225367,0.00020506111,0.00006750093,0.0010684622,0.0003770847,0.49789456,0.004298355,0.46702215,0.028079672,0.00010591443],"about_ca_topic_score_codex":0.002581319,"about_ca_topic_score_gemma":0.0015679611,"teacher_disagreement_score":0.008513275,"about_ca_system_score_codex":0.0009422559,"about_ca_system_score_gemma":0.0006399964,"threshold_uncertainty_score":0.028479755},"labels":[],"label_agreement":null},{"id":"W2338647221","doi":"10.13053/rcs-107-1-15","title":"3-approximation Algorithm for the Travelling Repairman Problem with Unit Time-windows","year":2015,"lang":"en","type":"article","venue":"Research in Computing Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Unit (ring theory); Computer science; Algorithm; Mathematics","score_opus":0.1528335924436866,"score_gpt":0.38960855446794607,"score_spread":0.23677496202425946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2338647221","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031408496,0.0010502611,0.9545106,0.0009405984,0.00024493257,0.00020271687,0.00038569182,0.002048434,0.00920828],"genre_scores_gemma":[0.20894876,0.00055724656,0.7818989,0.0003904097,0.00012927638,0.00049965,0.0009853487,0.00047810347,0.006112363],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998718,0.0003404786,0.00008518893,0.00023022958,0.00028761386,0.00033842688],"domain_scores_gemma":[0.9978947,0.001266344,0.00015621244,0.00029790433,0.00024938097,0.00013553891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018857312,0.0017373452,0.0021384098,0.0012119377,0.0009519659,0.0018862097,0.0035181085,0.0025844602,0.008568415],"category_scores_gemma":[0.0060559,0.0006904191,0.0019665547,0.0022501454,0.0007564058,0.0034495282,0.0019888207,0.0030957784,0.0020193176],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010757222,0.0005369944,0.001139765,0.00032801856,0.00017462735,0.00019034764,0.00032082055,0.72132033,0.002954344,0.055696826,0.018781982,0.19748014],"study_design_scores_gemma":[0.000106310144,0.00007378946,0.00013266318,0.000019605082,0.000023942364,0.000066176246,0.000041539242,0.97381216,0.00052686664,0.022860225,0.0023236584,0.000012995878],"about_ca_topic_score_codex":0.009356271,"about_ca_topic_score_gemma":0.009165594,"teacher_disagreement_score":0.009356271,"about_ca_system_score_codex":0.003020273,"about_ca_system_score_gemma":0.0039439774,"threshold_uncertainty_score":0.028664172},"labels":[],"label_agreement":null},{"id":"W2338813786","doi":"10.1007/978-3-319-41168-2_9","title":"Know When to Persist: Deriving Value from a Stream Buffer","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; McMaster University; Toronto Metropolitan University","funders":"","keywords":"Computer science; Data stream; Scheduling (production processes); Random permutation; Competitive analysis; Buffer (optical fiber); Online algorithm; Algorithm; Mathematical optimization; Upper and lower bounds; Mathematics; Discrete mathematics","score_opus":0.017708914270618627,"score_gpt":0.24411503559238928,"score_spread":0.22640612132177065,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2338813786","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019949522,0.00047842666,0.9680301,0.00085858325,0.0001937919,0.00009902029,0.00045159727,0.004604823,0.005334136],"genre_scores_gemma":[0.43505606,0.0006806758,0.5506636,0.00050226995,0.00032246736,0.00015094476,0.00086096954,0.002150454,0.009612552],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99838066,0.0002771648,0.00013183839,0.00039696076,0.0006297748,0.00018353642],"domain_scores_gemma":[0.9924124,0.004666289,0.0003235184,0.0015582565,0.00075547857,0.00028396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028593864,0.00091489387,0.0012275412,0.0010698651,0.000990859,0.0042179204,0.0031957182,0.001661859,0.005284767],"category_scores_gemma":[0.019801803,0.0008563636,0.0011820794,0.001356325,0.002324801,0.010708039,0.004034585,0.002683006,0.0013886621],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012342102,0.00020155354,0.004998158,0.0005107189,0.00013218918,0.0008440544,0.00203631,0.07225397,0.01402728,0.47152573,0.015908591,0.41632718],"study_design_scores_gemma":[0.0000923114,0.00011135114,0.00027906126,0.00013394275,0.00014322757,0.00022580747,0.00026536515,0.418164,0.026661234,0.536634,0.017219273,0.000070403774],"about_ca_topic_score_codex":0.0025206902,"about_ca_topic_score_gemma":0.0020868748,"teacher_disagreement_score":0.005284767,"about_ca_system_score_codex":0.0012405472,"about_ca_system_score_gemma":0.0018805409,"threshold_uncertainty_score":0.017679274},"labels":[],"label_agreement":null},{"id":"W2342108770","doi":"10.1016/j.tcs.2016.04.016","title":"An alternative proof for the equivalence of ∞-searcher and 2-searcher","year":2016,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Visibility; Equivalence (formal languages); Conjecture; Computer science; Mathematics; Theoretical computer science; Discrete mathematics","score_opus":0.03990573698417783,"score_gpt":0.33345797334618205,"score_spread":0.2935522363620042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2342108770","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035462763,0.0013070449,0.7769881,0.010914048,0.0017628646,0.00012405851,0.0008137489,0.0007345967,0.1718928],"genre_scores_gemma":[0.73084754,0.0016075346,0.21568961,0.008258612,0.0022599234,0.0004353628,0.00085697166,0.00058401,0.039460473],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969999,0.0008585029,0.00023258307,0.0007096303,0.0007069905,0.0004922498],"domain_scores_gemma":[0.9901428,0.006395643,0.00041137805,0.0013214259,0.0013725443,0.00035621226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030609115,0.000837214,0.0011599095,0.0016550457,0.0016369612,0.003491878,0.0027891237,0.0032730212,0.026998585],"category_scores_gemma":[0.01651488,0.00055113906,0.0020175395,0.0020739578,0.004303632,0.012320488,0.005132012,0.006486883,0.0022521012],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000025957917,0.000020048034,0.00011716938,0.000043607106,0.000008754004,0.00005540985,0.00010623103,0.00049591734,0.00036415164,0.99082655,0.0023594922,0.0055767456],"study_design_scores_gemma":[0.000019742469,0.00002056917,0.00015915139,0.000014761966,0.000008423059,0.000115352945,0.00003787625,0.0043089944,0.0003344224,0.9900614,0.0049066115,0.000012783704],"about_ca_topic_score_codex":0.0012166267,"about_ca_topic_score_gemma":0.00092188065,"teacher_disagreement_score":0.026998585,"about_ca_system_score_codex":0.00132522,"about_ca_system_score_gemma":0.0015876943,"threshold_uncertainty_score":0.090319276},"labels":[],"label_agreement":null},{"id":"W2342411541","doi":"10.1109/tkde.2016.2527003","title":"Conflict-Aware Weighted Bipartite B-Matching and Its Application to E-Commerce","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Knowledge and Data Engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bipartite graph; Computer science; Scalability; Matching (statistics); Scheduling (production processes); The Internet; Time complexity; Approximation algorithm; Blossom algorithm; Context (archaeology); Theoretical computer science; Data mining; Graph; Combinatorics; Algorithm; Mathematics; World Wide Web; Mathematical optimization; Database","score_opus":0.030657586213925878,"score_gpt":0.28427757784468977,"score_spread":0.2536199916307639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2342411541","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04071235,0.0022255636,0.9452356,0.0018972249,0.00015878731,0.00028924397,0.0007425092,0.0008764867,0.007862237],"genre_scores_gemma":[0.39251798,0.0018456426,0.59865534,0.0008003626,0.0002163891,0.00036708277,0.0016082904,0.0003192657,0.0036696882],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.997006,0.0014099869,0.0001538893,0.00072624773,0.0004950973,0.00020874564],"domain_scores_gemma":[0.99531436,0.0028997993,0.00044773656,0.0006876975,0.00040238173,0.00024800183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002932391,0.0011561281,0.0020132966,0.0018903662,0.0017632374,0.0020081038,0.0031167383,0.0026143617,0.005286394],"category_scores_gemma":[0.012452737,0.0009676278,0.0016443526,0.0071870782,0.0013317905,0.004582715,0.0024905861,0.0024713508,0.00095652393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039012535,0.0006668593,0.003358434,0.00077133114,0.0003151171,0.00034292764,0.0003187773,0.6191391,0.0036940554,0.14965078,0.022072973,0.1992795],"study_design_scores_gemma":[0.000045935896,0.000051236206,0.0003640938,0.000023484728,0.00003324751,0.0001638708,0.00006614447,0.8667449,0.0006214534,0.12731068,0.0045548226,0.000020241356],"about_ca_topic_score_codex":0.0055528153,"about_ca_topic_score_gemma":0.0045634834,"teacher_disagreement_score":0.0055528153,"about_ca_system_score_codex":0.0016824516,"about_ca_system_score_gemma":0.0018313733,"threshold_uncertainty_score":0.017684758},"labels":[],"label_agreement":null},{"id":"W2345197515","doi":"10.1142/s1793830916500427","title":"Survivability of bouncing robots","year":2016,"lang":"en","type":"article","venue":"Discrete Mathematics Algorithms and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Survivability; Swarm behaviour; Position (finance); Trajectory; Swarm robotics; Mobile robot; Computer science; Robotics; Control theory (sociology); Artificial intelligence; Physics; Control (management)","score_opus":0.02190954584372441,"score_gpt":0.27330321417213055,"score_spread":0.25139366832840615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2345197515","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.919101,0.0006773448,0.07170769,0.00021878818,0.000043320622,0.00003595689,0.000099756886,0.00020088661,0.007915181],"genre_scores_gemma":[0.9929923,0.0002249961,0.00450807,0.000033921384,0.00000935874,0.000039830236,0.00016795468,0.000017709486,0.0020059813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996934,0.000034437748,0.000017596496,0.00007182277,0.00009393827,0.0000888442],"domain_scores_gemma":[0.9991074,0.00023121771,0.00022921147,0.00013941001,0.0001256584,0.00016713317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027702417,0.0005159776,0.00057313463,0.0005118491,0.0008879314,0.00066051044,0.00080127874,0.0004711939,0.001643113],"category_scores_gemma":[0.001764311,0.0003088267,0.00043138716,0.0003214102,0.0014821303,0.0009991184,0.001807264,0.00056234637,0.00018585626],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011057314,0.0001539632,0.033411045,0.0006469032,0.00018571081,0.0038900648,0.0018272672,0.66147065,0.09246599,0.123987645,0.0029832618,0.07787179],"study_design_scores_gemma":[0.000050021237,0.00068008964,0.010002216,0.00008163691,0.00007434756,0.001255926,0.0009551971,0.86777085,0.025140498,0.085117504,0.008803247,0.000068416],"about_ca_topic_score_codex":0.0022944969,"about_ca_topic_score_gemma":0.0009732789,"teacher_disagreement_score":0.0022944969,"about_ca_system_score_codex":0.00046444184,"about_ca_system_score_gemma":0.00029428187,"threshold_uncertainty_score":0.0054968},"labels":[],"label_agreement":null},{"id":"W2354503817","doi":"","title":"Research on Strategy for Stochastic Blockage Recovery time in Canadian Travel Problem Based on Exponential Distribution","year":2011,"lang":"en","type":"article","venue":"Shuxue de shijian yu renshi","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Exponential function; Exponential distribution; Mathematical optimization; Computer science; Distribution (mathematics); Point (geometry); Operations research; Gamma distribution; Time point; Mathematics; Statistics","score_opus":0.09138370380683074,"score_gpt":0.3169595890350093,"score_spread":0.22557588522817856,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2354503817","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22719918,0.0035446852,0.7434052,0.0022895026,0.00018941413,0.0004161708,0.0004738961,0.0003071227,0.022174884],"genre_scores_gemma":[0.96071625,0.0024521307,0.028468633,0.00020692912,0.000104435814,0.00018104965,0.00030857202,0.000081616054,0.0074804337],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99865687,0.00031982193,0.00004100969,0.00025317472,0.00024035572,0.00048882596],"domain_scores_gemma":[0.99655247,0.0022363996,0.0003456468,0.00009805259,0.0003892515,0.00037811135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016344213,0.0013101726,0.0017219499,0.0011331263,0.0010409699,0.0018926429,0.00298308,0.0017004755,0.00457338],"category_scores_gemma":[0.0060175145,0.00051641354,0.0009250574,0.0017969103,0.0012099302,0.0030014252,0.0011248897,0.0018250488,0.00022475857],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002568492,0.00015122817,0.0019380017,0.0003533944,0.000098766985,0.0001652196,0.00021271808,0.86018133,0.001656978,0.1026896,0.0060890345,0.026206927],"study_design_scores_gemma":[0.00002589441,0.00006847206,0.00030607462,0.000012478123,0.000024638706,0.000049746784,0.00010616463,0.9835851,0.000251189,0.014707332,0.0008451495,0.000017780068],"about_ca_topic_score_codex":0.05732016,"about_ca_topic_score_gemma":0.028487984,"teacher_disagreement_score":0.9426798,"about_ca_system_score_codex":0.004102288,"about_ca_system_score_gemma":0.005562305,"threshold_uncertainty_score":0.11397302},"labels":[],"label_agreement":null},{"id":"W2371255390","doi":"","title":"Online Canadian Traveler Problem with Stochastic Blockages Recovery Time","year":2005,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Computer science; Point (geometry); Operations research; Process (computing); Accident (philosophy); Travel time; Mathematical optimization; Transport engineering; Mathematics; Engineering","score_opus":0.009456256601901239,"score_gpt":0.21090978062566035,"score_spread":0.2014535240237591,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2371255390","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57978845,0.002139529,0.3643348,0.0030166353,0.00035643548,0.0008035777,0.003920191,0.0010119812,0.04462848],"genre_scores_gemma":[0.9597889,0.00065843284,0.022097396,0.00016272989,0.000089031644,0.00018104832,0.001208829,0.00009958765,0.01571398],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985567,0.00027939156,0.000035595865,0.00022033969,0.00024806554,0.00065998884],"domain_scores_gemma":[0.99705863,0.0015576015,0.00037287155,0.00014422965,0.0002821021,0.00058465905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00140188,0.001850698,0.0024375743,0.0009204329,0.001451008,0.0017951055,0.0040476853,0.002841184,0.01033135],"category_scores_gemma":[0.0038008022,0.0006009936,0.0009747201,0.002189201,0.0013365835,0.002289737,0.0013915634,0.0018823168,0.0005033905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007282678,0.00017787702,0.00095167453,0.00016381597,0.00007907471,0.0004095819,0.000068638954,0.95143205,0.0007847547,0.023809675,0.0072981594,0.0140963895],"study_design_scores_gemma":[0.00009574175,0.00008221027,0.00048177937,0.00000788008,0.000027105827,0.00008056738,0.00008533958,0.9899483,0.00029529317,0.0073830257,0.0014885972,0.000024098032],"about_ca_topic_score_codex":0.25088865,"about_ca_topic_score_gemma":0.17308103,"teacher_disagreement_score":0.25088865,"about_ca_system_score_codex":0.005241382,"about_ca_system_score_gemma":0.0071906317,"threshold_uncertainty_score":0.4988566},"labels":[],"label_agreement":null},{"id":"W2382551251","doi":"","title":"The Research on Swarm Intelligence Based on 0/1 Knapsack Problem Solution","year":2007,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Knapsack problem; Continuous knapsack problem; Swarm intelligence; Computer science; Mathematical optimization; Cutting stock problem; Particle swarm optimization; Robustness (evolution); Polynomial-time approximation scheme; Generalized assignment problem; Ant colony optimization algorithms; Combinatorial optimization; Swarm behaviour; Convergence (economics); Optimization problem; Mathematics","score_opus":0.0695622077182088,"score_gpt":0.3686154180933716,"score_spread":0.2990532103751628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2382551251","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013270611,0.0150863025,0.9367219,0.0014465891,0.0007175485,0.00009304031,0.0000498592,0.00016986494,0.03244422],"genre_scores_gemma":[0.37746093,0.044219248,0.5566587,0.00075615983,0.001518579,0.0002961118,0.00029365125,0.000097529795,0.018699111],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991518,0.00028660032,0.00006328146,0.00015531553,0.00028918,0.00005384285],"domain_scores_gemma":[0.9992003,0.00046925785,0.00006556245,0.00006260782,0.00017604085,0.000026310794],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012466308,0.00078620214,0.00081948214,0.00086953474,0.00066396216,0.0015142405,0.0008758695,0.0011929485,0.0018232767],"category_scores_gemma":[0.0023971356,0.00039651772,0.0008966723,0.0015995405,0.0014121198,0.0027222354,0.0007352617,0.001539191,0.00044911331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006777485,0.00008422273,0.0014272624,0.0014968163,0.00014118543,0.00026107937,0.0003205599,0.17236295,0.0074171484,0.50193095,0.0062381774,0.3082519],"study_design_scores_gemma":[0.00003343434,0.00023553023,0.001240214,0.00033169345,0.00007560746,0.00043434792,0.00020334544,0.63161683,0.00759515,0.28933337,0.068822786,0.000077640994],"about_ca_topic_score_codex":0.0018434111,"about_ca_topic_score_gemma":0.00082520803,"teacher_disagreement_score":0.0018434111,"about_ca_system_score_codex":0.0007283218,"about_ca_system_score_gemma":0.00084764324,"threshold_uncertainty_score":0.0065928698},"labels":[],"label_agreement":null},{"id":"W23905021","doi":"10.1007/978-3-642-39212-2_45","title":"Localization for a System of Colliding Robots","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Mobile robot; Visibility; Trajectory; Position (finance); Obstacle; Computer science; Simulation; Control theory (sociology); Topology (electrical circuits); Physics; Engineering; Artificial intelligence; Geography; Control (management); Electrical engineering; Optics","score_opus":0.02593684835541053,"score_gpt":0.25550442466648365,"score_spread":0.22956757631107313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W23905021","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018979171,0.0008097327,0.9728213,0.00036704534,0.00009688778,0.000023783801,0.000043182834,0.00033088017,0.0065280516],"genre_scores_gemma":[0.6064192,0.0027241004,0.34808782,0.0002098145,0.00026643078,0.00028048342,0.0002806852,0.00017926184,0.04155226],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997341,0.000049985196,0.000016621918,0.000086192806,0.000078303834,0.000034846402],"domain_scores_gemma":[0.9997359,0.00013645233,0.000035500623,0.000028241899,0.000048721646,0.000015147741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00035245655,0.0008059791,0.0007517837,0.0005802496,0.000801375,0.000948911,0.0012895837,0.0015633448,0.0039650863],"category_scores_gemma":[0.0013199527,0.00045112378,0.0005830089,0.0009815408,0.0011536201,0.0013180502,0.002253233,0.00095535954,0.00095025543],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020358023,0.000036959696,0.00088385097,0.00059012056,0.000078809244,0.0008600025,0.00064121006,0.6625389,0.014823811,0.18497378,0.0048128674,0.12955613],"study_design_scores_gemma":[0.00004216516,0.000103228376,0.00031227153,0.000030488014,0.00002997872,0.00035827945,0.00010283456,0.8633565,0.0016456691,0.1289296,0.0050580655,0.000030932708],"about_ca_topic_score_codex":0.001929214,"about_ca_topic_score_gemma":0.0014311649,"teacher_disagreement_score":0.0039650863,"about_ca_system_score_codex":0.00047453932,"about_ca_system_score_gemma":0.00041725632,"threshold_uncertainty_score":0.013264537},"labels":[],"label_agreement":null},{"id":"W2393415573","doi":"10.1177/0278364915620848","title":"Reliable confirmation of an object identity by a mobile robot: A mixed appearance/localization-driven motion approach","year":2016,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Mobile robot; Novelty; Computer science; Artificial intelligence; Computer vision; Robot; Identity (music); Object (grammar); Motion (physics); Novelty detection; False positive paradox; Process (computing); Psychology","score_opus":0.05191870500519372,"score_gpt":0.36006660591655976,"score_spread":0.308147900911366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2393415573","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04040504,0.00015663785,0.9584099,0.0001837333,0.000015028796,0.000039344122,0.000020180567,0.00019314857,0.00057699403],"genre_scores_gemma":[0.8017901,0.00010891611,0.1963829,0.00008818579,0.00003884968,0.000097637356,0.000068903006,0.000066868866,0.001357683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985037,0.00056204427,0.000073721705,0.00028372245,0.00043450927,0.00014248499],"domain_scores_gemma":[0.9950336,0.0029818327,0.0008398338,0.00041021436,0.0005349163,0.0001995642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022745132,0.0008780767,0.0012119245,0.0010755837,0.00053089776,0.00083854696,0.0018864208,0.0013874163,0.00074911554],"category_scores_gemma":[0.0075624925,0.00074838736,0.00084046245,0.0005552666,0.001228539,0.0014911977,0.0021910695,0.0008518456,0.00023091478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044828025,0.00011597366,0.0033104704,0.00016067555,0.00009318914,0.00036661618,0.00021072078,0.8559041,0.012777463,0.017201893,0.00046529982,0.10894539],"study_design_scores_gemma":[0.000013096898,0.000088620116,0.0003647635,0.0000068317927,0.000013359402,0.000057995247,0.000013298819,0.9937856,0.0020128158,0.0034600769,0.0001704632,0.0000130939625],"about_ca_topic_score_codex":0.0019892845,"about_ca_topic_score_gemma":0.0013374226,"teacher_disagreement_score":0.0022745132,"about_ca_system_score_codex":0.00083607354,"about_ca_system_score_gemma":0.0010073138,"threshold_uncertainty_score":0.012028933},"labels":[],"label_agreement":null},{"id":"W2395192821","doi":"10.1007/978-3-662-48971-0_30","title":"When Patrolmen Become Corrupted: Monitoring a Graph Using Faulty Mobile Robots","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Patrolling; Computer science; Eulerian path; Enhanced Data Rates for GSM Evolution; Mobile robot; Domain (mathematical analysis); Robot; Graph; Line segment; Point (geometry); Algorithm; Robotics; Line (geometry); Combinatorics; Artificial intelligence; Theoretical computer science; Mathematics; Geometry","score_opus":0.05845675204202838,"score_gpt":0.305469587630638,"score_spread":0.2470128355886096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2395192821","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8115033,0.00040025244,0.18265004,0.001133296,0.00020400253,0.00006216672,0.00034221745,0.0011315626,0.0025731428],"genre_scores_gemma":[0.9791343,0.000082042316,0.019485416,0.000075407836,0.00002898718,0.000012404671,0.00020456906,0.00007515648,0.00090177683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993206,0.000109859226,0.000022353912,0.00022571743,0.00019022691,0.00013113314],"domain_scores_gemma":[0.99664515,0.0016493285,0.0005763143,0.00042660948,0.00040699795,0.00029544233],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053318107,0.0006797415,0.00085188006,0.0007066308,0.0007609229,0.00084998115,0.002469943,0.0020367748,0.0010742034],"category_scores_gemma":[0.006039542,0.0005763109,0.0004183127,0.0007395124,0.0010235572,0.0020432158,0.0010197534,0.0010723007,0.00021351427],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017982695,0.00034437294,0.042009324,0.0003941855,0.000265114,0.0049047456,0.0012958689,0.7981856,0.02869406,0.0066628656,0.008630451,0.10681515],"study_design_scores_gemma":[0.00002218583,0.00014835724,0.005731653,0.000017428278,0.000062131454,0.00043238103,0.0005321076,0.97805256,0.0061070034,0.008067167,0.00080687174,0.0000200679],"about_ca_topic_score_codex":0.005139065,"about_ca_topic_score_gemma":0.0063802293,"teacher_disagreement_score":0.005139065,"about_ca_system_score_codex":0.00053891813,"about_ca_system_score_gemma":0.00044271743,"threshold_uncertainty_score":0.010218263},"labels":[],"label_agreement":null},{"id":"W2397069087","doi":"","title":"Minimum degree and nowhere-zero 3-flows.","year":2013,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Degree (music); Zero (linguistics); Physics; Philosophy","score_opus":0.021657299920637,"score_gpt":0.23882028423757679,"score_spread":0.21716298431693978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2397069087","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5682374,0.003429939,0.1865114,0.008290999,0.000762494,0.00012416001,0.0026783433,0.00040310682,0.2295622],"genre_scores_gemma":[0.8961429,0.0012353915,0.053892452,0.0006725194,0.00025248138,0.00009170197,0.001204381,0.00016672157,0.04634149],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996201,0.000102632956,0.000018210907,0.00007613153,0.00006258672,0.00012031493],"domain_scores_gemma":[0.99844116,0.00086015806,0.00021833218,0.00013023167,0.000134731,0.00021540055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057027687,0.0005122171,0.0006206453,0.0008826303,0.0012996861,0.0021264206,0.001046611,0.0013154993,0.012793826],"category_scores_gemma":[0.0041574105,0.0003795296,0.00058024906,0.00073070073,0.0014488644,0.003279758,0.0015938916,0.0022555443,0.0016528213],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021218573,0.00008210596,0.0006454088,0.00014680333,0.000020437301,0.00012795613,0.00016429125,0.0067653656,0.0021033692,0.9615451,0.009550166,0.018636802],"study_design_scores_gemma":[0.000039401166,0.000013793885,0.00034454226,0.00003152003,0.0000099747995,0.00012367996,0.000103969745,0.008222213,0.00096096157,0.98437816,0.0057598343,0.000011792629],"about_ca_topic_score_codex":0.0014093737,"about_ca_topic_score_gemma":0.0023775501,"teacher_disagreement_score":0.012793826,"about_ca_system_score_codex":0.0010982068,"about_ca_system_score_gemma":0.000798921,"threshold_uncertainty_score":0.04279965},"labels":[],"label_agreement":null},{"id":"W2398465054","doi":"10.1007/978-3-319-28472-9_7","title":"Deterministic Rendezvous with Detection Using Beeps","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Computer science; Node (physics); Logarithm; Mobile agent; Real-time computing; Integer (computer science); Computer network; Distributed computing; Algorithm; Mathematics; Operating system","score_opus":0.047112980001445294,"score_gpt":0.27870269572671186,"score_spread":0.23158971572526657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2398465054","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.038019396,0.0003975655,0.9484428,0.00016945171,0.00016959688,0.00008055364,0.00011597711,0.0018184155,0.010786122],"genre_scores_gemma":[0.77760226,0.0001905128,0.20905957,0.00012294063,0.000043607837,0.00012516054,0.00015872887,0.0002491575,0.012448154],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923253,0.000110474524,0.00003205743,0.00022175114,0.00027591005,0.00012737156],"domain_scores_gemma":[0.9987532,0.000645866,0.00008249954,0.0003533105,0.000111485904,0.0000536411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049322663,0.0008274,0.0010946781,0.00047818714,0.00079764036,0.0008906276,0.0016277094,0.0010863614,0.0035357482],"category_scores_gemma":[0.002775865,0.0006804924,0.00051792123,0.00055329764,0.000993061,0.001350542,0.002353778,0.0010099977,0.0009972412],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012267751,0.000137041,0.0016771146,0.000326628,0.00013895344,0.00040844036,0.00022776771,0.54712087,0.062696606,0.085764386,0.0068832915,0.29339212],"study_design_scores_gemma":[0.00003786355,0.000068814894,0.00027119735,0.000017127926,0.000014458623,0.0001354523,0.000022681903,0.9629772,0.012033988,0.022013295,0.002376525,0.000031455224],"about_ca_topic_score_codex":0.0023868324,"about_ca_topic_score_gemma":0.0028378195,"teacher_disagreement_score":0.0035357482,"about_ca_system_score_codex":0.0005369344,"about_ca_system_score_gemma":0.0006424044,"threshold_uncertainty_score":0.011828244},"labels":[],"label_agreement":null},{"id":"W2402513160","doi":"","title":"Competitive Routing on a Bounded-Degree Plane Spanner","year":2012,"lang":"en","type":"article","venue":"University of Southern Denmark Research Portal (University of Southern Denmark)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Danmarks Frie Forskningsfond","keywords":"Degree (music); Bounded function; Spanner; Plane (geometry); Routing (electronic design automation); Combinatorics; Computer science; Mathematics; Computer network; Physics; Distributed computing; Geometry; Mathematical analysis","score_opus":0.05395445164663279,"score_gpt":0.2570213218994755,"score_spread":0.20306687025284273,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402513160","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6971441,0.00040633653,0.27921206,0.00071261765,0.000041994732,0.000111917194,0.00069920474,0.00028419244,0.021387681],"genre_scores_gemma":[0.8988279,0.0004436146,0.08678253,0.00009422293,0.000032613727,0.000101441256,0.0007893558,0.00006487834,0.012863441],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995091,0.000114743205,0.000024632485,0.00010002202,0.00011979817,0.00013175486],"domain_scores_gemma":[0.9989477,0.0004745688,0.00018162186,0.00016379963,0.000094389405,0.00013798798],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038820022,0.00056402007,0.0007602988,0.00044910773,0.00059805287,0.001376572,0.0010957918,0.0008908161,0.0083563],"category_scores_gemma":[0.0025762438,0.00025548608,0.0004931681,0.00092580065,0.00065688754,0.0027445168,0.0017108269,0.00067431584,0.00087278034],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009230881,0.0001854774,0.0015473714,0.00026275765,0.00006721821,0.00047611355,0.0003000374,0.7600025,0.019918388,0.16019993,0.0040335064,0.05208363],"study_design_scores_gemma":[0.000067014436,0.00024900664,0.00053824286,0.000017578624,0.000024745594,0.00020963264,0.00014405421,0.91804284,0.004968719,0.07140976,0.004307655,0.00002072017],"about_ca_topic_score_codex":0.0027849625,"about_ca_topic_score_gemma":0.002553838,"teacher_disagreement_score":0.0083563,"about_ca_system_score_codex":0.0008627233,"about_ca_system_score_gemma":0.00044733763,"threshold_uncertainty_score":0.027954638},"labels":[],"label_agreement":null},{"id":"W2404009953","doi":"10.1080/03155986.2001.11732437","title":"Le Stockage Massif De L’Énergie Hydroélectrique : Modèle D’Investissement Et Méthode De Solution Par Décomposition","year":2001,"lang":"fr","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Hydroelectricity; Energy storage; Environmental science; Mathematics; Mathematical optimization; Computer science; Electrical engineering; Engineering; Physics; Thermodynamics","score_opus":0.14738548314368705,"score_gpt":0.3633482117204766,"score_spread":0.21596272857678955,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404009953","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015695162,0.001973109,0.966881,0.0009731964,0.0001151074,0.00008369299,0.00051588,0.0001571096,0.0136057325],"genre_scores_gemma":[0.60873634,0.0050675436,0.3392162,0.0002585189,0.00024936983,0.0009979551,0.0008429045,0.00033261886,0.04429847],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996942,0.000109203436,0.000010116251,0.000057652353,0.00006764965,0.00006106428],"domain_scores_gemma":[0.9992368,0.00049281574,0.00010192072,0.000029138822,0.00008457732,0.00005471669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013887031,0.0012669107,0.0012013481,0.0007745949,0.0004493782,0.002412666,0.0015104653,0.002493291,0.004571043],"category_scores_gemma":[0.0021340258,0.0011635982,0.0013654598,0.0013234818,0.0012074485,0.0014377383,0.0010321474,0.0021036803,0.00093631365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017680468,0.000013789589,0.00014675826,0.00004060131,0.000014364784,0.000034074143,0.000016571876,0.96724,0.00024743797,0.027876385,0.0007631882,0.003589262],"study_design_scores_gemma":[0.000006769746,0.000005468423,0.000039797193,0.000009965108,0.0000055584487,0.000008076673,0.0000052749187,0.9917938,0.0000916946,0.0070132795,0.0010164939,0.0000037751213],"about_ca_topic_score_codex":0.017628567,"about_ca_topic_score_gemma":0.010142148,"teacher_disagreement_score":0.017628567,"about_ca_system_score_codex":0.0028118147,"about_ca_system_score_gemma":0.002412336,"threshold_uncertainty_score":0.035051942},"labels":[],"label_agreement":null},{"id":"W2405214329","doi":"10.1080/03155986.2003.11732679","title":"A Logarithmic Barrier Approach To Solving The Dashboard Planning Problem","year":2003,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Dashboard; Workload; Computer science; Logarithm; Mathematical optimization; Mathematics; Operating system; Data science","score_opus":0.07240547268433704,"score_gpt":0.3360515189362072,"score_spread":0.26364604625187016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2405214329","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006335078,0.00022872495,0.9879704,0.00035574034,0.000024682065,0.00006404013,0.00005658889,0.00012580106,0.0048390348],"genre_scores_gemma":[0.38778245,0.0008574522,0.5977514,0.00026549728,0.0000728407,0.0006639078,0.00028848206,0.00021037673,0.012107639],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992078,0.00035408736,0.000030367868,0.00012354946,0.00017519004,0.00010901028],"domain_scores_gemma":[0.99854916,0.0011093355,0.00008942906,0.000056481866,0.00013117043,0.000064475105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015181314,0.0012522575,0.0009370142,0.0006750813,0.0005136328,0.0012618107,0.001466471,0.0011654295,0.0070511913],"category_scores_gemma":[0.0040033762,0.0005021565,0.00065736036,0.0008906412,0.0010579247,0.0018442405,0.0012768254,0.0020882434,0.00077341177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000108900036,0.000094604344,0.00019188381,0.00017964652,0.00002868323,0.00009923513,0.00007448431,0.9159415,0.0015469982,0.053657543,0.0019101667,0.026166352],"study_design_scores_gemma":[0.000029974759,0.000052140986,0.00004452061,0.000012551424,0.000006782438,0.000018598996,0.00002202201,0.98164326,0.0005011507,0.016101763,0.0015607004,0.000006494861],"about_ca_topic_score_codex":0.0042740223,"about_ca_topic_score_gemma":0.0032251733,"teacher_disagreement_score":0.0070511913,"about_ca_system_score_codex":0.0009813926,"about_ca_system_score_gemma":0.0018715995,"threshold_uncertainty_score":0.023588598},"labels":[],"label_agreement":null},{"id":"W2463954311","doi":"10.1145/3280823","title":"Deterministic Graph Exploration with Advice","year":2018,"lang":"en","type":"preprint","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Oracle; Advice (programming); Graph; Computer science; Theoretical computer science; Time complexity; Combinatorics; A priori and a posteriori; Node (physics); Discrete mathematics; Mathematics; Algorithm","score_opus":0.04404600970732654,"score_gpt":0.2913510131177562,"score_spread":0.24730500341042966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2463954311","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12456146,0.0010152931,0.8508173,0.002896179,0.00018621288,0.00024858912,0.0010310751,0.0049879937,0.014255818],"genre_scores_gemma":[0.5591396,0.0006212975,0.4276135,0.0007201427,0.0001584214,0.00033269837,0.0013494798,0.0006235621,0.009441286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99778265,0.00044850717,0.00013508264,0.0006966458,0.00048205935,0.00045506164],"domain_scores_gemma":[0.9891349,0.0072989403,0.0005775278,0.0019003579,0.0005871716,0.0005009854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012908352,0.00108742,0.001168601,0.0005797908,0.0008839584,0.0015267907,0.0020818848,0.0019881707,0.006028649],"category_scores_gemma":[0.017211188,0.0005754884,0.0013246672,0.0009732285,0.002015066,0.0047395728,0.0028881703,0.0027549434,0.0012093437],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022469484,0.0003177543,0.0056045577,0.0011435472,0.00016449305,0.0005458184,0.0011542994,0.60459054,0.014113603,0.19662686,0.015227877,0.15826367],"study_design_scores_gemma":[0.00015403569,0.0001743999,0.00048550326,0.000048417784,0.000047291593,0.00016862311,0.00009594285,0.7372419,0.0038771816,0.24889733,0.00877826,0.00003100243],"about_ca_topic_score_codex":0.0038837497,"about_ca_topic_score_gemma":0.005048534,"teacher_disagreement_score":0.006028649,"about_ca_system_score_codex":0.0016995901,"about_ca_system_score_gemma":0.0020347899,"threshold_uncertainty_score":0.020167828},"labels":[],"label_agreement":null},{"id":"W2465741342","doi":"10.4230/dagsemproc.10071.6","title":"Every Deterministic Nonclairvoyant Scheduler has a Suboptimal Load Threshold","year":2010,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Sublinear function; Competitive analysis; Omega; Fixed point; Scheduling (production processes); Mathematics; Upper and lower bounds; Computer science; Discrete mathematics; BETA (programming language); Combinatorics; Algorithm; Mathematical optimization","score_opus":0.02426286062609075,"score_gpt":0.2645023520200533,"score_spread":0.24023949139396253,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2465741342","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20351481,0.0010909265,0.75637984,0.0070544714,0.0005211231,0.00043336817,0.0006189683,0.0037238144,0.026662644],"genre_scores_gemma":[0.66930056,0.00044922065,0.31734386,0.0020057254,0.00020762245,0.00047872402,0.00067356497,0.0009781917,0.008562569],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99216014,0.0013230201,0.0004869895,0.0025560313,0.0018654973,0.001608348],"domain_scores_gemma":[0.9727121,0.014683373,0.00194592,0.0062576835,0.0026466744,0.0017542368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058502434,0.0021819791,0.003000007,0.0010462572,0.0038914832,0.005717771,0.004918257,0.0033252002,0.0049801283],"category_scores_gemma":[0.029787904,0.0014176213,0.0022646831,0.0018378979,0.004040869,0.0059587806,0.0031038136,0.0065752603,0.0021028577],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0025518101,0.00066011527,0.0063570575,0.0008811266,0.00033664142,0.00025237192,0.0007120952,0.49934086,0.03178906,0.37897992,0.014089169,0.064049825],"study_design_scores_gemma":[0.00016683586,0.0002866592,0.0003914544,0.00004454422,0.00006879138,0.00009605755,0.00006597923,0.8281738,0.009752931,0.15741472,0.0034771448,0.00006105108],"about_ca_topic_score_codex":0.005746998,"about_ca_topic_score_gemma":0.0059871054,"teacher_disagreement_score":0.007656362,"about_ca_system_score_codex":0.007656362,"about_ca_system_score_gemma":0.011920064,"threshold_uncertainty_score":0.055551052},"labels":[],"label_agreement":null},{"id":"W2467644617","doi":"10.1007/s00224-015-9649-x","title":"On the Advice Complexity of the k-server Problem Under Sparse Metrics","year":2015,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Treewidth; Advice (programming); Combinatorics; Binary logarithm; Competitive analysis; Mathematics; Online algorithm; Metric space; Discrete mathematics; Upper and lower bounds; Sequence (biology); Metric (unit); Tree (set theory); Deterministic algorithm; Path (computing); Time complexity; Graph; Algorithm; Computer science; Pathwidth; Line graph","score_opus":0.12073271240766795,"score_gpt":0.2864676065370435,"score_spread":0.16573489412937556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2467644617","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31414837,0.006309311,0.58498913,0.03573401,0.0008123221,0.0004250627,0.003091337,0.0011918347,0.05329864],"genre_scores_gemma":[0.8930582,0.00393094,0.07613857,0.0018669915,0.0017796989,0.000577081,0.002030386,0.0007918868,0.019826174],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9934783,0.0027484137,0.00031007503,0.0008764483,0.0015355223,0.0010512561],"domain_scores_gemma":[0.8734667,0.11209063,0.0034549467,0.0040918333,0.0036139209,0.003282044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063918117,0.0020249565,0.0048185545,0.0022478567,0.0021614332,0.0060332534,0.005597012,0.0058062826,0.019089915],"category_scores_gemma":[0.08712261,0.0014570722,0.0014566053,0.0039053925,0.0053131804,0.017245056,0.0055116443,0.007830597,0.0015189325],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001206994,0.0003769221,0.003075483,0.0007630459,0.00015153535,0.00026435088,0.00074979995,0.24396513,0.0017989305,0.68873376,0.024891311,0.03402265],"study_design_scores_gemma":[0.0001094889,0.00004868996,0.0005422097,0.00004585524,0.000029751569,0.00007066924,0.00010217427,0.47733825,0.00021155662,0.52066714,0.00080119,0.000033033804],"about_ca_topic_score_codex":0.0073581454,"about_ca_topic_score_gemma":0.0067596273,"teacher_disagreement_score":0.019089915,"about_ca_system_score_codex":0.005153745,"about_ca_system_score_gemma":0.0051329494,"threshold_uncertainty_score":0.063862085},"labels":[],"label_agreement":null},{"id":"W2472280164","doi":"10.1007/s00224-016-9691-3","title":"Multi-processor Search and Scheduling Problems with Setup Cost","year":2016,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Schedule; Scheduling (production processes); Mathematical optimization; Set (abstract data type); Multiprocessing; Dynamic programming; Computation; Multiprocessor scheduling; Job shop scheduling; Parallel computing; Algorithm; Mathematics; Flow shop scheduling","score_opus":0.03973861380122752,"score_gpt":0.273707058850325,"score_spread":0.23396844504909747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2472280164","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050144415,0.004331075,0.9240896,0.0041803033,0.00070962723,0.0004184745,0.0008542568,0.00048539124,0.014786862],"genre_scores_gemma":[0.67352235,0.0031473115,0.29302862,0.00064697885,0.00117887,0.0011601269,0.00097498234,0.00065816706,0.025682587],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99572766,0.0022851466,0.00017730711,0.00073144777,0.0005695551,0.0005088902],"domain_scores_gemma":[0.9822161,0.015135199,0.0009936353,0.00061239244,0.00043998373,0.00060268404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055874633,0.0024063783,0.0048552416,0.001940699,0.0015975587,0.0045157946,0.0044181915,0.005663723,0.015477228],"category_scores_gemma":[0.02505484,0.002375938,0.0020119117,0.0063190125,0.0025388992,0.0062841526,0.0024398537,0.0047044526,0.0011150886],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048966956,0.00024880742,0.0004503802,0.00050784746,0.00013945349,0.00017643106,0.00006365999,0.91152406,0.00049329974,0.058825422,0.0065678083,0.020513142],"study_design_scores_gemma":[0.00012667282,0.00006644563,0.00020175538,0.00002052458,0.000039704886,0.00004680726,0.0000320934,0.9392606,0.0001995169,0.05894977,0.001038124,0.000017973463],"about_ca_topic_score_codex":0.0042067138,"about_ca_topic_score_gemma":0.004603142,"teacher_disagreement_score":0.015477228,"about_ca_system_score_codex":0.0038734695,"about_ca_system_score_gemma":0.003291568,"threshold_uncertainty_score":0.05177653},"labels":[],"label_agreement":null},{"id":"W2474482100","doi":"10.1007/978-3-319-30139-6_12","title":"A General Framework for Searching on a Line","year":2016,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Carleton University","funders":"","keywords":"Competitive analysis; Constant (computer programming); Search cost; Computer science; Line (geometry); Mathematical optimization; Search problem; Alpha (finance); Upper and lower bounds; Mathematics; Statistics; Geometry","score_opus":0.041626329975788655,"score_gpt":0.3133174656662515,"score_spread":0.2716911356904629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2474482100","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0014433486,0.00047548668,0.9570434,0.00040946482,0.000114891845,0.00004320307,0.00014260023,0.0004068638,0.039920676],"genre_scores_gemma":[0.094395205,0.0016529621,0.8347287,0.0004319234,0.00028881885,0.0003625707,0.00050589826,0.0006965066,0.0669374],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99945956,0.0001333948,0.000033362,0.00013501344,0.00016543377,0.000073140975],"domain_scores_gemma":[0.9996649,0.00012145763,0.000020242902,0.000096101976,0.000068679874,0.00002862741],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050514133,0.00095717213,0.00077738485,0.0011643675,0.0014354521,0.0025812075,0.0029557634,0.0019437409,0.027696883],"category_scores_gemma":[0.0021661527,0.00058603374,0.0013683614,0.002134191,0.0019326176,0.004940284,0.0023849802,0.0022739365,0.0063946587],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000140644715,0.000012406314,0.00005811321,0.0000712904,0.0000062060476,0.00004601507,0.00010799418,0.013764696,0.00059468334,0.9473348,0.006470891,0.031518828],"study_design_scores_gemma":[0.000017243412,0.000022273514,0.00004370702,0.00003956237,0.0000108760005,0.00010229191,0.00005739396,0.09465502,0.00042634577,0.8456611,0.05894817,0.000016019283],"about_ca_topic_score_codex":0.0030982017,"about_ca_topic_score_gemma":0.0029504995,"teacher_disagreement_score":0.027696883,"about_ca_system_score_codex":0.0009677759,"about_ca_system_score_gemma":0.0007534447,"threshold_uncertainty_score":0.0926553},"labels":[],"label_agreement":null},{"id":"W2475185878","doi":"10.1007/11664550_7","title":"Getting Mobile Autonomous Robots to Rendezvous","year":2006,"lang":"en","type":"book-chapter","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Rendezvous; Task (project management); Robot; Computer science; Mobile robot; Global Positioning System; Human–computer interaction; Event (particle physics); Artificial intelligence; Real-time computing; Engineering; Telecommunications; Systems engineering","score_opus":0.018963955019881244,"score_gpt":0.24749992572950008,"score_spread":0.22853597070961884,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2475185878","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013293564,0.012962401,0.6605755,0.0018008434,0.0015157616,0.0001016087,0.00025663545,0.0031474477,0.30634624],"genre_scores_gemma":[0.077745475,0.014542659,0.28718072,0.0004615876,0.00037992487,0.00017139883,0.00070672994,0.0010356153,0.617776],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999323,0.0000049167193,0.0000018135653,0.000015624557,0.00003609198,0.000009223027],"domain_scores_gemma":[0.9999596,0.000013048864,0.000002634811,0.00000890621,0.000009807675,0.000006102142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007658296,0.0006687272,0.00040365526,0.00026534792,0.00052590104,0.0010419555,0.0006599205,0.0007684767,0.020267053],"category_scores_gemma":[0.00032105035,0.00037114,0.00029873895,0.0005168907,0.0005136389,0.0015096759,0.0008582784,0.0010877402,0.008739404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000043080436,0.000046637244,0.00016462497,0.00042442096,0.000018738674,0.00012105851,0.00041248955,0.018970378,0.016250007,0.16403912,0.09066075,0.70884866],"study_design_scores_gemma":[0.000016807047,0.00006630285,0.00036436654,0.00014271215,0.00001831053,0.000349708,0.00022915454,0.034331672,0.01190284,0.13720104,0.81535095,0.000026062016],"about_ca_topic_score_codex":0.00077368936,"about_ca_topic_score_gemma":0.001754166,"teacher_disagreement_score":0.020267053,"about_ca_system_score_codex":0.0002761163,"about_ca_system_score_gemma":0.000339748,"threshold_uncertainty_score":0.067799985},"labels":[],"label_agreement":null},{"id":"W2475215202","doi":"10.1145/2875441","title":"Multiagent Resource Allocation for Dynamic Task Arrivals with Preemption","year":2016,"lang":"en","type":"article","venue":"ACM Transactions on Intelligent Systems and Technology","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Preemption; Computer science; Leverage (statistics); Task (project management); Distributed computing; Proxy (statistics); Resource (disambiguation); Resource allocation; Multi-agent system; Computer network; Artificial intelligence; Machine learning","score_opus":0.018738801178144377,"score_gpt":0.2621758147648627,"score_spread":0.2434370135867183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2475215202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0124827465,0.00016086607,0.9853731,0.00015130283,0.00004190583,0.0000564525,0.000011838662,0.00025374896,0.0014680502],"genre_scores_gemma":[0.6685856,0.00021361868,0.3257443,0.00015056449,0.000079337755,0.00025016497,0.00005589166,0.00011958105,0.004800999],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99866533,0.00051890843,0.000079259684,0.00028782256,0.00027212966,0.00017649766],"domain_scores_gemma":[0.9980059,0.0010519626,0.0002485322,0.00026874963,0.00024657123,0.00017820379],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021145772,0.0008582163,0.0010504093,0.0005157133,0.001044677,0.0013345852,0.0019933633,0.0009953191,0.00209973],"category_scores_gemma":[0.005498401,0.00046105945,0.00049518864,0.00056462194,0.00084188464,0.0018694566,0.0018161591,0.0014568113,0.00050428114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013634171,0.00010149201,0.000536837,0.000075103635,0.00004086504,0.00014128596,0.00015488826,0.9195549,0.0030851823,0.026390174,0.0014772122,0.04830577],"study_design_scores_gemma":[0.000013088412,0.00002123701,0.000042249143,0.0000031942172,0.0000050454405,0.00002250996,0.000013432557,0.9922896,0.00040051856,0.006285051,0.0008999215,0.0000041822586],"about_ca_topic_score_codex":0.0029113202,"about_ca_topic_score_gemma":0.0028159465,"teacher_disagreement_score":0.0029113202,"about_ca_system_score_codex":0.0011236095,"about_ca_system_score_gemma":0.0016097985,"threshold_uncertainty_score":0.011183083},"labels":[],"label_agreement":null},{"id":"W2477849570","doi":"10.1145/2933057.2933102","title":"Search on a Line with Faulty Robots","year":2016,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Carleton University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Mobile robot; Line (geometry); Computer science; Competitive analysis; Real-time computing; Artificial intelligence; Mathematics","score_opus":0.05193294596895519,"score_gpt":0.2997933968503015,"score_spread":0.24786045088134628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2477849570","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30960548,0.0008416276,0.6782216,0.0011999885,0.000097397584,0.00012266607,0.00036229478,0.00056076085,0.0089881765],"genre_scores_gemma":[0.8624484,0.0004522781,0.12789187,0.0001845726,0.000094870215,0.00019521503,0.00037653864,0.000105543964,0.008250635],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991867,0.00028532036,0.000033003013,0.00021145678,0.00012374151,0.00015972133],"domain_scores_gemma":[0.99717927,0.0018546804,0.0004121722,0.00015798118,0.00021582638,0.0001800252],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010533083,0.0011089351,0.0014003769,0.0007259951,0.0009946537,0.0013807584,0.0017703982,0.002285532,0.0042215213],"category_scores_gemma":[0.005035956,0.00060804345,0.0006453684,0.0012132435,0.0013279155,0.0018766258,0.0011592683,0.0008257437,0.00068897766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003582705,0.00006334902,0.0006916166,0.00008411525,0.000042566597,0.00028899167,0.000054816115,0.9820369,0.0014296592,0.0052005057,0.0007542319,0.008995019],"study_design_scores_gemma":[0.00006353815,0.00009758887,0.00012536325,0.0000042527936,0.000009786908,0.00006104987,0.000027844833,0.99218094,0.00044891113,0.006491317,0.00048320316,0.000006279937],"about_ca_topic_score_codex":0.005125338,"about_ca_topic_score_gemma":0.0027818296,"teacher_disagreement_score":0.005125338,"about_ca_system_score_codex":0.0010449508,"about_ca_system_score_gemma":0.0005954243,"threshold_uncertainty_score":0.0141224265},"labels":[],"label_agreement":null},{"id":"W2479012228","doi":"10.1007/978-3-540-31595-7_8","title":"Pursuit Strategies for Autonomous Agents","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in control and information sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mobile robot; Task (project management); Autonomous agent; Control (management); Artificial intelligence; Robot; Group (periodic table); Computer science; Subject (documents); Engineering; Distributed computing; Control engineering; Human–computer interaction; Systems engineering","score_opus":0.02463485298370909,"score_gpt":0.2696630236527044,"score_spread":0.2450281706689953,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2479012228","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041588265,0.005043473,0.83185387,0.0016006602,0.00028398554,0.00009904665,0.00008919288,0.00025294427,0.11918861],"genre_scores_gemma":[0.75110024,0.004587766,0.14775494,0.00027709288,0.0002239494,0.00038133023,0.00018901247,0.000105261206,0.0953805],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979573,0.000062394116,0.000011097519,0.000029599254,0.00007452188,0.000026665955],"domain_scores_gemma":[0.9997261,0.0001541162,0.000025782212,0.00002421636,0.000043760512,0.000026000636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042725168,0.0007344563,0.0006054706,0.00042806313,0.00045444025,0.0013997495,0.0007741329,0.0011324902,0.0040970896],"category_scores_gemma":[0.001764867,0.00029230549,0.00038606228,0.00057608355,0.0009806653,0.0013050844,0.0013797843,0.0012487301,0.0006527456],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048148515,0.000033407337,0.00012933643,0.000103866085,0.0000251967,0.00006441509,0.00017225194,0.09150097,0.0016496531,0.8433246,0.0044298684,0.058518294],"study_design_scores_gemma":[0.000028942632,0.000043196796,0.000091652706,0.000021744485,0.000009636549,0.00004143801,0.000057835903,0.3298011,0.00040043748,0.6621132,0.0073807794,0.0000100504585],"about_ca_topic_score_codex":0.0012000221,"about_ca_topic_score_gemma":0.00077916036,"teacher_disagreement_score":0.0040970896,"about_ca_system_score_codex":0.0007192173,"about_ca_system_score_gemma":0.00051363057,"threshold_uncertainty_score":0.013706207},"labels":[],"label_agreement":null},{"id":"W2488817718","doi":"10.1007/978-3-642-51182-0","title":"Advances in Markov-Switching Models","year":2002,"lang":"en","type":"book","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Markov chain; Computer science; Machine learning","score_opus":0.024007311892284295,"score_gpt":0.24729614016398255,"score_spread":0.22328882827169824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2488817718","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045041563,0.14074184,0.6671654,0.009190327,0.00674619,0.000082848295,0.0013393882,0.00090295484,0.16932689],"genre_scores_gemma":[0.17609487,0.315632,0.26454714,0.0036218972,0.011008506,0.00053047953,0.003935756,0.0008800169,0.2237494],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99907,0.0002320821,0.000053206335,0.00017753738,0.00041060243,0.000056556022],"domain_scores_gemma":[0.9978549,0.0016035654,0.000078963756,0.00018489984,0.00022515887,0.000052511285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012212825,0.0012920125,0.0012464586,0.0014584194,0.0004992923,0.0020582606,0.0010974623,0.0012709837,0.010464814],"category_scores_gemma":[0.0044212886,0.0008415494,0.0014863824,0.0026792102,0.0010869871,0.002665183,0.0010804402,0.0037409395,0.0035937852],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000026087297,0.000050595234,0.0003331324,0.00056921435,0.00008874669,0.00012569486,0.00014410973,0.04972957,0.0004565677,0.72289205,0.08038624,0.14519794],"study_design_scores_gemma":[0.000012978777,0.000027582979,0.00039304153,0.00023179743,0.00003819731,0.00020860406,0.000026339296,0.10810372,0.0002662642,0.63710517,0.25355405,0.000032320986],"about_ca_topic_score_codex":0.0028184124,"about_ca_topic_score_gemma":0.0025053201,"teacher_disagreement_score":0.010464814,"about_ca_system_score_codex":0.0016609487,"about_ca_system_score_gemma":0.0015626544,"threshold_uncertainty_score":0.03500831},"labels":[],"label_agreement":null},{"id":"W2489221610","doi":"10.1109/acc.2016.7526682","title":"Stochastic patrolling in adversarial settings","year":2016,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Patrolling; Markov chain; Computer science; Adversarial system; Mathematical optimization; Markov process; Path (computing); Mathematics; Artificial intelligence; Computer network; Machine learning; Statistics","score_opus":0.010353518433518975,"score_gpt":0.2301791471882417,"score_spread":0.21982562875472272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2489221610","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11177034,0.00036629123,0.8829759,0.0006277028,0.000041663658,0.00008472954,0.00014339274,0.00028587686,0.003704157],"genre_scores_gemma":[0.95178497,0.00033291118,0.043240093,0.00012481408,0.0000485281,0.00011461484,0.000120773955,0.000078807214,0.004154556],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983259,0.0007589391,0.000057423687,0.0003824852,0.00021203842,0.00026315177],"domain_scores_gemma":[0.99247605,0.005450406,0.0010018356,0.00049450697,0.00021255806,0.00036456258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016974491,0.0010717108,0.0012472556,0.00065288873,0.00060005405,0.0011827709,0.0012879622,0.0016890503,0.0022621835],"category_scores_gemma":[0.0069589536,0.00071663625,0.0008460742,0.0006114848,0.0022053649,0.0020647026,0.0015291243,0.0016723234,0.00026549114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049822225,0.000024852918,0.00032618782,0.000022706274,0.000025973428,0.00006378172,0.000024063362,0.9756693,0.00062888797,0.020300115,0.00025190966,0.002612431],"study_design_scores_gemma":[0.000008724395,0.000029527202,0.00010979856,0.0000033932017,0.000005521395,0.000018084836,0.00000923306,0.978381,0.00021103378,0.021027,0.00019089637,0.0000058733926],"about_ca_topic_score_codex":0.0025504066,"about_ca_topic_score_gemma":0.0020845702,"teacher_disagreement_score":0.0025504066,"about_ca_system_score_codex":0.0015100769,"about_ca_system_score_gemma":0.00072368694,"threshold_uncertainty_score":0.010956466},"labels":[],"label_agreement":null},{"id":"W2491829515","doi":"10.1016/j.tcs.2015.09.011","title":"The Beachcombers' Problem: Walking and searching with mobile robots","year":2015,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Waterloo; Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Schedule; Mobile robot; Set (abstract data type); Computer science; Algorithm; Line segment; Real-time computing; Artificial intelligence","score_opus":0.012996402439254037,"score_gpt":0.26030036725639494,"score_spread":0.2473039648171409,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2491829515","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09661519,0.0029320768,0.8785539,0.0029192844,0.00038140223,0.00012676041,0.0003782927,0.00027711136,0.01781598],"genre_scores_gemma":[0.6649534,0.0027700062,0.28804043,0.0004308583,0.00030533815,0.00026791764,0.0005521751,0.00017803082,0.04250179],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999642,0.00012865583,0.000016979679,0.00009848282,0.00007158331,0.00004228098],"domain_scores_gemma":[0.9993112,0.00045320462,0.000055862118,0.00006619256,0.000040850893,0.00007266413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005329707,0.0006806701,0.0010838592,0.00060681585,0.0009531616,0.001510284,0.001657647,0.003808054,0.0060696956],"category_scores_gemma":[0.0041774646,0.00063352316,0.0008020423,0.0012614838,0.0015348529,0.0027343663,0.0019931383,0.0014309831,0.00061003945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006167785,0.00017859548,0.001815453,0.00055061834,0.00013147134,0.0007028281,0.00047229294,0.5629424,0.0031806498,0.24976745,0.018121397,0.16152011],"study_design_scores_gemma":[0.000120578,0.00011402332,0.00051481486,0.0000503642,0.000029168219,0.00029134238,0.0002697788,0.7842691,0.0010494267,0.20138343,0.011871423,0.000036539222],"about_ca_topic_score_codex":0.0034492856,"about_ca_topic_score_gemma":0.0034685754,"teacher_disagreement_score":0.0060696956,"about_ca_system_score_codex":0.0004298337,"about_ca_system_score_gemma":0.0006267554,"threshold_uncertainty_score":0.020305157},"labels":[],"label_agreement":null},{"id":"W2497949436","doi":"10.1016/j.ejor.2016.07.057","title":"A new lift-and-project operator","year":2016,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Operator (biology); Lift (data mining); Mathematics; Set (abstract data type); Hull; Binary number; Combinatorics; Integer (computer science); Computer science; Discrete mathematics; Data mining; Arithmetic; Engineering","score_opus":0.1280800995088859,"score_gpt":0.38667762288483915,"score_spread":0.2585975233759532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2497949436","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0074028177,0.0001742922,0.97667694,0.0005421854,0.0006785276,0.00007607788,0.00014262223,0.0004873962,0.013819144],"genre_scores_gemma":[0.26648134,0.0006278646,0.6845508,0.000773805,0.0011105163,0.0003337018,0.00038772082,0.0006279895,0.045106266],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99884856,0.0002274803,0.00007618131,0.00024159168,0.0004639841,0.00014206831],"domain_scores_gemma":[0.99908316,0.00023630584,0.00007114227,0.00020263958,0.00020041937,0.00020633382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012861021,0.0009739562,0.0009675854,0.00095500605,0.0009944442,0.001685188,0.0017101152,0.0017953406,0.016163303],"category_scores_gemma":[0.0028294122,0.00030530526,0.0009534222,0.0010432622,0.0015900182,0.0033673085,0.0042646653,0.0022813897,0.0025386335],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035192104,0.0002219934,0.000417275,0.00020164768,0.00003713797,0.00039156913,0.00017173422,0.023400275,0.02161558,0.6823167,0.018603576,0.2522706],"study_design_scores_gemma":[0.00017767448,0.0003643014,0.00026836694,0.000045132547,0.000045864792,0.000998502,0.0001057774,0.4302814,0.008402037,0.5067648,0.052446812,0.00009943446],"about_ca_topic_score_codex":0.00047748093,"about_ca_topic_score_gemma":0.0005460815,"teacher_disagreement_score":0.016163303,"about_ca_system_score_codex":0.0004746382,"about_ca_system_score_gemma":0.0013082138,"threshold_uncertainty_score":0.054071605},"labels":[],"label_agreement":null},{"id":"W25030497","doi":"10.1007/978-3-642-25873-2_29","title":"Asynchronous Rendezvous of Anonymous Agents in Arbitrary Graphs","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Asynchronous communication; Computer science; Graph; Theoretical computer science; Algorithm; Computer network","score_opus":0.03403932489494358,"score_gpt":0.2595617817778395,"score_spread":0.22552245688289593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W25030497","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36270028,0.0005334324,0.58302647,0.00059808313,0.00028108462,0.00013950454,0.00020143128,0.0012603757,0.05125942],"genre_scores_gemma":[0.93219453,0.00030701,0.045133013,0.000074129326,0.00008583584,0.00010404637,0.00013939604,0.00026483135,0.021697288],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991239,0.0002391663,0.00003981994,0.00022074256,0.00019127082,0.000185165],"domain_scores_gemma":[0.99659026,0.0018318195,0.00026053688,0.0006962043,0.00024611352,0.0003750169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081616663,0.0005718624,0.00090026605,0.0009214415,0.0018874661,0.0016552545,0.0021836378,0.0010549955,0.004908507],"category_scores_gemma":[0.0051547377,0.0005657306,0.00075122004,0.00088200613,0.0017048207,0.0036714904,0.0028502836,0.0015924611,0.0007541185],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00069782283,0.00010023212,0.0007167901,0.00019183176,0.000062635314,0.0005025328,0.0010245179,0.15002824,0.010176111,0.79736495,0.0039446587,0.03518964],"study_design_scores_gemma":[0.000098083125,0.00007253968,0.00027104048,0.000024285773,0.000044897763,0.00018097163,0.0003564117,0.44783822,0.0054131714,0.5394169,0.0062480215,0.000035533652],"about_ca_topic_score_codex":0.0021245263,"about_ca_topic_score_gemma":0.0023912997,"teacher_disagreement_score":0.004908507,"about_ca_system_score_codex":0.000812252,"about_ca_system_score_gemma":0.0006230931,"threshold_uncertainty_score":0.016420603},"labels":[],"label_agreement":null},{"id":"W2513559281","doi":"10.1007/s10878-016-0079-8","title":"On the online multi-agent O–D k-Canadian Traveler Problem","year":2016,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Disjoint sets; Computer science; Focus (optics); Theory of computation; Graph; A priori and a posteriori; Enhanced Data Rates for GSM Evolution; Node (physics); Competitive analysis; Combinatorics; Theoretical computer science; Mathematics; Upper and lower bounds; Artificial intelligence; Algorithm","score_opus":0.026356182436590086,"score_gpt":0.2547440991462963,"score_spread":0.22838791670970623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2513559281","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39163995,0.0042994833,0.47079757,0.011214316,0.00082423567,0.0013402074,0.005276953,0.00089970144,0.1137076],"genre_scores_gemma":[0.88440025,0.0014009966,0.07497565,0.0007949595,0.00022682264,0.00037802692,0.0020296506,0.00026493205,0.035528883],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984591,0.0005384626,0.000056128138,0.00034111374,0.00014471626,0.00046037755],"domain_scores_gemma":[0.99579054,0.0026129647,0.00030903786,0.00024413843,0.00029633022,0.00074712845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020952306,0.0023520486,0.004352696,0.0014655859,0.0031127215,0.0035788605,0.005378807,0.0064008813,0.016768059],"category_scores_gemma":[0.008202987,0.0010570855,0.0014544999,0.0031701035,0.0025799002,0.0047106678,0.0036908782,0.0027839206,0.0010229201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010999016,0.00033953474,0.0014554774,0.00042712066,0.0001875722,0.00048089586,0.00024237492,0.86529905,0.00043433785,0.08614002,0.023494529,0.020399073],"study_design_scores_gemma":[0.00016961194,0.00011850221,0.00036411308,0.00004078769,0.0000545936,0.00007999387,0.00026073633,0.9544687,0.00016400439,0.040297497,0.003939384,0.00004203001],"about_ca_topic_score_codex":0.1330462,"about_ca_topic_score_gemma":0.09470004,"teacher_disagreement_score":0.1330462,"about_ca_system_score_codex":0.0055462467,"about_ca_system_score_gemma":0.006119312,"threshold_uncertainty_score":0.2645436},"labels":[],"label_agreement":null},{"id":"W2517199428","doi":"10.1145/2970398.2970430","title":"Total Recall","year":2016,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Mars Exploration Program; Recall; Cache; Information retrieval; Martian; Latency (audio); World Wide Web; Computer network; Astrobiology; Telecommunications","score_opus":0.01610766868185716,"score_gpt":0.2363649852544086,"score_spread":0.22025731657255143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2517199428","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.096484885,0.01444427,0.5104311,0.005172801,0.0019131071,0.0010450396,0.016811943,0.0067348313,0.346962],"genre_scores_gemma":[0.7544155,0.005514788,0.09654372,0.0016896201,0.0010744059,0.0008806675,0.015986636,0.0011254384,0.12276913],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99506795,0.0008276036,0.0005175524,0.0014794779,0.0014446593,0.00066274585],"domain_scores_gemma":[0.99194944,0.0026139466,0.0004171804,0.0031126135,0.0016682347,0.0002385684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028132242,0.0015097283,0.0018238401,0.0021088587,0.0016459516,0.0043421304,0.002592206,0.0013970282,0.057634503],"category_scores_gemma":[0.020330964,0.00046044216,0.0016083714,0.0028112158,0.0012999183,0.0068576247,0.0027396402,0.0014687239,0.0155564435],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011829436,0.0003508784,0.009060083,0.0016088368,0.00037249958,0.00032487357,0.0007381614,0.020699983,0.0032611697,0.22961323,0.092683144,0.6401041],"study_design_scores_gemma":[0.00026900362,0.0009471213,0.0058300416,0.0003615513,0.000528986,0.0024340586,0.00084957964,0.06669673,0.008255547,0.70964974,0.20400609,0.00017159418],"about_ca_topic_score_codex":0.0033245792,"about_ca_topic_score_gemma":0.0033436967,"teacher_disagreement_score":0.057634503,"about_ca_system_score_codex":0.0017249214,"about_ca_system_score_gemma":0.0024142265,"threshold_uncertainty_score":0.1928066},"labels":[],"label_agreement":null},{"id":"W2519829944","doi":"10.1002/net.20233","title":"Approximation bounds for Black Hole Search problems","year":2008,"lang":"en","type":"article","venue":"Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Node (physics); Computer science; Black hole (networking); Black box; Set (abstract data type); Time complexity; Process (computing); Task (project management); Approximation algorithm; Theoretical computer science; Algorithm; Computer network; Artificial intelligence; Physics","score_opus":0.04569803779833919,"score_gpt":0.2672764333897557,"score_spread":0.2215783955914165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2519829944","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14232229,0.009391626,0.768687,0.0122745875,0.00064404093,0.0005543108,0.0022080282,0.003897461,0.06002072],"genre_scores_gemma":[0.67675585,0.0035552566,0.2984015,0.0018185118,0.00065106706,0.0008072711,0.003403295,0.0012063106,0.013400939],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99529713,0.0014867436,0.00022410248,0.00084796274,0.0010189158,0.0011251153],"domain_scores_gemma":[0.978693,0.016679926,0.0009134464,0.0021403953,0.00075687945,0.00081644976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005030249,0.0029214018,0.0028270117,0.0017432352,0.002046162,0.0051978063,0.0042743324,0.002951806,0.012909384],"category_scores_gemma":[0.023036858,0.0008669325,0.002536654,0.0025325827,0.002547989,0.010395797,0.004122124,0.0058968524,0.0020244468],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002769681,0.00091149216,0.0046674474,0.0013409252,0.00042298072,0.00027625967,0.000891641,0.5960666,0.0037860607,0.24078816,0.036389597,0.11168915],"study_design_scores_gemma":[0.00018614264,0.00013345481,0.0005101138,0.00010569375,0.00011708429,0.00015962856,0.00017012106,0.7376651,0.0012204017,0.25387,0.005839984,0.000022297669],"about_ca_topic_score_codex":0.004371668,"about_ca_topic_score_gemma":0.0043143826,"teacher_disagreement_score":0.012909384,"about_ca_system_score_codex":0.00526238,"about_ca_system_score_gemma":0.0033058913,"threshold_uncertainty_score":0.043186188},"labels":[],"label_agreement":null},{"id":"W2521963297","doi":"","title":"Tight bounds on the competitive ratio on accomodating sequences for the seat reservation problem","year":2000,"lang":"en","type":"article","venue":"Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation; Centrum Wiskunde and Informatica; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; European Research Consortium for Informatics and Mathematics; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Reservation; Competitive analysis; Upper and lower bounds; Matching (statistics); Combinatorics; Line (geometry); Asymptotically optimal algorithm; Computer science; Mathematics; Discrete mathematics; Mathematical optimization; Computer network; Statistics","score_opus":0.11407420941787147,"score_gpt":0.36277077989047674,"score_spread":0.24869657047260527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2521963297","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30161878,0.003909056,0.56890404,0.0071440227,0.00053250685,0.0010327463,0.0014798129,0.0027476747,0.11263136],"genre_scores_gemma":[0.83633715,0.0031838352,0.14027137,0.0016511402,0.00079813,0.0009961575,0.0015088612,0.0010877346,0.01416571],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9875947,0.0037545755,0.00040443844,0.0017226303,0.0030306182,0.0034929786],"domain_scores_gemma":[0.9384238,0.04989833,0.002672154,0.00470372,0.0017542322,0.002547783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0107114995,0.0037311495,0.0039986027,0.0030255658,0.003549772,0.006645465,0.0062263296,0.004274369,0.016858762],"category_scores_gemma":[0.059086263,0.0012191376,0.002067475,0.0043605766,0.0045342715,0.010661078,0.00501417,0.0058850846,0.0032120934],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0056310133,0.0019993435,0.0037328652,0.0008714192,0.00029477105,0.00030762516,0.0007024714,0.45439914,0.011940915,0.3691173,0.020618483,0.13038474],"study_design_scores_gemma":[0.00027411434,0.0004897898,0.00063478,0.00010303521,0.00009589468,0.00029072296,0.00015725818,0.77339274,0.00422279,0.21575503,0.004525012,0.00005885445],"about_ca_topic_score_codex":0.004959978,"about_ca_topic_score_gemma":0.004979644,"teacher_disagreement_score":0.016858762,"about_ca_system_score_codex":0.006534741,"about_ca_system_score_gemma":0.006728529,"threshold_uncertainty_score":0.056648552},"labels":[],"label_agreement":null},{"id":"W2526250255","doi":"10.1007/978-3-540-28629-5_34","title":"Graph Exploration by a Finite Automaton","year":2004,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Traverse; Planar graph; Graph; Combinatorics; Discrete mathematics; Butterfly graph; Book embedding; Mathematics; Computer science; Voltage graph; Topology (electrical circuits); Line graph; 1-planar graph","score_opus":0.022123243478462947,"score_gpt":0.25036453029300454,"score_spread":0.2282412868145416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526250255","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.155582,0.0004722669,0.7938519,0.00070812146,0.00015206577,0.00010859756,0.00031975206,0.0025928994,0.046212345],"genre_scores_gemma":[0.79068863,0.00027969107,0.19147673,0.00010858818,0.000029691057,0.0001744506,0.00024352573,0.00033161184,0.016667048],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997714,0.000065342,0.0000129922,0.00007057613,0.000049179613,0.000030505405],"domain_scores_gemma":[0.99894565,0.00074928626,0.00003261077,0.00016136274,0.00006032452,0.00005069221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024870294,0.00033314154,0.00051084603,0.00051957817,0.0007729844,0.0009980059,0.0008645539,0.0008877842,0.008086923],"category_scores_gemma":[0.0018772734,0.0003372882,0.0010471372,0.0006175728,0.0012382959,0.0016600578,0.0012270416,0.0010325271,0.0006556932],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027066542,0.00009964406,0.0012364184,0.00028880904,0.00006895629,0.0004136123,0.00059125334,0.22351871,0.017259344,0.65605575,0.0046299305,0.09556697],"study_design_scores_gemma":[0.00003519395,0.000052631414,0.00018016473,0.000029203782,0.00002571443,0.00012463387,0.00006425651,0.52191526,0.0037855394,0.46863687,0.005131782,0.000018685038],"about_ca_topic_score_codex":0.0017708938,"about_ca_topic_score_gemma":0.0022352608,"teacher_disagreement_score":0.008086923,"about_ca_system_score_codex":0.0005813927,"about_ca_system_score_gemma":0.00054368883,"threshold_uncertainty_score":0.027053416},"labels":[],"label_agreement":null},{"id":"W2530140542","doi":"","title":"Dynamic Storage Provisioning with SLO Guarantees","year":2010,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"University of Waterloo","keywords":"Provisioning; Computer science; Computer network","score_opus":0.0056564532632080895,"score_gpt":0.20024668093763975,"score_spread":0.19459022767443165,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2530140542","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.109052695,0.0007719752,0.862265,0.0010253686,0.000078215366,0.00021353229,0.0003608652,0.0014371711,0.024795044],"genre_scores_gemma":[0.86938614,0.00026715433,0.12650281,0.00011655903,0.000044301316,0.00010822088,0.00019276218,0.00012150103,0.0032605613],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990256,0.000279054,0.000054561533,0.00014826354,0.00028128744,0.00021124836],"domain_scores_gemma":[0.9987992,0.00045528248,0.0001721826,0.0002697637,0.00022342238,0.000080217644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010797854,0.0006888388,0.0007480508,0.00060295465,0.00070264935,0.0017433952,0.00103993,0.0008700876,0.0026878843],"category_scores_gemma":[0.0031668355,0.0005101001,0.00053473696,0.0010901453,0.0005462122,0.0017983717,0.0013980045,0.00081519195,0.00043060945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017229292,0.00010517471,0.0013173816,0.00013852524,0.00003259136,0.00014212303,0.000100978985,0.8858543,0.007615449,0.02702227,0.0035510925,0.073947735],"study_design_scores_gemma":[0.000011610279,0.000033912565,0.00035532558,0.000011874937,0.000009795268,0.00005495216,0.000046958092,0.9835517,0.0016135913,0.011899567,0.0024021366,0.000008610157],"about_ca_topic_score_codex":0.0023495683,"about_ca_topic_score_gemma":0.0033277518,"teacher_disagreement_score":0.0026878843,"about_ca_system_score_codex":0.0008618753,"about_ca_system_score_gemma":0.0016926659,"threshold_uncertainty_score":0.0089918375},"labels":[],"label_agreement":null},{"id":"W2535803352","doi":"10.1007/s00453-016-0233-9","title":"When Patrolmen Become Corrupted: Monitoring a Graph Using Faulty Mobile Robots","year":2016,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"Mitacs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Patrolling; Theory of computation; Eulerian path; Enhanced Data Rates for GSM Evolution; Mobile robot; Domain (mathematical analysis); Robot; Computer science; Graph; Line segment; Combinatorics; Mathematics; Line (geometry); Point (geometry); Algorithm; Discrete mathematics; Artificial intelligence","score_opus":0.03223269614456528,"score_gpt":0.2869592527689605,"score_spread":0.25472655662439525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2535803352","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8437573,0.000247046,0.15218326,0.0014241533,0.00013548085,0.00004990112,0.00024107385,0.00052095496,0.0014408273],"genre_scores_gemma":[0.98735994,0.00004111667,0.011859402,0.00005264176,0.000020885916,0.000011983721,0.00012074379,0.000034252524,0.0004992187],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999084,0.00019352548,0.00003409142,0.00029308663,0.00020723442,0.00018814571],"domain_scores_gemma":[0.99382436,0.0033365954,0.001177828,0.0006450144,0.00057387975,0.0004422467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009610906,0.0007150447,0.00093421363,0.000979767,0.0009073755,0.0010888666,0.0025750704,0.0028462356,0.0010162654],"category_scores_gemma":[0.011482044,0.00071805133,0.00045503472,0.0008588928,0.0015732776,0.00253856,0.0012348786,0.0012285443,0.00015968093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011931146,0.00024843964,0.04075584,0.00018408214,0.00018741412,0.0028516976,0.0007219434,0.8913712,0.0087862685,0.005927975,0.0035101532,0.044261813],"study_design_scores_gemma":[0.000021157946,0.00008565619,0.0038767697,0.000009710501,0.000040101746,0.00021399543,0.00034769587,0.9859768,0.0023935663,0.006669696,0.00035120104,0.000013572721],"about_ca_topic_score_codex":0.007383296,"about_ca_topic_score_gemma":0.008394386,"teacher_disagreement_score":0.007383296,"about_ca_system_score_codex":0.0007602601,"about_ca_system_score_gemma":0.00065126293,"threshold_uncertainty_score":0.014680624},"labels":[],"label_agreement":null},{"id":"W2550472248","doi":"10.1016/j.tcs.2016.11.019","title":"Evacuating two robots from multiple unknown exits in a circle","year":2016,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Parameterized complexity; Mobile robot; Simple (philosophy); Computer science; Control (management); Mathematics; Domain (mathematical analysis); Algorithm; Topology (electrical circuits); Artificial intelligence; Combinatorics; Mathematical analysis","score_opus":0.017454379383506465,"score_gpt":0.27701269766194486,"score_spread":0.2595583182784384,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2550472248","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5990949,0.00030464234,0.3846512,0.0014548191,0.00027640825,0.000223899,0.00019015095,0.00074155384,0.013062343],"genre_scores_gemma":[0.9122266,0.000109930836,0.075119704,0.00009833408,0.000041069925,0.00011631214,0.00020010416,0.0000726936,0.0120151965],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992848,0.00015856195,0.000032396263,0.00022414004,0.00012422749,0.000175924],"domain_scores_gemma":[0.99812216,0.0008441504,0.00022645411,0.0002212197,0.00016041638,0.0004256319],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00084093586,0.000909897,0.001285131,0.0006012377,0.002633963,0.0015075627,0.0018091076,0.0032796473,0.003361567],"category_scores_gemma":[0.004284388,0.00077163585,0.0009365728,0.00053552195,0.0017016295,0.002240866,0.006597096,0.0019514831,0.0007818219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0022881285,0.00029504762,0.0073547466,0.00023364332,0.0002227795,0.005775692,0.0019183183,0.90405256,0.011680099,0.031038892,0.0030102564,0.03212975],"study_design_scores_gemma":[0.00013708333,0.0005238684,0.0011790778,0.00003927121,0.0000595131,0.00045129153,0.0011324431,0.9749893,0.0056653763,0.012340453,0.0034179753,0.00006428705],"about_ca_topic_score_codex":0.0034380779,"about_ca_topic_score_gemma":0.0027251227,"teacher_disagreement_score":0.0034380779,"about_ca_system_score_codex":0.0007637346,"about_ca_system_score_gemma":0.0010895494,"threshold_uncertainty_score":0.011245489},"labels":[],"label_agreement":null},{"id":"W2558107975","doi":"10.32920/24231049","title":"Search-and-Fetch with 2 Robots on a Disk: Wireless and Face-to-Face Communication Models","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; McMaster University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Treasure; Robot; Computer science; Wireless; Face (sociological concept); Drone; Protocol (science); Human–computer interaction; Artificial intelligence; Operating system; Geography; Medicine","score_opus":0.08521711455668612,"score_gpt":0.30682898132328595,"score_spread":0.22161186676659983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2558107975","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.100419484,0.0013929332,0.8584262,0.0038903086,0.00025141166,0.00021973232,0.0005606392,0.0003952248,0.034444004],"genre_scores_gemma":[0.871216,0.0017054237,0.08697635,0.0006064057,0.0003357563,0.0005617956,0.0003117463,0.00018351,0.038102966],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99843997,0.00053953216,0.000053725886,0.00029938156,0.000300047,0.00036734156],"domain_scores_gemma":[0.9914199,0.0057581137,0.0010923734,0.00081331696,0.0005186742,0.0003975278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016181798,0.0014008518,0.00156884,0.0009360447,0.0014090617,0.0022316033,0.0049424553,0.0036023688,0.009698263],"category_scores_gemma":[0.010244071,0.0006663609,0.0011359088,0.0013744163,0.002570845,0.007248047,0.0033567713,0.0028247987,0.0020420193],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040328843,0.00018172694,0.0005485381,0.00021844407,0.00003400736,0.00035008776,0.00036878843,0.7847259,0.0015277227,0.178598,0.00601597,0.027027491],"study_design_scores_gemma":[0.000023372439,0.000059618647,0.0000822542,0.000012323272,0.0000090404965,0.00007571544,0.000088637484,0.9684201,0.00033834425,0.029866077,0.0010086636,0.00001584963],"about_ca_topic_score_codex":0.0040730536,"about_ca_topic_score_gemma":0.00310189,"teacher_disagreement_score":0.009698263,"about_ca_system_score_codex":0.0017462107,"about_ca_system_score_gemma":0.00092399685,"threshold_uncertainty_score":0.03244394},"labels":[],"label_agreement":null},{"id":"W2560800565","doi":"10.14778/3137628.3137635","title":"Revenue maximization in incentivized social advertising","year":2017,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":61,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Submodular set function; Incentive; Revenue; Online advertising; Viral marketing; Monetization; Budget constraint; Knapsack problem; Microeconomics; Computer science; Social graph; Bidding; Advertising; Maximization; Social media; Business; Economics; The Internet; Mathematical optimization; Mathematics","score_opus":0.019394091572590408,"score_gpt":0.2669975460336904,"score_spread":0.2476034544611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2560800565","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10234477,0.0020880033,0.8599838,0.0042467783,0.0002625308,0.0005522731,0.0012458974,0.0012594571,0.02801654],"genre_scores_gemma":[0.7783884,0.0013094222,0.20319638,0.00087146705,0.00029680645,0.00049303443,0.0010229023,0.00035699853,0.014064591],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99707615,0.0013905051,0.000084638166,0.000592655,0.00033310527,0.000523078],"domain_scores_gemma":[0.9932025,0.005103923,0.0003838311,0.00051968836,0.0003329012,0.0004571812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003228744,0.0023119815,0.0029052044,0.0008404356,0.00089396595,0.0035407417,0.0032974598,0.0027610417,0.006620575],"category_scores_gemma":[0.011300501,0.0010882657,0.0016091993,0.0016497674,0.0019847306,0.0047348295,0.0025971124,0.00394913,0.0011597936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007705103,0.00054482353,0.0010951337,0.00062934915,0.00014899507,0.0003419334,0.00038849065,0.7115955,0.003264885,0.20727336,0.014331527,0.059615497],"study_design_scores_gemma":[0.0000917566,0.00006427991,0.00017813234,0.000033116117,0.000030405234,0.00009525766,0.00006566053,0.89958805,0.0007892948,0.096408024,0.0026377495,0.000018382409],"about_ca_topic_score_codex":0.00347565,"about_ca_topic_score_gemma":0.0032681483,"teacher_disagreement_score":0.006620575,"about_ca_system_score_codex":0.0038850782,"about_ca_system_score_gemma":0.0025754867,"threshold_uncertainty_score":0.028188348},"labels":[],"label_agreement":null},{"id":"W2561815760","doi":"10.1109/ssrr.2016.7784323","title":"Multi-target search strategies","year":2016,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Probabilistic logic; Search and rescue; Beam search; Schedule; Context (archaeology); Obstacle; Task (project management); Search algorithm; Machine learning; Artificial intelligence; Search problem; Data mining; Engineering; Algorithm; Robot","score_opus":0.04783042107704689,"score_gpt":0.30534309053157277,"score_spread":0.2575126694545259,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2561815760","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02028004,0.00055919663,0.9742464,0.00018444727,0.000034303324,0.00012254911,0.000065663044,0.00021478607,0.004292699],"genre_scores_gemma":[0.7679404,0.0005727299,0.22175446,0.00022998506,0.00004867853,0.0005155921,0.00022553546,0.00010932602,0.008603201],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99908125,0.0002535199,0.00007063301,0.00021873921,0.00026417238,0.000111710724],"domain_scores_gemma":[0.9981097,0.0011124596,0.00020371882,0.00022152708,0.00024963723,0.00010300895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012611336,0.0010844753,0.0010851641,0.0008427395,0.0005028318,0.00091187446,0.00233723,0.0013337402,0.0030483725],"category_scores_gemma":[0.0044403393,0.00044092015,0.00075116963,0.00080297224,0.0007526352,0.001901635,0.0019631989,0.0008545931,0.00079926365],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015568746,0.00007035899,0.0008819008,0.00015645653,0.00010426139,0.00014593397,0.0001020014,0.89659363,0.003257757,0.032462884,0.0016322529,0.06443693],"study_design_scores_gemma":[0.00002572844,0.00009527974,0.00011322241,0.00001060053,0.00001582298,0.000089570574,0.000024034569,0.9855312,0.0010985505,0.01155884,0.001426649,0.000010384419],"about_ca_topic_score_codex":0.0011611001,"about_ca_topic_score_gemma":0.0010545282,"teacher_disagreement_score":0.0030483725,"about_ca_system_score_codex":0.00058246346,"about_ca_system_score_gemma":0.00086369505,"threshold_uncertainty_score":0.010197759},"labels":[],"label_agreement":null},{"id":"W2563013149","doi":"10.1016/j.jcss.2016.11.008","title":"Collision-free network exploration","year":2016,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Node (physics); Upper and lower bounds; Network topology; Tree (set theory); Topology (electrical circuits); Collision; Mobile agent; Distributed computing; Computer network; Combinatorics; Mathematics; Computer security; Physics","score_opus":0.03322928801255541,"score_gpt":0.25679849622801937,"score_spread":0.22356920821546394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2563013149","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15772128,0.0008829802,0.7882025,0.0013503464,0.00018654249,0.0003422538,0.00033836885,0.0007109724,0.0502647],"genre_scores_gemma":[0.8421841,0.00029202926,0.13920175,0.00022643837,0.000053658918,0.0003203334,0.00024606203,0.00014208608,0.017333554],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963665,0.0001233125,0.000013168996,0.00006173165,0.000098724995,0.00006639445],"domain_scores_gemma":[0.9978816,0.001593533,0.00010532252,0.00016201168,0.00013682545,0.00012081322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079032447,0.0006730603,0.0010390928,0.0012566431,0.001091294,0.00088119885,0.0015588528,0.0015991353,0.008276407],"category_scores_gemma":[0.0058824574,0.0005385312,0.00072879496,0.0010453017,0.001098447,0.0018772224,0.0030529073,0.0010134488,0.00066962227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002971421,0.00008157875,0.0007337325,0.00009620938,0.000051984734,0.000093733826,0.000118832075,0.91859,0.0012109906,0.036326673,0.0032244876,0.039174587],"study_design_scores_gemma":[0.00003395843,0.000037153146,0.000092294315,0.000009306703,0.000009011338,0.000027908252,0.00002302838,0.9864667,0.0002434151,0.012416214,0.00063644187,0.0000045431843],"about_ca_topic_score_codex":0.003656162,"about_ca_topic_score_gemma":0.0044386783,"teacher_disagreement_score":0.008276407,"about_ca_system_score_codex":0.0007789013,"about_ca_system_score_gemma":0.0012182682,"threshold_uncertainty_score":0.027687311},"labels":[],"label_agreement":null},{"id":"W2564284893","doi":"10.1109/iros.2016.7759404","title":"Multi-target rendezvous search","year":2016,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; McGill University","keywords":"Computer science; Rendezvous; Beam search; Bidirectional search; Search algorithm; Beam stack search; Maxima and minima; Maxima; Search engine; Search problem; Best-first search; Iterative deepening depth-first search; Realization (probability); Probability distribution; Guided Local Search; Search theory; Local search (optimization); Artificial intelligence; Algorithm; Mathematics; Engineering; Statistics; Information retrieval","score_opus":0.04664574852945272,"score_gpt":0.29254187167391354,"score_spread":0.24589612314446083,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2564284893","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14071272,0.0010138855,0.84784156,0.00020586843,0.000027309872,0.00007190488,0.000056178123,0.0002423212,0.009828218],"genre_scores_gemma":[0.94268906,0.00030492156,0.053697508,0.000041095143,0.0000088647375,0.00006460292,0.000038090835,0.00003436766,0.0031214487],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972695,0.000063776715,0.000010744753,0.000070892864,0.00008446529,0.00004311671],"domain_scores_gemma":[0.999363,0.0004041025,0.00008021549,0.000049671165,0.00006605649,0.000037035217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049419864,0.0005142324,0.0006969709,0.0005277721,0.0003860577,0.0005453543,0.0006345502,0.0006895304,0.0019416765],"category_scores_gemma":[0.0022679726,0.00022814289,0.00044457463,0.00056040887,0.00059917883,0.0011266705,0.0009484325,0.00029800704,0.0002872093],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000944622,0.000023786382,0.0009008065,0.00008277281,0.000043729953,0.00014785655,0.00007733661,0.9522607,0.0042084237,0.016561756,0.00032067535,0.02527781],"study_design_scores_gemma":[0.000015755923,0.00009144733,0.00050346117,0.000009227384,0.000010563954,0.00016844974,0.000056318007,0.9854548,0.0022644629,0.010452023,0.00096136733,0.000012211282],"about_ca_topic_score_codex":0.0015987204,"about_ca_topic_score_gemma":0.0015137806,"teacher_disagreement_score":0.0019416765,"about_ca_system_score_codex":0.0005022278,"about_ca_system_score_gemma":0.0006033455,"threshold_uncertainty_score":0.006495595},"labels":[],"label_agreement":null},{"id":"W2567810766","doi":"10.1007/978-3-662-46018-4_5","title":"Fast Rendezvous with Advice","year":2015,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Computer science; Advice (programming); Oracle; Node (physics); Set (abstract data type); Upper and lower bounds; Integer (computer science); Algorithm; Theoretical computer science; Mathematics","score_opus":0.025126376839355112,"score_gpt":0.25765961762593964,"score_spread":0.23253324078658452,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2567810766","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015817314,0.0010800674,0.7602939,0.0006075993,0.00083868694,0.00015995526,0.0013965244,0.07162512,0.14818083],"genre_scores_gemma":[0.23309037,0.0011475958,0.5193824,0.00038737583,0.0002717372,0.00023114555,0.002761169,0.012539432,0.23018879],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994698,0.000051652798,0.000020108644,0.000097605436,0.0002576291,0.00010322243],"domain_scores_gemma":[0.99906033,0.00031523212,0.000024745576,0.00037986555,0.00017799067,0.000041878222],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005047659,0.0012897331,0.00087882247,0.0007784442,0.0008155206,0.0010724657,0.0015772472,0.0009918427,0.06522306],"category_scores_gemma":[0.0033033234,0.0005762247,0.00056911807,0.0007433397,0.00072114414,0.0021236695,0.0021067194,0.0015401037,0.026513955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000719308,0.000054766155,0.00054478244,0.0004915857,0.00005181043,0.00034522815,0.00047348515,0.013378158,0.020880472,0.102013275,0.13673006,0.7243171],"study_design_scores_gemma":[0.00026791455,0.00012404303,0.0006974351,0.00029097023,0.000103630075,0.0008218986,0.00027425517,0.1760274,0.05528029,0.2632069,0.50278974,0.00011551117],"about_ca_topic_score_codex":0.003367342,"about_ca_topic_score_gemma":0.004597116,"teacher_disagreement_score":0.06522306,"about_ca_system_score_codex":0.00047773382,"about_ca_system_score_gemma":0.0005895565,"threshold_uncertainty_score":0.21819288},"labels":[],"label_agreement":null},{"id":"W2567820845","doi":"10.2514/6.2017-1132","title":"Cooperative Searching Strategies for Distributed Sensor Networks","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer science; Wireless sensor network; Distributed computing; Computer network","score_opus":0.04810183111553763,"score_gpt":0.32928121409203864,"score_spread":0.281179382976501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2567820845","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039700393,0.0009590094,0.95226955,0.00038475217,0.00005660171,0.00009047257,0.00004408011,0.0001211114,0.0063741365],"genre_scores_gemma":[0.8991051,0.00067322154,0.0919094,0.000113738075,0.00006944989,0.0003952822,0.000078556506,0.00006998417,0.0075853737],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990324,0.0004209626,0.000046514815,0.00015392614,0.00023387457,0.0001122364],"domain_scores_gemma":[0.9966689,0.002417509,0.0002525007,0.00023136627,0.00030317542,0.0001265746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021040505,0.0010558944,0.0012166917,0.0009816501,0.00064105185,0.001196171,0.002280198,0.0015498955,0.0018328062],"category_scores_gemma":[0.007992991,0.00056461524,0.00057921384,0.0014028188,0.0011537188,0.0021379937,0.002014551,0.0008603942,0.00030520253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015353366,0.00009949901,0.00038540093,0.00014955441,0.00007329911,0.000092133596,0.00022887794,0.8694216,0.0020310383,0.075913295,0.0018569106,0.04959494],"study_design_scores_gemma":[0.000032849563,0.00006353042,0.00007509622,0.000009854296,0.0000132612895,0.000023968365,0.00004041062,0.95830697,0.00030582404,0.040457055,0.0006650302,0.000006086546],"about_ca_topic_score_codex":0.0017192077,"about_ca_topic_score_gemma":0.0013350785,"teacher_disagreement_score":0.002280198,"about_ca_system_score_codex":0.00082471396,"about_ca_system_score_gemma":0.0007799656,"threshold_uncertainty_score":0.011127353},"labels":[],"label_agreement":null},{"id":"W2568630404","doi":"10.1007/s00446-015-0253-8","title":"Time versus cost tradeoffs for deterministic rendezvous in networks","year":2015,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rendezvous; Benchmark (surveying); Computer science; Node (physics); Upper and lower bounds; Enhanced Data Rates for GSM Evolution; Integer (computer science); Theory of computation; Set (abstract data type); Binary logarithm; Mathematics; Algorithm; Mathematical optimization; Combinatorics; Artificial intelligence; Physics","score_opus":0.06831252283688527,"score_gpt":0.30887218951202783,"score_spread":0.24055966667514256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2568630404","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5569002,0.0046050004,0.39255688,0.0043338845,0.00022352657,0.0002779142,0.0005798864,0.00074395037,0.03977875],"genre_scores_gemma":[0.9692532,0.0006921851,0.025102047,0.000095465206,0.000069436464,0.00008858152,0.00008732137,0.00018036847,0.004431387],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975025,0.0010265359,0.00008914774,0.00027865302,0.00053389906,0.00056926697],"domain_scores_gemma":[0.9684124,0.028154077,0.0008288804,0.0011172255,0.00073653844,0.00075084047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052550193,0.0010606399,0.0017809549,0.0015250434,0.0014320387,0.0026614,0.0019900477,0.0021669338,0.0075133466],"category_scores_gemma":[0.032395903,0.0008982265,0.000653358,0.001830535,0.0023143564,0.004598316,0.002213795,0.001470198,0.00050891296],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013082961,0.000103824226,0.00054260367,0.00019230925,0.0000388788,0.00005493393,0.00019385434,0.9012066,0.002460046,0.06903172,0.0018437161,0.023023136],"study_design_scores_gemma":[0.00009167186,0.00013005923,0.00031958462,0.00002456058,0.000030777734,0.000042678806,0.00013875624,0.9494182,0.0011459985,0.048008587,0.0006294345,0.000019754865],"about_ca_topic_score_codex":0.004242463,"about_ca_topic_score_gemma":0.004186494,"teacher_disagreement_score":0.0075133466,"about_ca_system_score_codex":0.0033115665,"about_ca_system_score_gemma":0.0018633177,"threshold_uncertainty_score":0.0277915},"labels":[],"label_agreement":null},{"id":"W2572992153","doi":"","title":"WaterlooClarke: TREC 2015 Microblog Track.","year":2015,"lang":"en","type":"article","venue":"Text REtrieval Conference","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Victoria","funders":"","keywords":"Microblogging; Social media; Track (disk drive); Computer science; World Wide Web; Information retrieval; Narrative","score_opus":0.06991052720693956,"score_gpt":0.2990576984579198,"score_spread":0.22914717125098022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2572992153","genre_codex":"dataset","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011156387,0.014497669,0.009045472,0.020298978,0.008709198,0.003763945,0.7637238,0.03639557,0.13240899],"genre_scores_gemma":[0.015452468,0.0022649067,0.010816544,0.0022349008,0.0010488129,0.0011999257,0.82101303,0.002182941,0.14378646],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958507,0.00070485676,0.0002694079,0.0006292471,0.0020443632,0.00050142437],"domain_scores_gemma":[0.9856163,0.0015132027,0.00048468728,0.0013185964,0.008560801,0.0025064382],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007988935,0.004885445,0.0034770225,0.0077460385,0.005613895,0.008823962,0.0051492997,0.0031881763,0.11962767],"category_scores_gemma":[0.012368054,0.0017817765,0.0010185111,0.006711323,0.0016678355,0.00921065,0.002552829,0.004829469,0.09634684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006063212,0.000087638255,0.00011790295,0.000121920726,0.000017017732,0.00001699073,0.000016486256,0.00015840857,0.00035042866,0.00015831432,0.99229735,0.006596931],"study_design_scores_gemma":[0.0010393327,0.00033989098,0.01294559,0.00037627437,0.0001363901,0.00012805112,0.00033932552,0.011275042,0.0061328965,0.0033639888,0.9636944,0.00022873454],"about_ca_topic_score_codex":0.4552945,"about_ca_topic_score_gemma":0.70593566,"teacher_disagreement_score":0.4552945,"about_ca_system_score_codex":0.012972352,"about_ca_system_score_gemma":0.014169215,"threshold_uncertainty_score":0.90528876},"labels":[],"label_agreement":null},{"id":"W257746328","doi":"","title":"Subset selection of search heuristics","year":2013,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Heuristics; Submodular set function; Mathematical optimization; Heuristic; Selection (genetic algorithm); Computer science; Greedy algorithm; Function (biology); Limit (mathematics); Monotonic function; Mathematics; Artificial intelligence","score_opus":0.02241517170922976,"score_gpt":0.25929622060505547,"score_spread":0.2368810488958257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W257746328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06730681,0.0010944869,0.92193496,0.00040587498,0.000060631257,0.00041093235,0.00024566994,0.00079402677,0.0077467333],"genre_scores_gemma":[0.5533122,0.0005500407,0.4418236,0.00032614157,0.00007106335,0.00058044563,0.00061269576,0.00021758118,0.0025062377],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99600273,0.0024891717,0.00015805323,0.00045955446,0.00065833156,0.00023213516],"domain_scores_gemma":[0.9913639,0.0060902587,0.00040005488,0.0013718349,0.0005551911,0.00021871479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046097143,0.0011478716,0.0015592248,0.0013108904,0.0006596055,0.0017706908,0.0014346828,0.0010484133,0.0039026185],"category_scores_gemma":[0.015405287,0.0006474476,0.0011242062,0.0016492223,0.001272178,0.0029893324,0.002000519,0.0015865186,0.0009563167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005934008,0.00031758004,0.0057429913,0.0005262622,0.00023265005,0.00019200321,0.00047503397,0.42885998,0.0060271355,0.1171398,0.01068019,0.429213],"study_design_scores_gemma":[0.00006837754,0.00025421477,0.00064178207,0.00007371752,0.000064589745,0.00012108175,0.00014178494,0.91635853,0.0032537305,0.07486508,0.004136333,0.000020755857],"about_ca_topic_score_codex":0.00097663,"about_ca_topic_score_gemma":0.0017336219,"teacher_disagreement_score":0.0046097143,"about_ca_system_score_codex":0.0014346254,"about_ca_system_score_gemma":0.001708758,"threshold_uncertainty_score":0.024378836},"labels":[],"label_agreement":null},{"id":"W2578195970","doi":"10.1609/socs.v7i1.18399","title":"Extended Abstract: An Improved Priority Function for Bidirectional Heuristic Search","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Bidirectional search; Correctness; Heuristic; Node (physics); Incremental heuristic search; Computer science; Search algorithm; State (computer science); Function (biology); Sketch; Best-first search; Algorithm; Evaluation function; Beam search; Search problem; Mathematical optimization; Mathematics; Artificial intelligence; Engineering","score_opus":0.022153089281185496,"score_gpt":0.28496387440972265,"score_spread":0.26281078512853717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2578195970","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012075504,0.0005490721,0.9713093,0.0006353659,0.00031869754,0.00019534165,0.00036085755,0.0021386018,0.012417209],"genre_scores_gemma":[0.28629798,0.00040960524,0.7003579,0.0005879131,0.0003258145,0.00040032607,0.00069598464,0.000896794,0.010027676],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99725,0.0008004065,0.00022390517,0.000461066,0.00087699044,0.00038768782],"domain_scores_gemma":[0.9926569,0.002841168,0.00049645524,0.0020155238,0.0015321092,0.00045789627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038587842,0.0011986415,0.0011135436,0.0014568709,0.0010121535,0.0027512112,0.0034347174,0.0017532143,0.01513141],"category_scores_gemma":[0.018660776,0.00054527016,0.0012509516,0.0018210029,0.0011050422,0.004889645,0.0036560025,0.0029388682,0.004096679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00083716476,0.00035422153,0.0021672784,0.0006704299,0.000072997645,0.00018309614,0.0003217841,0.12021156,0.012116268,0.28338638,0.026881551,0.5527974],"study_design_scores_gemma":[0.00014513877,0.00030200212,0.0006787959,0.000094025614,0.000049840044,0.00026154146,0.00008016073,0.75475746,0.0071461755,0.2098183,0.026599035,0.0000674494],"about_ca_topic_score_codex":0.0024525812,"about_ca_topic_score_gemma":0.0026303364,"teacher_disagreement_score":0.01513141,"about_ca_system_score_codex":0.0016907605,"about_ca_system_score_gemma":0.0026531466,"threshold_uncertainty_score":0.050619602},"labels":[],"label_agreement":null},{"id":"W2583569053","doi":"10.20429/tag.2017.040102","title":"An Eternal Domination Problem in Grids","year":2017,"lang":"en","type":"article","venue":"Theory and Applications of Graphs","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Division of Mathematical Sciences; Natural Sciences and Engineering Research Council of Canada; Mount Allison University","keywords":"Combinatorics; Vertex (graph theory); Guard (computer science); Graph; Eviction; Mathematics; Sequence (biology); Discrete mathematics; Upper and lower bounds; Computer science; Political science; Law","score_opus":0.010245610522857105,"score_gpt":0.29468773347360777,"score_spread":0.28444212295075066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2583569053","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.49056146,0.0009771235,0.4835359,0.0018946783,0.00013601712,0.00018712791,0.00084953924,0.0003659408,0.02149215],"genre_scores_gemma":[0.93196356,0.00040716233,0.055885248,0.00019516329,0.00007237422,0.00011071751,0.00044465132,0.00006949277,0.010851591],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991855,0.00025492886,0.00004550368,0.0002034737,0.00011109001,0.00019949363],"domain_scores_gemma":[0.9971641,0.0017784898,0.0003118612,0.00029377424,0.00016888561,0.00028279462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095683476,0.00058455823,0.0007021222,0.00046000764,0.001014875,0.0012912226,0.0012841278,0.00077147037,0.0031868627],"category_scores_gemma":[0.0035787926,0.00028422757,0.00050969137,0.00082514435,0.0012189205,0.0024784787,0.0013068962,0.00086152356,0.00021934268],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00097218016,0.00022882792,0.0046134586,0.00032031396,0.00014187931,0.00074722484,0.00068910525,0.5912291,0.009802051,0.31650615,0.0093731,0.065376654],"study_design_scores_gemma":[0.0001317828,0.00012557175,0.001106587,0.000025066613,0.000029401634,0.0003897196,0.00027209782,0.72277725,0.002626118,0.26351556,0.00897497,0.000025822732],"about_ca_topic_score_codex":0.003861584,"about_ca_topic_score_gemma":0.0030890852,"teacher_disagreement_score":0.003861584,"about_ca_system_score_codex":0.0010989164,"about_ca_system_score_gemma":0.00060366595,"threshold_uncertainty_score":0.010661066},"labels":[],"label_agreement":null},{"id":"W2584897526","doi":"10.1007/978-3-319-57586-5_3","title":"Scheduling Maintenance Jobs in Networks","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Preemption; Computer science; Scheduling (production processes); Time complexity; Job shop scheduling; Mathematical optimization; Simple (philosophy); Approximation algorithm; Distributed computing; Algorithm; Mathematics; Computer network","score_opus":0.02342604167475172,"score_gpt":0.26489842661823215,"score_spread":0.24147238494348044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2584897526","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08891173,0.0145156095,0.7910744,0.0016619734,0.0022613478,0.00024073732,0.00041118643,0.0019809334,0.098942146],"genre_scores_gemma":[0.6944141,0.0098696835,0.19041105,0.00032369638,0.0013107242,0.00019210757,0.00086494716,0.00074253004,0.10187113],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99983966,0.000025325724,0.0000072469993,0.000036842208,0.00005463761,0.00003633092],"domain_scores_gemma":[0.9997814,0.00009620489,0.000022911063,0.000043493277,0.000029460502,0.00002656544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002847687,0.0007700275,0.0005238755,0.00041222377,0.00041232203,0.00082686765,0.0011301651,0.00053413253,0.0065701166],"category_scores_gemma":[0.0009210737,0.0003399996,0.00030373808,0.0009272325,0.00037500646,0.0008732827,0.0005307523,0.00082806457,0.0014866274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006635882,0.00016228246,0.00043683875,0.0008952077,0.000065021435,0.00018851287,0.00015857928,0.3255398,0.020853339,0.07045404,0.042049386,0.53853345],"study_design_scores_gemma":[0.0000774506,0.00038839102,0.001343867,0.00015309239,0.000055585202,0.00037187172,0.00011494238,0.72936386,0.011077973,0.17035043,0.08666561,0.000036856825],"about_ca_topic_score_codex":0.00096751994,"about_ca_topic_score_gemma":0.0011566839,"teacher_disagreement_score":0.0065701166,"about_ca_system_score_codex":0.00063166657,"about_ca_system_score_gemma":0.0005344913,"threshold_uncertainty_score":0.021979272},"labels":[],"label_agreement":null},{"id":"W2594754650","doi":"","title":"OrthoMADS: A Deterministic MADS Instance with Orthogonal Directions","year":2008,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Polling; Convergence (economics); Mathematics; Mathematical optimization; Computer science; Regular polygon; Class (philosophy); Measure (data warehouse); Algorithm; Artificial intelligence; Data mining","score_opus":0.014696171396016509,"score_gpt":0.22925701613149196,"score_spread":0.21456084473547546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594754650","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0764898,0.0006427599,0.9013729,0.0010601656,0.00023365584,0.00016683653,0.0014517913,0.00131988,0.0172623],"genre_scores_gemma":[0.3917846,0.00024333976,0.59797394,0.0002727421,0.0001023831,0.00033732512,0.0013238969,0.00030909324,0.0076526674],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994574,0.00014397483,0.000037501242,0.00012178848,0.00015836915,0.00008091814],"domain_scores_gemma":[0.9993994,0.00028358347,0.00005846291,0.00012989774,0.000053878797,0.00007472401],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007757546,0.0005828492,0.0010344525,0.00040813553,0.00038805982,0.0014967616,0.0016115153,0.0012667539,0.005346691],"category_scores_gemma":[0.0024068535,0.0004168786,0.00094649027,0.0006304531,0.00061203144,0.0011401491,0.0015749338,0.0015783063,0.00044577962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036982208,0.00010427193,0.0013061455,0.00015479622,0.000062710074,0.00017471274,0.0000677971,0.8280764,0.0018341171,0.08523951,0.009911707,0.07269802],"study_design_scores_gemma":[0.00006194124,0.00004332162,0.00012648718,0.000010502305,0.000006031041,0.000049195412,0.000013879631,0.97159785,0.0006608212,0.023314591,0.0041050245,0.000010393381],"about_ca_topic_score_codex":0.0026470541,"about_ca_topic_score_gemma":0.0051972764,"teacher_disagreement_score":0.005346691,"about_ca_system_score_codex":0.00081083644,"about_ca_system_score_gemma":0.00093756913,"threshold_uncertainty_score":0.01788646},"labels":[],"label_agreement":null},{"id":"W2598880527","doi":"10.1007/978-3-319-55911-7_48","title":"Fast Searching on Cartesian Products of Graphs","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Cartesian product; Upper and lower bounds; Eulerian path; Hypercube; Computer science; Cartesian coordinate system; Graph; Lattice graph; Product (mathematics); Combinatorics; Path (computing); Search tree; Discrete mathematics; Search algorithm; Theoretical computer science; Mathematics; Algorithm; Parallel computing; Line graph; Voltage graph; Applied mathematics; Geometry","score_opus":0.027269901835308544,"score_gpt":0.27199713060153935,"score_spread":0.24472722876623082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2598880527","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11450531,0.0025082116,0.8336662,0.0005007022,0.0002139461,0.00017595419,0.000805112,0.0030155184,0.044609085],"genre_scores_gemma":[0.20996045,0.0013906276,0.76773417,0.00013300571,0.00006945437,0.00013924608,0.0013924869,0.0008583184,0.018322278],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99935836,0.00018963327,0.00003366521,0.00014282037,0.000204019,0.00007139598],"domain_scores_gemma":[0.9978834,0.0013172806,0.000095117844,0.0003860257,0.00023259767,0.000085586675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007182717,0.0009905782,0.0013326342,0.0013229116,0.000668087,0.001343845,0.001558596,0.00073722063,0.013177033],"category_scores_gemma":[0.004298588,0.000827,0.0010260904,0.0024742808,0.001112458,0.0036389453,0.0021556804,0.0013780253,0.0028628674],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000518335,0.00012237379,0.001184784,0.0013955169,0.0001151923,0.0002018032,0.0006069983,0.09404514,0.010098588,0.37269807,0.035578366,0.4834348],"study_design_scores_gemma":[0.00009477584,0.00020857259,0.00053239445,0.00015856503,0.000062447834,0.00042057832,0.00019067769,0.2992914,0.0048238006,0.66727805,0.026903609,0.000035153284],"about_ca_topic_score_codex":0.00188744,"about_ca_topic_score_gemma":0.0027355952,"teacher_disagreement_score":0.013177033,"about_ca_system_score_codex":0.0007287251,"about_ca_system_score_gemma":0.0006167858,"threshold_uncertainty_score":0.04408157},"labels":[],"label_agreement":null},{"id":"W2603214747","doi":"10.1142/s012905411750006x","title":"Deterministic Rendezvous with Detection Using Beeps","year":2017,"lang":"en","type":"article","venue":"International Journal of Foundations of Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Rendezvous; Computer science; Node (physics); Mobile agent; Computer network; Real-time computing; Distributed computing","score_opus":0.04234109411602974,"score_gpt":0.35111037560664526,"score_spread":0.30876928149061555,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2603214747","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017291535,0.00026113522,0.97406274,0.00023010864,0.00007264878,0.000086121465,0.00011932643,0.0007205067,0.0071558454],"genre_scores_gemma":[0.82047737,0.00043218568,0.16510193,0.00027619803,0.00007257083,0.0004290337,0.00026958762,0.00022656802,0.012714601],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976184,0.0005366655,0.0001306613,0.0005863431,0.00067317626,0.00045477177],"domain_scores_gemma":[0.9950352,0.0026870251,0.00054198236,0.0010755954,0.00040837808,0.00025181525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012108133,0.0012153601,0.0013020203,0.00071065925,0.0012159559,0.0019470813,0.0029539904,0.001848286,0.004271036],"category_scores_gemma":[0.0066012377,0.0007484751,0.001144807,0.0008231225,0.0020349196,0.0030082087,0.0039651524,0.0019794125,0.0009114675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041996743,0.00008182196,0.0012519428,0.00025348313,0.0000823064,0.0005404186,0.00047129084,0.62306565,0.011004806,0.32263923,0.0037107535,0.036478393],"study_design_scores_gemma":[0.000043660853,0.000059632028,0.0001092155,0.000015078717,0.000018647277,0.00012350896,0.00004195021,0.92790395,0.0027878108,0.06455946,0.004301586,0.000035483466],"about_ca_topic_score_codex":0.0048512784,"about_ca_topic_score_gemma":0.004416908,"teacher_disagreement_score":0.0048512784,"about_ca_system_score_codex":0.0014894372,"about_ca_system_score_gemma":0.0012931746,"threshold_uncertainty_score":0.014288008},"labels":[],"label_agreement":null},{"id":"W2604377131","doi":"10.1016/j.dam.2017.03.003","title":"The fast search number of a Cartesian product of graphs","year":2017,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cartesian product; Mathematics; Product (mathematics); Combinatorics; Discrete mathematics; Geometry","score_opus":0.024039843949368953,"score_gpt":0.30076120095634834,"score_spread":0.27672135700697936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2604377131","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36242366,0.0015433186,0.6097702,0.0015172416,0.00022772703,0.0001391421,0.0008465734,0.0009672967,0.022564927],"genre_scores_gemma":[0.6184156,0.0006710362,0.37026197,0.00021962317,0.00009663331,0.00016257023,0.00073529413,0.0003892882,0.00904808],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99874073,0.00047263943,0.000059795842,0.0003039816,0.00030686485,0.00011608907],"domain_scores_gemma":[0.9884272,0.008461231,0.00056927965,0.0012743594,0.00083194417,0.00043592276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017798541,0.00068930304,0.0010489203,0.0012603542,0.0007452179,0.0019466013,0.0015098613,0.0010759364,0.0065771104],"category_scores_gemma":[0.015621767,0.00074357283,0.0007672244,0.0013638339,0.0016926498,0.0051659956,0.0016616439,0.0016205482,0.001033057],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001421182,0.00016350615,0.004921721,0.0008545494,0.00013159895,0.0003006782,0.0006359587,0.19952214,0.016236002,0.5895054,0.019788478,0.16651884],"study_design_scores_gemma":[0.00007947671,0.00024413453,0.0011752995,0.000072555784,0.00006080745,0.0003810753,0.00012220883,0.5205624,0.0055319844,0.46594095,0.005795414,0.00003365557],"about_ca_topic_score_codex":0.0016362766,"about_ca_topic_score_gemma":0.001903543,"teacher_disagreement_score":0.0065771104,"about_ca_system_score_codex":0.00095246756,"about_ca_system_score_gemma":0.0013826025,"threshold_uncertainty_score":0.022002578},"labels":[],"label_agreement":null},{"id":"W2606510480","doi":"10.1007/978-3-319-57351-9_15","title":"Time Prediction of the Next Refueling Event: A Case Study","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Computer science; Event (particle physics); Set (abstract data type); Artificial intelligence; Data mining; Machine learning; Ensemble learning; Ensemble forecasting; Data set","score_opus":0.042457695149409294,"score_gpt":0.28441510745532844,"score_spread":0.24195741230591916,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606510480","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9007083,0.00069460424,0.074188694,0.0012338384,0.00016069727,0.00017863026,0.0018008511,0.000878878,0.020155497],"genre_scores_gemma":[0.982781,0.00018472255,0.012822928,0.000044756132,0.000022049426,0.000024282419,0.0005648748,0.000059391794,0.00349596],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957997,0.000114064496,0.00002263988,0.000095899,0.00012354739,0.000063810105],"domain_scores_gemma":[0.995239,0.0034585092,0.0002701642,0.0003062822,0.00046029492,0.00026570878],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011036799,0.0004761583,0.00035881152,0.0008380916,0.000652787,0.0008580997,0.0013724674,0.0015538943,0.005224669],"category_scores_gemma":[0.006015302,0.00020073718,0.00037564893,0.001114829,0.00040442386,0.00085407577,0.00046076003,0.0007947535,0.0008682362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028274707,0.0022079835,0.1367727,0.0006600555,0.00016852222,0.02954044,0.0021112924,0.5275942,0.011831313,0.01991847,0.020439904,0.24592753],"study_design_scores_gemma":[0.0001362647,0.00076413405,0.020277515,0.00008202243,0.00011867865,0.003529225,0.0023991475,0.9318875,0.012129324,0.012807733,0.015778726,0.00008972459],"about_ca_topic_score_codex":0.011711153,"about_ca_topic_score_gemma":0.011044997,"teacher_disagreement_score":0.011711153,"about_ca_system_score_codex":0.00058384414,"about_ca_system_score_gemma":0.00069424027,"threshold_uncertainty_score":0.023285985},"labels":[],"label_agreement":null},{"id":"W2608449519","doi":"10.1016/j.jcss.2017.04.001","title":"The impact of processing order on performance: A taxonomy of semi-FIFO policies","year":2017,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"National Research University Higher School of Economics","keywords":"FIFO (computing and electronics); Computer science; Order (exchange); Taxonomy (biology); Operations research; Mathematics; Business; Programming language; Biology; Finance","score_opus":0.05195371665569185,"score_gpt":0.32342264984391245,"score_spread":0.2714689331882206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608449519","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51539826,0.011047317,0.4189272,0.0035073021,0.00039175243,0.0004353278,0.0007623912,0.0017092989,0.0478212],"genre_scores_gemma":[0.95551103,0.0036847466,0.03811226,0.00018736885,0.00027397118,0.000110492074,0.00015571839,0.00015597937,0.0018084953],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99465287,0.0011077898,0.00052077067,0.0003927291,0.002258665,0.0010671782],"domain_scores_gemma":[0.9124268,0.067238085,0.007493688,0.005848152,0.0049583702,0.00203488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007400285,0.00088193465,0.0011183412,0.003106525,0.0009861281,0.004855025,0.0017565206,0.0012973654,0.002599773],"category_scores_gemma":[0.04607871,0.0005990395,0.00071195874,0.0037085544,0.0014309284,0.005840515,0.0012903449,0.0016262401,0.000346231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017754507,0.0010603298,0.03773467,0.0010071542,0.00028729593,0.00037355957,0.00058283476,0.3312881,0.011494266,0.23420614,0.004671484,0.37551865],"study_design_scores_gemma":[0.00009494481,0.0011800358,0.011432102,0.00024110901,0.00030094423,0.00066558743,0.00039115033,0.7406103,0.010501177,0.2275885,0.006881171,0.00011294141],"about_ca_topic_score_codex":0.0016159528,"about_ca_topic_score_gemma":0.001273058,"teacher_disagreement_score":0.007400285,"about_ca_system_score_codex":0.0020909111,"about_ca_system_score_gemma":0.0028617855,"threshold_uncertainty_score":0.039136946},"labels":[],"label_agreement":null},{"id":"W2610562287","doi":"","title":"The number of increasing nonconsecutive subpaths in a path","year":2006,"lang":"en","type":"article","venue":"HKBU Institutional Repository (Hong Kong Baptist University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Path (computing); Computer science","score_opus":0.005753194385482556,"score_gpt":0.1968608752115206,"score_spread":0.19110768082603805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610562287","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8711562,0.0006703312,0.088226706,0.0016809901,0.00013695448,0.00050348515,0.0034035102,0.00046839638,0.033753425],"genre_scores_gemma":[0.7672688,0.0012934195,0.19129872,0.00029984856,0.00012044968,0.0006478267,0.0047090077,0.00029450023,0.034067366],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979553,0.00035735453,0.00014980738,0.00052996574,0.00051425886,0.0004932763],"domain_scores_gemma":[0.97324276,0.01865355,0.001961037,0.00141989,0.002356336,0.0023663985],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016309579,0.0011208347,0.0011910031,0.0036095644,0.0030850866,0.0038938313,0.0026733656,0.0020859602,0.015627943],"category_scores_gemma":[0.014720264,0.00092413236,0.0012075285,0.0040851315,0.0020705517,0.005585579,0.0021096177,0.003209653,0.0012544045],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0037509496,0.0014147345,0.048985578,0.002583456,0.0004466058,0.002749423,0.0027938588,0.098746255,0.04709412,0.5298457,0.020746615,0.24084279],"study_design_scores_gemma":[0.00030288406,0.0014221974,0.028386394,0.00041969735,0.0005755686,0.0046407315,0.002675642,0.3211835,0.022409683,0.58246243,0.035379536,0.00014178998],"about_ca_topic_score_codex":0.0020076241,"about_ca_topic_score_gemma":0.0030056643,"teacher_disagreement_score":0.015627943,"about_ca_system_score_codex":0.0020742074,"about_ca_system_score_gemma":0.0021193821,"threshold_uncertainty_score":0.052280724},"labels":[],"label_agreement":null},{"id":"W2611167225","doi":"10.1002/net.21810","title":"Deterministic gathering with crash faults","year":2018,"lang":"en","type":"preprint","venue":"Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Traverse; Computer science; Node (physics); Crash; Asynchrony (computer programming); Fault (geology); Enhanced Data Rates for GSM Evolution; Real-time computing; Distributed computing; Computer network; Computer security; Artificial intelligence; Engineering; Asynchronous communication","score_opus":0.018497622520054307,"score_gpt":0.2539627596083782,"score_spread":0.23546513708832392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2611167225","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26799327,0.0011828009,0.71725327,0.00173164,0.0001315321,0.00016453808,0.0006155759,0.00037729382,0.010550119],"genre_scores_gemma":[0.94775397,0.00050584064,0.04368841,0.00016673587,0.000077759316,0.00023096126,0.0004732284,0.00008265068,0.007020485],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99882835,0.00044750498,0.000058514375,0.00028552258,0.00012839599,0.00025181522],"domain_scores_gemma":[0.9936871,0.00407673,0.0010085044,0.00043910474,0.0004030251,0.0003855394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015081313,0.0009189607,0.0010603939,0.0005248029,0.0008614874,0.0011037403,0.0013267739,0.0018234624,0.0029155891],"category_scores_gemma":[0.00956158,0.0006272759,0.0007953001,0.0006142298,0.0012565677,0.0018425462,0.0016418166,0.0011127976,0.000340038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021013372,0.00004084392,0.0012597862,0.00013627225,0.00004975174,0.00020113631,0.00011904335,0.9532893,0.00079541584,0.033391356,0.0017458694,0.008761088],"study_design_scores_gemma":[0.00004504276,0.00006232706,0.0003714926,0.000013861986,0.000017653725,0.00005455869,0.00007497937,0.96190083,0.00048076623,0.035949886,0.001017273,0.000011341868],"about_ca_topic_score_codex":0.0042795087,"about_ca_topic_score_gemma":0.0023796798,"teacher_disagreement_score":0.0042795087,"about_ca_system_score_codex":0.0014350361,"about_ca_system_score_gemma":0.00072890293,"threshold_uncertainty_score":0.010411978},"labels":[],"label_agreement":null},{"id":"W2612999812","doi":"10.48550/arxiv.1705.03538","title":"Shape Formation by Programmable Particles","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science; Grid; Hexagonal tiling; Node (physics); Rotation (mathematics); Chirality (physics); Tessellation (computer graphics); Topology (electrical circuits); Algorithm; Geometry; Mathematics; Combinatorics; Physics; Artificial intelligence; Symmetry breaking; Spontaneous symmetry breaking","score_opus":0.11172414915517952,"score_gpt":0.2086057545161518,"score_spread":0.09688160536097228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2612999812","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09842236,0.00015949323,0.8908703,0.0004342723,0.00008772475,0.00019303466,0.00009723811,0.00054815266,0.009187405],"genre_scores_gemma":[0.7630503,0.00030447697,0.22196099,0.00025970006,0.000057608926,0.00033017818,0.0003620244,0.00021400843,0.013460765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926263,0.00013511899,0.00004007219,0.0002394451,0.00020890312,0.00011377834],"domain_scores_gemma":[0.9981687,0.00080867263,0.00020182738,0.0005066585,0.00014209528,0.00017201304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007208195,0.00044572694,0.0006290822,0.00035776276,0.0009621529,0.001340955,0.0016493386,0.0011750304,0.0042130346],"category_scores_gemma":[0.0040645325,0.00044658603,0.0010469446,0.00038753173,0.0024328204,0.0019038942,0.002986118,0.0012723191,0.0007633268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031186422,0.00006620731,0.0018189023,0.00014509272,0.00005234528,0.0003301632,0.00038968827,0.6280824,0.0179449,0.28231332,0.0022992543,0.066245936],"study_design_scores_gemma":[0.000057894205,0.00009446271,0.0002762966,0.000018797522,0.000014525087,0.00012269992,0.00008541159,0.8629398,0.008772904,0.1223052,0.0052872477,0.000024841402],"about_ca_topic_score_codex":0.0014712471,"about_ca_topic_score_gemma":0.0011253018,"teacher_disagreement_score":0.0042130346,"about_ca_system_score_codex":0.00086408196,"about_ca_system_score_gemma":0.0008512354,"threshold_uncertainty_score":0.014093995},"labels":[],"label_agreement":null},{"id":"W2613774992","doi":"10.1007/s10107-020-01576-0","title":"General bounds for incremental maximization","year":2020,"lang":"en","type":"preprint","venue":"Mathematical Programming","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Technische Universität Darmstadt; Deutsche Forschungsgemeinschaft","keywords":"Cardinality (data modeling); Knapsack problem; Competitive analysis; Submodular set function; Maximization; Mathematics; Mathematical optimization; Greedy algorithm; Bounded function; Matching (statistics); Class (philosophy); Combinatorics; Function (biology); Upper and lower bounds; Computer science","score_opus":0.06959338221277929,"score_gpt":0.3216730882626167,"score_spread":0.2520797060498374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2613774992","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015473946,0.0030105456,0.89990187,0.002609768,0.00021324909,0.00027604934,0.0005412789,0.0010398686,0.07693349],"genre_scores_gemma":[0.47204235,0.003638488,0.4994244,0.0021079243,0.00091209123,0.0012338993,0.0013487278,0.0012108826,0.018081125],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9931537,0.0020141206,0.00023228185,0.0011753282,0.0021532185,0.0012713346],"domain_scores_gemma":[0.9818818,0.012935832,0.0008790679,0.0021292118,0.001528832,0.000645376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0071098907,0.0025617906,0.0018652634,0.002870106,0.0020575027,0.005261029,0.006205357,0.0029973085,0.016437842],"category_scores_gemma":[0.030320002,0.0010020178,0.0026921378,0.0043528285,0.003278706,0.009907246,0.005199789,0.0071570766,0.0026808812],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021489858,0.000119052806,0.0006009234,0.0003891366,0.0000676033,0.0000989714,0.00019986977,0.11764123,0.001710251,0.8240385,0.01342476,0.041494746],"study_design_scores_gemma":[0.000044057277,0.00008457347,0.00038518303,0.000088757166,0.00006857184,0.00016789058,0.00005476813,0.4895849,0.0014402494,0.4918856,0.016163375,0.00003217292],"about_ca_topic_score_codex":0.004367349,"about_ca_topic_score_gemma":0.0041450406,"teacher_disagreement_score":0.016437842,"about_ca_system_score_codex":0.006711905,"about_ca_system_score_gemma":0.0031151252,"threshold_uncertainty_score":0.054989994},"labels":[],"label_agreement":null},{"id":"W2615288237","doi":"10.5539/jmr.v9n3p23","title":"An Addendum on Postoptimality of Maximally Reliable Path","year":2017,"lang":"en","type":"article","venue":"Journal of Mathematics Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Infimum and supremum; Multiplicative function; Addendum; Path (computing); Robustness (evolution); Arc (geometry); Mathematical optimization; Combinatorics; Mathematical analysis; Geometry; Computer science","score_opus":0.1787361470804617,"score_gpt":0.44478508777291587,"score_spread":0.26604894069245416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2615288237","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013585854,0.0075549055,0.9118312,0.008079743,0.0066444725,0.00010641634,0.00045073454,0.0005720196,0.051174704],"genre_scores_gemma":[0.4240734,0.018118868,0.4636197,0.006265396,0.03394977,0.0006667269,0.0010496932,0.0015752014,0.050681245],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977361,0.0005893566,0.00010630328,0.00063842826,0.0007656585,0.00016416096],"domain_scores_gemma":[0.98053646,0.013613015,0.0008720056,0.002838211,0.0015749172,0.0005653113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027905882,0.0021901096,0.0012307861,0.0018003586,0.0013010342,0.0020134978,0.0027141569,0.002113161,0.019615836],"category_scores_gemma":[0.020538894,0.0005820262,0.002028557,0.0016726492,0.0028983185,0.0047457963,0.003978667,0.006772923,0.003488014],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005863215,0.00025004195,0.0014148437,0.0016869812,0.00030240105,0.0015381422,0.00042681114,0.10687168,0.015110515,0.6234529,0.05866924,0.18969014],"study_design_scores_gemma":[0.00004729579,0.0008316652,0.0012347221,0.0003536932,0.00024162674,0.0014844802,0.00011010347,0.26009053,0.010674231,0.6240605,0.100705676,0.0001655406],"about_ca_topic_score_codex":0.00077064085,"about_ca_topic_score_gemma":0.0007407922,"teacher_disagreement_score":0.019615836,"about_ca_system_score_codex":0.0012203952,"about_ca_system_score_gemma":0.0010342938,"threshold_uncertainty_score":0.065621495},"labels":[],"label_agreement":null},{"id":"W2620280838","doi":"10.1016/j.jpdc.2017.04.003","title":"Decidability classes for mobile agents computing","year":2017,"lang":"en","type":"article","venue":"Journal of Parallel and Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université Paris Diderot; Agence Nationale de la Recherche; Université du Québec en Outaouais","keywords":"Decidability; Class (philosophy); Decision problem; Certificate; Computer science; Verifiable secret sharing; Protocol (science); Focus (optics); Reduction (mathematics); Theoretical computer science; Artificial intelligence; Mathematics; Algorithm; Programming language","score_opus":0.04602957870674327,"score_gpt":0.3446050114997421,"score_spread":0.2985754327929988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620280838","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12536298,0.0020395725,0.7859628,0.015828565,0.00051207136,0.0004402454,0.0022153668,0.0019638157,0.06567457],"genre_scores_gemma":[0.8288357,0.001068181,0.14267927,0.0021267417,0.0008393573,0.0008402624,0.0031009004,0.000678175,0.019831322],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9953998,0.0011505309,0.00036758013,0.0012007103,0.0010407228,0.00084064296],"domain_scores_gemma":[0.9676403,0.02834628,0.0008093109,0.0016409808,0.0007743321,0.0007887927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044200355,0.0011006865,0.0014276509,0.0017427397,0.0036178832,0.0073470883,0.0038528736,0.003315067,0.010207946],"category_scores_gemma":[0.02197492,0.0013146513,0.0041061956,0.0016546667,0.004557569,0.014791758,0.004826933,0.009271705,0.00078592275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001203731,0.00014321541,0.000914952,0.00023797466,0.00006994834,0.0001830328,0.00088067725,0.012065284,0.00072437944,0.96318614,0.006152828,0.015321196],"study_design_scores_gemma":[0.00005281669,0.0000099135195,0.00013434568,0.000026410124,0.00003327091,0.000054835153,0.00012521105,0.03846601,0.00054955017,0.95750856,0.0030253031,0.000013829015],"about_ca_topic_score_codex":0.005257046,"about_ca_topic_score_gemma":0.0055090883,"teacher_disagreement_score":0.010207946,"about_ca_system_score_codex":0.0042153075,"about_ca_system_score_gemma":0.0031017426,"threshold_uncertainty_score":0.03414899},"labels":[],"label_agreement":null},{"id":"W2621324178","doi":"10.5555/1283383.1283446","title":"Tree exploration with logarithmic memory","year":2007,"lang":"en","type":"article","venue":"Symposium on Discrete Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":46,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Traverse; Computer science; Node (physics); Tree (set theory); Network topology; Logarithm; Binary logarithm; Graph; Upper and lower bounds; Enhanced Data Rates for GSM Evolution; Theoretical computer science; Task (project management); Topology (electrical circuits); Mathematics; Combinatorics; Computer network; Artificial intelligence","score_opus":0.018104980120028976,"score_gpt":0.2619032041318963,"score_spread":0.24379822401186735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621324178","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19382031,0.0022844342,0.77684444,0.0013492438,0.00012763405,0.00012243466,0.00061266567,0.0023670506,0.022471737],"genre_scores_gemma":[0.7500607,0.0009946837,0.23709704,0.00027584648,0.00006100246,0.00030023887,0.00059500843,0.0002924401,0.010323139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99961334,0.0000886066,0.000021384189,0.00008327147,0.00007233626,0.00012119833],"domain_scores_gemma":[0.9983608,0.001064085,0.00012215825,0.00026025332,0.00009726459,0.000095461764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039889372,0.00057838217,0.00075826887,0.0004298304,0.00061700563,0.0010916444,0.0014132399,0.0009965398,0.0071659703],"category_scores_gemma":[0.003846026,0.00027419702,0.00052976015,0.0009908231,0.00072085485,0.0038317791,0.0017218932,0.0007996842,0.0011393565],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016327762,0.00018526525,0.0015714616,0.00054492225,0.000083697894,0.00040771806,0.0003759915,0.77228737,0.009961211,0.07838773,0.009081185,0.12548058],"study_design_scores_gemma":[0.00009792434,0.000114507,0.00016592092,0.000019530034,0.000022551034,0.00010631372,0.00005434522,0.9084169,0.0028034642,0.08522197,0.002964132,0.000012443772],"about_ca_topic_score_codex":0.0018794762,"about_ca_topic_score_gemma":0.0019330427,"teacher_disagreement_score":0.0071659703,"about_ca_system_score_codex":0.00065799506,"about_ca_system_score_gemma":0.0006754559,"threshold_uncertainty_score":0.02397257},"labels":[],"label_agreement":null},{"id":"W2621800709","doi":"","title":"How to meet asynchronously (almost) everywhere","year":2012,"lang":"en","type":"article","venue":"HAL AMU","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":126,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Asynchronous communication; Computer science; Terrain; Graph; Simply connected space; Point (geometry); Path (computing); Strongly connected component; Robot; Plane (geometry); Theoretical computer science; Mathematics; Algorithm; Combinatorics; Artificial intelligence; Geometry; Computer network","score_opus":0.02134146295016659,"score_gpt":0.24616554408899366,"score_spread":0.22482408113882707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2621800709","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.082072355,0.0001256164,0.9061904,0.00087169616,0.00006340318,0.00015869181,0.00024068888,0.0020847286,0.00819248],"genre_scores_gemma":[0.6017067,0.00016015314,0.38865504,0.00017164499,0.00002748573,0.00023046904,0.00067075365,0.0003368019,0.0080409385],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982249,0.00037913985,0.00014556073,0.00058642577,0.00038677885,0.00027723043],"domain_scores_gemma":[0.995116,0.0020530755,0.0004175211,0.0016528318,0.00048951805,0.00027098253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012397275,0.0008345871,0.00085235754,0.00035452828,0.0015497303,0.001915466,0.0022347537,0.0014488016,0.004196511],"category_scores_gemma":[0.008173278,0.0006468386,0.00085474213,0.0004970557,0.0016185312,0.0036623687,0.0024326073,0.0012405165,0.0017695416],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012702699,0.00018197892,0.005639047,0.00047957976,0.00017911146,0.00046778776,0.0018903478,0.46056068,0.02413516,0.29966283,0.011606219,0.19392706],"study_design_scores_gemma":[0.00017994404,0.00017966214,0.0006328584,0.000044497578,0.00007171488,0.00036512502,0.0006348133,0.7708567,0.022168182,0.18563905,0.019154528,0.00007296277],"about_ca_topic_score_codex":0.004558671,"about_ca_topic_score_gemma":0.004727483,"teacher_disagreement_score":0.004558671,"about_ca_system_score_codex":0.00092518074,"about_ca_system_score_gemma":0.0016299302,"threshold_uncertainty_score":0.014038801},"labels":[],"label_agreement":null},{"id":"W2622743094","doi":"10.1145/2629671","title":"Distributed Selfish Load Balancing on Networks","year":2014,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Division of Computer and Network Systems; Deutsche Forschungsgemeinschaft; National Science Foundation","keywords":"Nash equilibrium; Convergence (economics); Computer science; Logarithm; Vertex (graph theory); Potential game; Load balancing (electrical power); Mathematical optimization; Computation; Graph; Best response; Distributed algorithm; Polynomial; Coordination game; Mathematics; Distributed computing; Theoretical computer science; Mathematical economics; Algorithm","score_opus":0.013687302818713581,"score_gpt":0.24350609256702183,"score_spread":0.22981878974830824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2622743094","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17244053,0.0006238917,0.8168623,0.00066951016,0.00009388693,0.00008868248,0.00004059994,0.00025941484,0.008921185],"genre_scores_gemma":[0.9646684,0.00038766058,0.03059993,0.00007266956,0.000069936366,0.00007704454,0.000029754547,0.000034845296,0.004059732],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992411,0.00028415897,0.000027550945,0.00015023803,0.00016739851,0.00012962821],"domain_scores_gemma":[0.9977715,0.0013160405,0.0003735829,0.00024188071,0.00018719117,0.00010975129],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010849604,0.0005911044,0.0006540558,0.00045659,0.00072274543,0.0012905292,0.0012561375,0.0009117645,0.0015239938],"category_scores_gemma":[0.0046912665,0.00028880103,0.00033780726,0.00070349197,0.0014789687,0.002632047,0.0012509873,0.0007165294,0.00027593525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000114586386,0.000051332092,0.0005205557,0.00006442934,0.00003327468,0.00010808958,0.00013983494,0.916131,0.0034743533,0.06429674,0.0005385129,0.014527189],"study_design_scores_gemma":[0.000016577706,0.00003094936,0.000062601626,0.0000034144973,0.0000046746013,0.000017842687,0.000019340221,0.9728749,0.000518567,0.025659846,0.00078706373,0.0000041118883],"about_ca_topic_score_codex":0.0016718681,"about_ca_topic_score_gemma":0.0011130929,"teacher_disagreement_score":0.0016718681,"about_ca_system_score_codex":0.0009828578,"about_ca_system_score_gemma":0.00045222984,"threshold_uncertainty_score":0.0071310997},"labels":[],"label_agreement":null},{"id":"W2623507859","doi":"10.1016/j.tcs.2017.05.029","title":"Improved analysis of the online set cover problem with advice","year":2017,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Advice (programming); Set cover problem; Cover (algebra); Online algorithm; Set (abstract data type); Competitive analysis; Upper and lower bounds; Time complexity; Computer science; Mathematics; Computational complexity theory; Quality (philosophy); Algorithm; Discrete mathematics; Theoretical computer science; Combinatorics","score_opus":0.013541789528518268,"score_gpt":0.2784548933950822,"score_spread":0.26491310386656397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2623507859","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06781044,0.0023756353,0.87598825,0.0036139027,0.0004685092,0.00031368932,0.00096111855,0.0012781904,0.047190193],"genre_scores_gemma":[0.6948515,0.002151447,0.25551498,0.001137669,0.0015937459,0.0005026143,0.0014901119,0.0014141692,0.041343708],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99553156,0.0011994763,0.00011330553,0.00046454577,0.0018840005,0.00080703787],"domain_scores_gemma":[0.9709701,0.023979008,0.00084243435,0.0017042345,0.001717678,0.0007865468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003930311,0.0019104416,0.0031270923,0.0023848915,0.0012363973,0.0032972863,0.0054376815,0.0034947963,0.02265198],"category_scores_gemma":[0.031560186,0.0010723614,0.0025963564,0.0027457764,0.002302656,0.0071058148,0.0030181934,0.0057864124,0.0015264401],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007304193,0.0005421789,0.0014342285,0.00078730425,0.00016965656,0.00028913806,0.0003278916,0.6150464,0.003580149,0.27393514,0.024231823,0.078925624],"study_design_scores_gemma":[0.000035586407,0.000047191064,0.00023752492,0.00004356422,0.0000351584,0.00005353924,0.000025227033,0.90100586,0.0004143861,0.09656467,0.0015233267,0.000013949028],"about_ca_topic_score_codex":0.007950711,"about_ca_topic_score_gemma":0.007746951,"teacher_disagreement_score":0.02265198,"about_ca_system_score_codex":0.004003036,"about_ca_system_score_gemma":0.0039367643,"threshold_uncertainty_score":0.075778365},"labels":[],"label_agreement":null},{"id":"W2624136382","doi":"10.1145/1240233.1240246","title":"Sharing the cost more efficiently","year":2007,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Steiner tree problem; Minimum-cost flow problem; Approximation algorithm; Mathematical optimization; Mathematics; Computer science; Provisioning; Flow network; Combinatorics; Discrete mathematics; Computer network","score_opus":0.03576802905243455,"score_gpt":0.30946723761663547,"score_spread":0.27369920856420094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624136382","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14082167,0.0020507614,0.7387528,0.0041646007,0.0008635765,0.0009548147,0.0010214391,0.0031281922,0.108242184],"genre_scores_gemma":[0.6391036,0.0009981303,0.312467,0.0008983237,0.00021841314,0.00043607247,0.0009399746,0.0011083364,0.04383013],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971175,0.0004505449,0.0001272628,0.0005612638,0.00085560104,0.0008877883],"domain_scores_gemma":[0.997036,0.0008489652,0.00015282437,0.0015352862,0.00028503852,0.00014189235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015827969,0.0022208567,0.002474262,0.0010781012,0.0013592803,0.0044180215,0.0031290492,0.0018818894,0.045244638],"category_scores_gemma":[0.007151072,0.00072237843,0.0013416486,0.0025316614,0.0008142192,0.008972271,0.0029466727,0.00272917,0.006156171],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009928279,0.0009453234,0.0012273734,0.0005430633,0.00020643635,0.00035704908,0.00033028447,0.35538512,0.017232373,0.18432364,0.036979217,0.40147734],"study_design_scores_gemma":[0.00022787593,0.00033692239,0.0006627822,0.000092464674,0.00016261285,0.0005726457,0.00036419104,0.7681853,0.006997572,0.17966262,0.042663395,0.000071650546],"about_ca_topic_score_codex":0.0050035757,"about_ca_topic_score_gemma":0.007976279,"teacher_disagreement_score":0.045244638,"about_ca_system_score_codex":0.0029082708,"about_ca_system_score_gemma":0.0036712585,"threshold_uncertainty_score":0.15135837},"labels":[],"label_agreement":null},{"id":"W2625894783","doi":"10.1016/j.tcs.2017.05.021","title":"Know when to persist: Deriving value from a stream buffer","year":2017,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; McMaster University; Toronto Metropolitan University","funders":"","keywords":"Computer science; Random permutation; Competitive analysis; Scheduling (production processes); Data stream; Online algorithm; Permutation (music); Algorithm; Mathematics; Mathematical optimization; Upper and lower bounds; Statistics; Discrete mathematics","score_opus":0.01683647901415447,"score_gpt":0.27598478296795875,"score_spread":0.2591483039538043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2625894783","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05780859,0.0005784046,0.9327365,0.0018220957,0.00015241561,0.00011852583,0.00049102673,0.0012128847,0.005079515],"genre_scores_gemma":[0.73140264,0.00046453855,0.26215422,0.00036147624,0.00024344488,0.00010780006,0.0005033476,0.0005256855,0.00423689],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99782157,0.00051400217,0.0001474299,0.000616652,0.0005701147,0.00033025866],"domain_scores_gemma":[0.9815594,0.013392254,0.0008670255,0.001891766,0.0015075267,0.00078194024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043997997,0.00091810746,0.0016393469,0.0015991573,0.0011238074,0.0044787605,0.0032091297,0.0022832442,0.0042957845],"category_scores_gemma":[0.036137253,0.0008806981,0.0010158892,0.0016397444,0.0027531742,0.012823236,0.0037045751,0.0030801862,0.000699028],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015465408,0.00033936027,0.009308179,0.00036345876,0.00014244582,0.0007516299,0.0016389941,0.25034067,0.0057091275,0.49920335,0.008291566,0.2223646],"study_design_scores_gemma":[0.00004606176,0.000073725416,0.00026664007,0.000057852074,0.000060997307,0.00007833106,0.0001751838,0.60638297,0.0029974917,0.38770795,0.0021211975,0.000031644984],"about_ca_topic_score_codex":0.0041385936,"about_ca_topic_score_gemma":0.0030856496,"teacher_disagreement_score":0.0044787605,"about_ca_system_score_codex":0.0017437382,"about_ca_system_score_gemma":0.002754253,"threshold_uncertainty_score":0.0232687},"labels":[],"label_agreement":null},{"id":"W2626096427","doi":"10.1142/s2301385017500066","title":"Heterogeneous Task Allocation and Sequencing via Decentralized Large Neighborhood Search","year":2017,"lang":"en","type":"article","venue":"Unmanned Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science","keywords":"Robot; Computer science; Travelling salesman problem; Task (project management); Mathematical optimization; Path (computing); Motion planning; Distributed computing; Common value auction; Artificial intelligence; Algorithm; Mathematics; Computer network; Engineering","score_opus":0.030212712552797543,"score_gpt":0.2798406045165266,"score_spread":0.24962789196372906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2626096427","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053788792,0.00018855359,0.941271,0.0001726018,0.000026263231,0.00011629507,0.000048185295,0.0005013511,0.0038870424],"genre_scores_gemma":[0.69841737,0.00013080121,0.29688862,0.00010025568,0.000030881853,0.00036242206,0.00018857032,0.00013711744,0.0037439242],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991322,0.00031730282,0.000029837433,0.00020098296,0.00019611257,0.00012347003],"domain_scores_gemma":[0.9987888,0.00061473635,0.00016922873,0.00020485545,0.00011902278,0.00010338777],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011782764,0.00076260266,0.0011305016,0.00046998073,0.0008346559,0.0007750516,0.0014838185,0.00077458785,0.0023088874],"category_scores_gemma":[0.00282832,0.00044297287,0.0005167614,0.000740573,0.0007793468,0.0014124566,0.0013906658,0.00085913227,0.00038011442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008281442,0.00008872802,0.00028194697,0.000036836467,0.000019585505,0.000045018336,0.00004916813,0.9564008,0.0018708039,0.0081009595,0.0008673941,0.03215593],"study_design_scores_gemma":[0.000021767208,0.000030704356,0.000063269305,0.0000021422902,0.0000037195716,0.00001113666,0.000016785909,0.99274385,0.00041258044,0.006270502,0.00042060835,0.0000029525484],"about_ca_topic_score_codex":0.0047379313,"about_ca_topic_score_gemma":0.0074972385,"teacher_disagreement_score":0.0047379313,"about_ca_system_score_codex":0.0011251235,"about_ca_system_score_gemma":0.0018431558,"threshold_uncertainty_score":0.0094207525},"labels":[],"label_agreement":null},{"id":"W2626553122","doi":"10.1109/radar.2017.7944344","title":"Task selection and scheduling in multifunction multichannel radars","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":35,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Heuristics; Computer science; Scheduling (production processes); Computational complexity theory; Radar; Radar tracker; Job shop scheduling; Branch and bound; Real-time computing; Task analysis; Timeline; Task (project management); Distributed computing; Mathematical optimization; Algorithm; Engineering; Embedded system; Mathematics; Telecommunications","score_opus":0.025128207510878655,"score_gpt":0.27895386953962154,"score_spread":0.2538256620287429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2626553122","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15297422,0.0018091383,0.838812,0.0004289295,0.00016296856,0.00014140777,0.00011336131,0.00032804688,0.00522992],"genre_scores_gemma":[0.85498375,0.00056431664,0.14197287,0.00009507481,0.000078121346,0.00009486015,0.000077882854,0.000050520342,0.0020827034],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926883,0.0002249592,0.000031593496,0.00015000827,0.00012476298,0.00019991292],"domain_scores_gemma":[0.99903107,0.00055438635,0.00014032863,0.00005504417,0.000097434466,0.00012181225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089015043,0.00068406475,0.0009323263,0.0005002734,0.0007007398,0.0007072755,0.0008057265,0.0007124107,0.0016207712],"category_scores_gemma":[0.0020948618,0.00036111914,0.00035002138,0.00085027475,0.0005113776,0.000671504,0.000565884,0.0005931505,0.00018916019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029472736,0.00013536883,0.00069918117,0.00018909451,0.000034578967,0.00017746243,0.00012847155,0.9134323,0.009380433,0.010115836,0.0016965938,0.06371589],"study_design_scores_gemma":[0.00003332561,0.000089478126,0.0003962641,0.000008186474,0.000009492464,0.000055244604,0.00005334241,0.98850024,0.0019049458,0.0077994545,0.0011389661,0.0000110086585],"about_ca_topic_score_codex":0.0051345327,"about_ca_topic_score_gemma":0.0053598885,"teacher_disagreement_score":0.0051345327,"about_ca_system_score_codex":0.0008133434,"about_ca_system_score_gemma":0.0013196982,"threshold_uncertainty_score":0.010209262},"labels":[],"label_agreement":null},{"id":"W2658712968","doi":"10.1007/s00453-017-0337-x","title":"Minimizing Latency of Capacitated k-Tours","year":2017,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Rounding; Vehicle routing problem; Latency (audio); Computer science; Theory of computation; Mathematical optimization; Approximation algorithm; Constant (computer programming); Orienteering; Routing (electronic design automation); Mathematics; Algorithm; Computer network; Telecommunications","score_opus":0.025833774242835745,"score_gpt":0.28174052564240587,"score_spread":0.25590675139957014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2658712968","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46459165,0.0016768336,0.4932323,0.0017443387,0.00021558418,0.00035394685,0.0023644732,0.0012786316,0.034542102],"genre_scores_gemma":[0.8729566,0.0008559384,0.103902474,0.00017207352,0.00007851473,0.00024690691,0.0012176597,0.00068081485,0.019889107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994388,0.00014173033,0.00002080548,0.00008784355,0.000069642636,0.00024102429],"domain_scores_gemma":[0.99729365,0.0015414642,0.00025068273,0.0001897227,0.00028002722,0.0004443989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006259776,0.0013510359,0.0012880781,0.00074548816,0.00080358575,0.0015946666,0.0022430846,0.001134845,0.01140038],"category_scores_gemma":[0.0044496804,0.00070179236,0.0006296004,0.0020072698,0.0006422982,0.0021504364,0.0013954047,0.0014042886,0.0012031163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007568704,0.000209041,0.0012423877,0.00050021405,0.00007852401,0.00014121561,0.00017643438,0.90350264,0.005374052,0.03359095,0.009570562,0.04485713],"study_design_scores_gemma":[0.000054860924,0.0001856362,0.0005747252,0.000034164423,0.000032138087,0.00006626118,0.00014388835,0.95543134,0.0017533479,0.039837416,0.0018701983,0.000016001826],"about_ca_topic_score_codex":0.006830978,"about_ca_topic_score_gemma":0.010349439,"teacher_disagreement_score":0.01140038,"about_ca_system_score_codex":0.0022400483,"about_ca_system_score_gemma":0.0022544265,"threshold_uncertainty_score":0.038138032},"labels":[],"label_agreement":null},{"id":"W2731797971","doi":"10.1007/978-3-319-62389-4_6","title":"Constrained Routing Between Non-Visible Vertices","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Routing (electronic design automation); Static routing; Combinatorics; Equal-cost multi-path routing; Set (abstract data type); Line segment; Line (geometry); Routing table; Algorithm; Mathematics; Computer network; Artificial intelligence; Routing protocol","score_opus":0.03226791445916056,"score_gpt":0.2866327263484828,"score_spread":0.25436481188932225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2731797971","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026591659,0.00084746606,0.916011,0.00052199565,0.00042577562,0.00013136686,0.00087223377,0.0005349417,0.054063573],"genre_scores_gemma":[0.34333113,0.0027517527,0.5364249,0.00040927937,0.00018944615,0.00042663532,0.0018596654,0.0009447228,0.11366261],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994641,0.000098412165,0.000025051804,0.00020302561,0.00012800367,0.000081524944],"domain_scores_gemma":[0.9991498,0.00037466234,0.00008468004,0.00020564036,0.00010403095,0.00008121216],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003998724,0.0013546016,0.00096804096,0.0006140387,0.0008346813,0.002008382,0.0027910515,0.0016769272,0.022808097],"category_scores_gemma":[0.0025636773,0.00091243203,0.00089292135,0.0013289422,0.000653723,0.0028989522,0.002030904,0.0022791266,0.0038609141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045694242,0.00013942942,0.00035504473,0.0011422868,0.000123057,0.0005209411,0.0001580313,0.35054907,0.020994518,0.38949534,0.021243734,0.21482159],"study_design_scores_gemma":[0.00006581551,0.00014679329,0.00036771136,0.00024736725,0.00008568649,0.00043261054,0.00014151532,0.51388454,0.015949339,0.41874146,0.04987455,0.0000625533],"about_ca_topic_score_codex":0.001305945,"about_ca_topic_score_gemma":0.0018998157,"teacher_disagreement_score":0.022808097,"about_ca_system_score_codex":0.00083057635,"about_ca_system_score_gemma":0.0008767767,"threshold_uncertainty_score":0.07630074},"labels":[],"label_agreement":null},{"id":"W2733630045","doi":"10.1109/ipdps.2017.52","title":"Tight Load Balancing Via Randomized Local Search","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of British Columbia; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Load balancing (electrical power); Bin; Ball (mathematics); Randomized algorithm; Queueing theory; Mathematics; Combinatorics; Computer science; Discrete mathematics; Algorithm; Statistics; Geometry","score_opus":0.02664937889080082,"score_gpt":0.29797194599999305,"score_spread":0.2713225671091922,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2733630045","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036480602,0.0010359101,0.9483008,0.0009628783,0.00015976414,0.00022583037,0.000248426,0.0033029872,0.009282785],"genre_scores_gemma":[0.8090522,0.0005053018,0.18013123,0.0007243438,0.00021952877,0.0004916818,0.00058416754,0.00054360536,0.007747935],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99690276,0.0010573413,0.00010494623,0.0007669896,0.0005595787,0.00060828845],"domain_scores_gemma":[0.9935214,0.0041727684,0.0007544128,0.00074255513,0.00037762045,0.00043131204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025872248,0.0019927486,0.0030470237,0.0011460275,0.0012302141,0.0026632042,0.0049175685,0.00235345,0.008885567],"category_scores_gemma":[0.012649455,0.0011325766,0.00097492075,0.001833134,0.001890133,0.0042773494,0.0034089976,0.0023175923,0.0021692312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005660162,0.000259044,0.00043611845,0.00020074834,0.00008666814,0.00013209379,0.00009897038,0.92910093,0.001932666,0.030810563,0.006533491,0.029842636],"study_design_scores_gemma":[0.000060158403,0.00003484063,0.000031968055,0.000006242162,0.0000106881125,0.000014374775,0.000011091494,0.98706144,0.00021345528,0.012069796,0.00047936648,0.000006612192],"about_ca_topic_score_codex":0.0046303226,"about_ca_topic_score_gemma":0.005604288,"teacher_disagreement_score":0.008885567,"about_ca_system_score_codex":0.002261919,"about_ca_system_score_gemma":0.0023976876,"threshold_uncertainty_score":0.029725194},"labels":[],"label_agreement":null},{"id":"W273815955","doi":"","title":"Stochastic Optimal Harvesting Applied to Fisheries","year":2013,"lang":"en","type":"article","venue":"Sound Ideas (University of Puget Sound)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Fishery; Fishing; Computer science; Environmental science; Biology","score_opus":0.018152369329902145,"score_gpt":0.2060457504252967,"score_spread":0.18789338109539455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W273815955","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16031341,0.0004705339,0.8288296,0.0015190216,0.000082247985,0.00004361306,0.000033059045,0.000083764266,0.008624703],"genre_scores_gemma":[0.9491535,0.00031037745,0.045244,0.00015085848,0.000041607564,0.00005033469,0.000018176028,0.00004815252,0.004982933],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99947447,0.00025751998,0.00002395478,0.000083302155,0.0001002992,0.00006044378],"domain_scores_gemma":[0.99832445,0.0011326881,0.0001714846,0.00011572594,0.00016315118,0.000092425755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015960361,0.00048661383,0.000798615,0.00043343933,0.00052118674,0.0010996022,0.0009931623,0.0014243013,0.0013623494],"category_scores_gemma":[0.0054016053,0.00044459902,0.000614914,0.00051977206,0.001563644,0.0013850472,0.0014867329,0.0011057926,0.000085975975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00002441072,0.00003613583,0.00027566784,0.00003556206,0.000018484381,0.000042528452,0.000061344144,0.8347452,0.0019099752,0.15702505,0.00019624471,0.0056292713],"study_design_scores_gemma":[0.0000067001943,0.000014767605,0.000054851043,0.000004971494,0.000004387914,0.000005753569,0.000008001176,0.97263145,0.0001950792,0.026891142,0.00017691264,0.0000059019594],"about_ca_topic_score_codex":0.0057301326,"about_ca_topic_score_gemma":0.0033928761,"teacher_disagreement_score":0.0057301326,"about_ca_system_score_codex":0.0011425382,"about_ca_system_score_gemma":0.0013865564,"threshold_uncertainty_score":0.011393547},"labels":[],"label_agreement":null},{"id":"W2740177778","doi":"10.24963/ijcai.2017/624","title":"A Scalable Approach to Chasing Multiple Moving Targets with Multiple Agents","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Google (Canada)","funders":"","keywords":"Scalability; Computer science; Minimax; Grid; Distributed computing; Mathematical optimization; Mathematics","score_opus":0.045848332633835906,"score_gpt":0.2729597083947184,"score_spread":0.22711137576088247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2740177778","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011982927,0.00027082706,0.9808951,0.00037303907,0.00008362527,0.00011427647,0.00006303542,0.0011452768,0.005071916],"genre_scores_gemma":[0.3683603,0.00031673585,0.6244512,0.00026033554,0.00012233962,0.00043046096,0.0002271578,0.00030037796,0.005531006],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993581,0.00013961969,0.000027884875,0.00017415437,0.00019683583,0.00010348303],"domain_scores_gemma":[0.99907887,0.0004297896,0.000103761406,0.0001783673,0.00009774039,0.00011146517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000966792,0.0011023444,0.0011513842,0.00049982866,0.00093751197,0.00096505415,0.002313948,0.0015112946,0.00582299],"category_scores_gemma":[0.002904385,0.000674635,0.0007788386,0.0007058255,0.0008756588,0.0016450753,0.0025038202,0.0019191169,0.0009274517],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008641734,0.00008627464,0.00049305725,0.00011136862,0.000051363488,0.00011754742,0.00008947987,0.88736486,0.004050425,0.018919572,0.0041944413,0.0844352],"study_design_scores_gemma":[0.000030494652,0.000034337794,0.000078160694,0.0000069285143,0.000008814857,0.000037392347,0.000017943199,0.9899671,0.0006103108,0.007896567,0.0013061066,0.0000059624804],"about_ca_topic_score_codex":0.005426223,"about_ca_topic_score_gemma":0.006182932,"teacher_disagreement_score":0.00582299,"about_ca_system_score_codex":0.0009606933,"about_ca_system_score_gemma":0.002039601,"threshold_uncertainty_score":0.019479811},"labels":[],"label_agreement":null},{"id":"W2747422829","doi":"10.4230/lipics.approx-random.2017.5","title":"Scheduling Problems over Network of Machines","year":2017,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Job shop scheduling; Computer science; Preemption; Scheduling (production processes); Flow shop scheduling; Schedule; Distributed computing; Mathematical optimization; Mathematics; Operating system","score_opus":0.025341678855584946,"score_gpt":0.29091071457535445,"score_spread":0.2655690357197695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2747422829","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06208929,0.008429749,0.9004489,0.0022459198,0.0008653504,0.00031281984,0.0016877016,0.000615763,0.023304425],"genre_scores_gemma":[0.58680975,0.012480091,0.36623362,0.0005310469,0.0014257027,0.00062666787,0.002585501,0.00034518825,0.028962415],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99841094,0.00064667687,0.00010527573,0.00041245192,0.00021068695,0.00021395949],"domain_scores_gemma":[0.99825996,0.0012241208,0.00021528447,0.00010768592,0.0000980815,0.000094851035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011685308,0.0016549582,0.0014445914,0.0009631261,0.0011530936,0.002306277,0.0013705688,0.0020297195,0.0059101167],"category_scores_gemma":[0.004220527,0.0005747662,0.0009852782,0.0032411611,0.0009915554,0.0031110619,0.0013046153,0.001325574,0.0010181444],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018951617,0.00011032579,0.0008366376,0.00087440974,0.00014108597,0.000679344,0.00019400136,0.7908277,0.0019110525,0.15401505,0.00731209,0.042908754],"study_design_scores_gemma":[0.0000739302,0.00012339438,0.00042379322,0.00006726057,0.000049870963,0.0003376951,0.00013364934,0.7314378,0.0007416037,0.24285416,0.023731202,0.000025605988],"about_ca_topic_score_codex":0.0029165817,"about_ca_topic_score_gemma":0.002046911,"teacher_disagreement_score":0.0059101167,"about_ca_system_score_codex":0.00149759,"about_ca_system_score_gemma":0.00077904935,"threshold_uncertainty_score":0.019771338},"labels":[],"label_agreement":null},{"id":"W2749237848","doi":"10.1016/j.jocs.2017.08.008","title":"On enhancing the object migration automaton using the Pursuit paradigm","year":2017,"lang":"en","type":"article","venue":"Journal of Computational Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Benchmark (surveying); Automaton; Field (mathematics); Theoretical computer science; Cellular automaton; Learning automata; Task (project management); Graph; Realization (probability); Object (grammar); Artificial intelligence; Distributed computing; Mathematics","score_opus":0.03582544266573404,"score_gpt":0.3362522927853283,"score_spread":0.30042685011959425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2749237848","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08370548,0.00023895453,0.9092382,0.00028834332,0.000092971946,0.000034840614,0.000022685386,0.00058313477,0.0057954644],"genre_scores_gemma":[0.8105168,0.00030035328,0.18413022,0.00015755111,0.00003294788,0.0000643617,0.00006435526,0.00013000851,0.004603463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997365,0.00006966463,0.000015812786,0.000057901365,0.000074673764,0.00004533311],"domain_scores_gemma":[0.9992436,0.00036632147,0.00005675768,0.00015093926,0.0001189562,0.00006339136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000597887,0.00040284818,0.0006937192,0.00031194356,0.0005319701,0.0008046087,0.0011219708,0.000937952,0.0022511028],"category_scores_gemma":[0.0021827787,0.00021969451,0.0004817023,0.00034205354,0.00082822517,0.0015614437,0.0016588911,0.0009562283,0.00043833422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039226672,0.00023263374,0.0015861287,0.00018620338,0.00005115171,0.00014542238,0.00025115092,0.6283704,0.043235093,0.14421298,0.0015655619,0.17977099],"study_design_scores_gemma":[0.000007066583,0.00008316966,0.00007780462,0.000004692751,0.000007714243,0.000029383309,0.00001816439,0.9824028,0.0024078747,0.014355951,0.0005998847,0.0000053558565],"about_ca_topic_score_codex":0.0016974491,"about_ca_topic_score_gemma":0.0017147583,"teacher_disagreement_score":0.0022511028,"about_ca_system_score_codex":0.0003794938,"about_ca_system_score_gemma":0.0006342092,"threshold_uncertainty_score":0.0075306296},"labels":[],"label_agreement":null},{"id":"W2751970538","doi":"10.1016/j.orl.2018.01.007","title":"On the complexity of instationary gas flows","year":2018,"lang":"en","type":"article","venue":"Operations Research Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Einstein Stiftung Berlin; Deutsche Forschungsgemeinschaft","keywords":"Sequence (biology); Computer science; Biology","score_opus":0.1779869882226343,"score_gpt":0.37888232275254263,"score_spread":0.20089533452990832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751970538","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47550687,0.006304508,0.42326564,0.018133441,0.0006617384,0.00015107193,0.0014365657,0.0003327898,0.074207395],"genre_scores_gemma":[0.94946545,0.0027911086,0.034030735,0.00047711257,0.00062811625,0.00014597233,0.0007291006,0.00019958086,0.011532847],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985885,0.00052495516,0.00006748904,0.00015769666,0.0004210405,0.00024026707],"domain_scores_gemma":[0.97089314,0.02535667,0.001240188,0.0007856463,0.0008687476,0.00085562235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022809284,0.0009990195,0.001585475,0.0017239511,0.0011684959,0.0039047233,0.0018819788,0.0023859513,0.0069499034],"category_scores_gemma":[0.026902528,0.0006147001,0.0011202652,0.0014754744,0.0030218575,0.007871596,0.0030836745,0.0045189857,0.00038490637],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002758877,0.00010673824,0.002227351,0.00022160528,0.00004663555,0.0001858339,0.00022247134,0.3255684,0.0007332937,0.65171045,0.005154263,0.013547063],"study_design_scores_gemma":[0.00002042739,0.000017720986,0.00043302335,0.000022810294,0.000010514737,0.000034131197,0.000049547394,0.54926157,0.00015604666,0.44919378,0.00078509987,0.00001536037],"about_ca_topic_score_codex":0.0041863965,"about_ca_topic_score_gemma":0.0031211562,"teacher_disagreement_score":0.0069499034,"about_ca_system_score_codex":0.0023866564,"about_ca_system_score_gemma":0.0016687997,"threshold_uncertainty_score":0.023249745},"labels":[],"label_agreement":null},{"id":"W2754604279","doi":"10.1007/s00453-017-0373-6","title":"Algorithms for Communication Scheduling in Data Gathering Network with Data Compression","year":2017,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":42,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Natural Science Foundation of Ningbo; China Scholarship Council","keywords":"Job shop scheduling; Polynomial-time approximation scheme; Approximation algorithm; Computer science; Data compression; Scheduling (production processes); Mathematical optimization; Time complexity; Dynamic programming; Theory of computation; Wireless sensor network; Base station; Optimization problem; Data transmission; Algorithm; Mathematics; Computer network","score_opus":0.18964819929404286,"score_gpt":0.38079587530731945,"score_spread":0.1911476760132766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754604279","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018635133,0.0005705646,0.9760485,0.0005633513,0.00011055173,0.00014929673,0.000115206385,0.00039464436,0.0034127266],"genre_scores_gemma":[0.35318276,0.0008220695,0.63910323,0.00021347673,0.00025952095,0.0006614588,0.00036596102,0.00025934837,0.005132297],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914384,0.00028369864,0.000047804937,0.00015921293,0.00019756422,0.00016784242],"domain_scores_gemma":[0.9948631,0.0038939503,0.00032672976,0.00035044496,0.00037441432,0.00019136255],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022564104,0.0012172473,0.0016488683,0.0015408885,0.001502066,0.001959741,0.0023852228,0.001686062,0.00421753],"category_scores_gemma":[0.008411657,0.0007037025,0.0009261139,0.0028231456,0.0011574692,0.002769157,0.0017714646,0.0018759541,0.0004309026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018427278,0.00011876119,0.0005472411,0.0001580365,0.00003201106,0.000032963482,0.00012384239,0.8786215,0.0007841712,0.040329587,0.004615804,0.07445181],"study_design_scores_gemma":[0.00002077271,0.000016144144,0.00005770919,0.0000067828896,0.000007074626,0.00000994572,0.000018594204,0.98300433,0.00024421245,0.016198887,0.0004120374,0.0000035705295],"about_ca_topic_score_codex":0.006644467,"about_ca_topic_score_gemma":0.005430401,"teacher_disagreement_score":0.006644467,"about_ca_system_score_codex":0.0025802942,"about_ca_system_score_gemma":0.0037001425,"threshold_uncertainty_score":0.018721461},"labels":[],"label_agreement":null},{"id":"W2754752206","doi":"10.1016/j.tcs.2017.08.023","title":"A general framework for searching on a line","year":2017,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Carleton University","funders":"","keywords":"Competitive analysis; Constant (computer programming); Search cost; Mathematics; Mathematical optimization; Line (geometry); Search problem; Upper and lower bounds; Fixed cost; Computer science","score_opus":0.048514790885910465,"score_gpt":0.3635690444791842,"score_spread":0.3150542535932737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754752206","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015815246,0.0002848584,0.98594785,0.00043322454,0.00005992063,0.000028296945,0.00007352286,0.00016315712,0.011427669],"genre_scores_gemma":[0.15088049,0.001368808,0.81882846,0.00053721864,0.000310699,0.0003688667,0.0003716024,0.0003773954,0.026956405],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990683,0.00031313035,0.00005338037,0.00021443467,0.00023860262,0.000112278976],"domain_scores_gemma":[0.999111,0.00039328446,0.00006400239,0.00019777131,0.0001631731,0.000070800554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011102812,0.0010009845,0.001033848,0.0015324915,0.0014757484,0.0028417313,0.003364946,0.0023284866,0.017483031],"category_scores_gemma":[0.0045476095,0.00060072815,0.0016155483,0.0027748712,0.0022522276,0.005391902,0.0025938929,0.0029082224,0.0032431106],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000152080465,0.000018284743,0.00013496328,0.000068514615,0.000011518766,0.000054422344,0.000111388516,0.03305468,0.0005045778,0.94139814,0.0037072792,0.020921068],"study_design_scores_gemma":[0.000018246197,0.000029025197,0.000065097396,0.000031195104,0.000012456147,0.000077639386,0.000047482103,0.20532341,0.00023769845,0.7735708,0.020571593,0.000015367652],"about_ca_topic_score_codex":0.0034967014,"about_ca_topic_score_gemma":0.0032501672,"teacher_disagreement_score":0.017483031,"about_ca_system_score_codex":0.0012754482,"about_ca_system_score_gemma":0.0011070268,"threshold_uncertainty_score":0.05848652},"labels":[],"label_agreement":null},{"id":"W2754813051","doi":"10.1016/j.jcss.2017.10.005","title":"Use of information, memory and randomization in asynchronous gathering","year":2017,"lang":"en","type":"preprint","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Construct (python library); Computer science; Asynchronous communication; Turing machine; Theoretical computer science; Grid; Finite-state machine; Algorithm; Mathematics; Programming language","score_opus":0.03790261855482626,"score_gpt":0.2688181432647735,"score_spread":0.23091552470994722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2754813051","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3679226,0.0011457169,0.61161083,0.0021801123,0.00028614883,0.00018760032,0.00018779328,0.0011007308,0.015378441],"genre_scores_gemma":[0.9791403,0.00010840211,0.018911289,0.00008977266,0.000058244183,0.00007220649,0.000027834312,0.00006646768,0.0015254411],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966858,0.0017879135,0.00021878675,0.00053912797,0.00038361485,0.00038472936],"domain_scores_gemma":[0.93181825,0.05422162,0.0035700162,0.007372487,0.001477881,0.0015397449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067085996,0.00060294085,0.0014795313,0.0012206231,0.0020014513,0.0036170718,0.0022460406,0.001749613,0.0050179423],"category_scores_gemma":[0.06135817,0.00075462065,0.00064755994,0.0009733291,0.0022959602,0.0065507954,0.0037313127,0.0016816405,0.00048315772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050715376,0.0007208833,0.0073025646,0.0005122799,0.00028461622,0.0006076024,0.0011730499,0.3296965,0.019283671,0.4958887,0.0046612737,0.13479738],"study_design_scores_gemma":[0.00029005922,0.00032245836,0.0007468832,0.000036938523,0.00011394382,0.00015257754,0.0001460901,0.73386747,0.005922972,0.25695994,0.0013689855,0.00007169001],"about_ca_topic_score_codex":0.0009341697,"about_ca_topic_score_gemma":0.001374411,"teacher_disagreement_score":0.0067085996,"about_ca_system_score_codex":0.0011390505,"about_ca_system_score_gemma":0.0018972541,"threshold_uncertainty_score":0.03547895},"labels":[],"label_agreement":null},{"id":"W2762128374","doi":"10.1109/infocom.2017.8057149","title":"Single restart with time stamps for computational offloading in a semi-online setting","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Job shop scheduling; Competitive analysis; Computer science; Scheduling (production processes); Heuristic; Task (project management); Computational complexity theory; Parallel computing; Server; Constant (computer programming); A priori and a posteriori; Asymptotically optimal algorithm; Online algorithm; Execution time; Time complexity; Distributed computing; Mathematical optimization; Algorithm; Upper and lower bounds; Mathematics; Artificial intelligence; Embedded system; Computer network","score_opus":0.03434765795284483,"score_gpt":0.293111656975736,"score_spread":0.25876399902289116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762128374","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.106300734,0.00065690785,0.88805723,0.00043470334,0.00008825624,0.00010982095,0.00010967987,0.00056015066,0.003682585],"genre_scores_gemma":[0.9093331,0.00033060252,0.08790256,0.000121978344,0.00007270411,0.00014155512,0.00012631943,0.000118545206,0.0018527195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877983,0.00047079794,0.00005137013,0.00025798383,0.0002174444,0.00022260116],"domain_scores_gemma":[0.99587786,0.0028606413,0.00049428345,0.0003566494,0.000175119,0.00023543857],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016412478,0.0011065919,0.0015510641,0.0004207593,0.0006136728,0.00124008,0.0016870109,0.0011310063,0.00212317],"category_scores_gemma":[0.005973774,0.0006717642,0.00078943034,0.0008054421,0.001198589,0.0018489821,0.00091919326,0.0011402848,0.00033832242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003271568,0.0001248255,0.00050216477,0.00011842225,0.00003653865,0.00012590269,0.000056217505,0.96753055,0.002551388,0.010751272,0.00068804447,0.017187439],"study_design_scores_gemma":[0.000011717573,0.000033108143,0.00006993764,0.0000025081508,0.0000044177586,0.00001677132,0.0000060159605,0.995652,0.0003346112,0.0037235033,0.00014226054,0.0000031267443],"about_ca_topic_score_codex":0.0051541217,"about_ca_topic_score_gemma":0.0033945714,"teacher_disagreement_score":0.0051541217,"about_ca_system_score_codex":0.001028304,"about_ca_system_score_gemma":0.0018448813,"threshold_uncertainty_score":0.010248244},"labels":[],"label_agreement":null},{"id":"W2762426729","doi":"10.1007/978-3-319-73117-9_27","title":"Exploring Graphs with Time Constraints by Unreliable Collections of Mobile Robots","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Robot; Traverse; Computer science; Graph; Mobile robot; A priori and a posteriori; Time complexity; Node (physics); Enhanced Data Rates for GSM Evolution; Adversary; Theoretical computer science; Algorithm; Artificial intelligence","score_opus":0.03790816574046223,"score_gpt":0.2490121587925893,"score_spread":0.21110399305212707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2762426729","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17560475,0.0013052807,0.8140765,0.00065209664,0.00013135913,0.000097068245,0.00036567045,0.0007133306,0.0070539736],"genre_scores_gemma":[0.7946707,0.0010154443,0.19430113,0.00017294181,0.00021295875,0.0002559617,0.0007675246,0.00053636706,0.008066877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991098,0.00028849326,0.00004434909,0.00024027308,0.00019525421,0.00012184183],"domain_scores_gemma":[0.99555546,0.0029006966,0.00037689862,0.0006053359,0.00022778643,0.00033378246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010653285,0.0014203077,0.002508277,0.0014334824,0.0016831863,0.0021160638,0.0046234904,0.0019077094,0.0035256643],"category_scores_gemma":[0.007948767,0.0021712945,0.0017539315,0.0030747661,0.0021020563,0.0050489153,0.0052217455,0.0021983595,0.00057750026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002927554,0.00005331513,0.00075358566,0.00022566105,0.00010234684,0.0003674312,0.00034700066,0.9406003,0.0024863193,0.030911488,0.0023479823,0.021511864],"study_design_scores_gemma":[0.000033129018,0.000060369923,0.00022691407,0.000023289685,0.000038384947,0.00008564493,0.0001188324,0.9404616,0.0007999325,0.05673224,0.0013988259,0.000020859705],"about_ca_topic_score_codex":0.004727061,"about_ca_topic_score_gemma":0.007037956,"teacher_disagreement_score":0.004727061,"about_ca_system_score_codex":0.001158164,"about_ca_system_score_gemma":0.0008607846,"threshold_uncertainty_score":0.011794567},"labels":[],"label_agreement":null},{"id":"W2763019392","doi":"10.1109/infocom.2017.8057085","title":"Efficient minimization of sum and differential costs on machines with job placement constraints","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Minification; Computer science; Algorithm; Mathematics; Discrete mathematics; Mathematical optimization; Combinatorics","score_opus":0.01672313873068668,"score_gpt":0.26577698374377,"score_spread":0.24905384501308334,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763019392","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14370522,0.0005603534,0.84680074,0.0005166598,0.000072188916,0.00018988001,0.0002235657,0.00054721575,0.007384169],"genre_scores_gemma":[0.6552642,0.00042587012,0.33650216,0.00015707324,0.000068133304,0.00021809601,0.00034857064,0.0002924585,0.0067234775],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871147,0.00041339255,0.000045654615,0.0002300876,0.00030591033,0.00029362264],"domain_scores_gemma":[0.9982712,0.0010689583,0.00014863971,0.0001601563,0.0001843831,0.0001667021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015055392,0.0013532393,0.0015107667,0.0008146829,0.00070519454,0.0014111652,0.0022623278,0.0011144255,0.0041555925],"category_scores_gemma":[0.003874607,0.00079606584,0.00065953354,0.0018401273,0.0009777029,0.0020347491,0.0014180628,0.0009649824,0.00042145737],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024711833,0.00008598309,0.00052878546,0.00021531197,0.00003307589,0.000110761146,0.000063882886,0.9182134,0.0041397577,0.018304082,0.0018746051,0.05618317],"study_design_scores_gemma":[0.00002557475,0.000058162892,0.00027517695,0.000007463261,0.00001041525,0.000036268062,0.000027074375,0.9798759,0.0018051958,0.01708352,0.00078750774,0.000007682727],"about_ca_topic_score_codex":0.0046646376,"about_ca_topic_score_gemma":0.0052959407,"teacher_disagreement_score":0.0046646376,"about_ca_system_score_codex":0.0020829807,"about_ca_system_score_gemma":0.0018029244,"threshold_uncertainty_score":0.015113115},"labels":[],"label_agreement":null},{"id":"W2765981104","doi":"10.1016/j.ipl.2018.04.006","title":"Reaching a target in the plane with no information","year":2018,"lang":"en","type":"preprint","venue":"Information Processing Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Multiplicative function; Plane (geometry); Bounded function; Binary logarithm; Trajectory; Combinatorics; Mathematics; Euclidean geometry; Euclidean distance; Computer science; Discrete mathematics; Physics; Mathematical analysis; Geometry","score_opus":0.012523325368783537,"score_gpt":0.23126683504676068,"score_spread":0.21874350967797715,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2765981104","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10458619,0.0005822816,0.84443486,0.0024613666,0.0001824774,0.00014797242,0.00059822627,0.0005067512,0.046499863],"genre_scores_gemma":[0.78748983,0.0007594771,0.18810089,0.0005824912,0.0001743803,0.0002998963,0.00087053096,0.0002745286,0.021447962],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99913293,0.00021017682,0.000041975352,0.00026659932,0.00020366062,0.00014474904],"domain_scores_gemma":[0.9979001,0.0014926682,0.00018587019,0.00014620122,0.00016618735,0.000109011824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009802175,0.0014906157,0.0016713929,0.000960956,0.00092809834,0.0027433436,0.0012193745,0.004475804,0.005192594],"category_scores_gemma":[0.0070969732,0.000805014,0.0008791416,0.001006356,0.0016472349,0.0040314286,0.0035053787,0.002366572,0.0014839867],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017666023,0.00023629615,0.0015204819,0.0005824724,0.00021016276,0.00069762836,0.00042202833,0.73934174,0.013480208,0.17857179,0.0084474,0.05472322],"study_design_scores_gemma":[0.00008531028,0.0001381487,0.00033049096,0.00004143445,0.000028456552,0.00013393241,0.00012502805,0.8589654,0.0028129758,0.13583228,0.0014781414,0.000028418854],"about_ca_topic_score_codex":0.003469851,"about_ca_topic_score_gemma":0.0017191431,"teacher_disagreement_score":0.005192594,"about_ca_system_score_codex":0.0010402561,"about_ca_system_score_gemma":0.0012726743,"threshold_uncertainty_score":0.017370999},"labels":[],"label_agreement":null},{"id":"W2766495319","doi":"10.1016/j.ifacol.2017.08.420","title":"Parameter Tuning for Prediction-based Quadcopter Trajectory Planning using Learning Automata","year":2017,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Royal Military College of Canada","funders":"","keywords":"Quadcopter; Weighting; Control theory (sociology); Model predictive control; Computer science; Sequence (biology); Trajectory; Tracking (education); Function (biology); Tracking error; Control (management); Artificial intelligence; Engineering","score_opus":0.08699319490310632,"score_gpt":0.34465205873618926,"score_spread":0.25765886383308295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766495319","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03699196,0.00020580749,0.95953774,0.00009965411,0.000031265554,0.000038616017,0.000031776395,0.0006032255,0.0024599193],"genre_scores_gemma":[0.936456,0.00010995951,0.062252894,0.000038944476,0.000009710228,0.00008912167,0.000046616566,0.00004498927,0.0009517722],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99981743,0.000038581693,0.000014626401,0.000060808186,0.00004618272,0.000022446118],"domain_scores_gemma":[0.9993432,0.0003798184,0.00008355384,0.00008521666,0.00008659124,0.000021592243],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038485334,0.0004621194,0.0005464473,0.00030174627,0.00035046734,0.00052938564,0.0006171059,0.0005739371,0.001473202],"category_scores_gemma":[0.0019392328,0.00033665498,0.00031697768,0.00021358798,0.00055078143,0.0006176941,0.0006516771,0.00087483606,0.00032006597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031199772,0.000021779186,0.00040062427,0.000036756563,0.000013350284,0.000034023262,0.00004942308,0.9592042,0.004063267,0.0038086972,0.00029991954,0.03203678],"study_design_scores_gemma":[0.000002321411,0.000013066802,0.00003683168,0.0000029540029,0.0000018280614,0.0000067554697,0.0000029380585,0.99814975,0.0006983292,0.00092778425,0.0001553161,0.0000021865785],"about_ca_topic_score_codex":0.0029523983,"about_ca_topic_score_gemma":0.0026156614,"teacher_disagreement_score":0.0029523983,"about_ca_system_score_codex":0.00045744807,"about_ca_system_score_gemma":0.00050767866,"threshold_uncertainty_score":0.005870402},"labels":[],"label_agreement":null},{"id":"W2774748477","doi":"10.1109/mlsp.2017.8168149","title":"Partitioning in signal processing using the object migration automaton and the pursuit paradigm","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Benchmark (surveying); Field (mathematics); Learning automata; Cellular automaton; Automaton; Process (computing); Task (project management); Theoretical computer science; Signal processing; Object (grammar); Artificial intelligence; Distributed computing; Programming language","score_opus":0.039454626781235694,"score_gpt":0.3027507960456966,"score_spread":0.2632961692644609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2774748477","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03796067,0.00060788874,0.95512795,0.00044973686,0.000101421225,0.00006714551,0.00010052299,0.00055753865,0.0050270874],"genre_scores_gemma":[0.69842046,0.00067755254,0.2940077,0.00025180663,0.00015058913,0.0003046429,0.00030592404,0.00013944096,0.005741875],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924797,0.00018451264,0.00006224152,0.00019902078,0.00021826828,0.00008797641],"domain_scores_gemma":[0.9989838,0.0005453087,0.000085383894,0.00017533627,0.00014187118,0.00006832751],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058777514,0.00055767805,0.00063141884,0.00045470323,0.000695841,0.0013316218,0.0011297701,0.0010385158,0.002286392],"category_scores_gemma":[0.0021632677,0.0002549814,0.0009298398,0.00052351214,0.0015128239,0.001686774,0.0014668118,0.0014762664,0.00052761595],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036966157,0.00011322852,0.0016279153,0.000266494,0.00007615052,0.00027449036,0.0006156507,0.5047703,0.024590738,0.35776064,0.0024615799,0.107073165],"study_design_scores_gemma":[0.00001726387,0.00013849433,0.00023086338,0.000017171787,0.000015108911,0.00009275184,0.000042257278,0.8912555,0.003526207,0.10125734,0.003384676,0.000022426282],"about_ca_topic_score_codex":0.0017370278,"about_ca_topic_score_gemma":0.001571683,"teacher_disagreement_score":0.002286392,"about_ca_system_score_codex":0.00077134283,"about_ca_system_score_gemma":0.0008153606,"threshold_uncertainty_score":0.007648766},"labels":[],"label_agreement":null},{"id":"W2775462516","doi":"10.1007/978-3-642-12200-2_59","title":"Layered Working-Set Trees","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Set (abstract data type); Theoretical computer science; Programming language","score_opus":0.031656926722692824,"score_gpt":0.2645210166984087,"score_spread":0.2328640899757159,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2775462516","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020931698,0.0013049066,0.86958706,0.0006295885,0.00020016402,0.00008029137,0.0012889854,0.002229729,0.10374772],"genre_scores_gemma":[0.28216988,0.002333879,0.61403215,0.00037381772,0.00025687437,0.00026072006,0.00391101,0.0015895399,0.0950721],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994723,0.00007372527,0.000037720238,0.00009063729,0.00023003176,0.00009552185],"domain_scores_gemma":[0.99858886,0.00044989682,0.000064778,0.0005468202,0.00020454195,0.00014516525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00066727883,0.0005676792,0.00086971244,0.0012208814,0.001110324,0.0029187086,0.0016742822,0.0008549311,0.019395899],"category_scores_gemma":[0.003374362,0.0007016727,0.00089177315,0.0023011083,0.00094905833,0.004505552,0.0024153257,0.0025943888,0.0072884215],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060636812,0.000038089307,0.0002634177,0.000127588,0.00002321683,0.000068068744,0.00018351151,0.011260321,0.0026224277,0.78300047,0.016177127,0.18617512],"study_design_scores_gemma":[0.000009384334,0.000021704316,0.00020486569,0.00005644805,0.00002212309,0.00020046381,0.000048591606,0.038595557,0.0020491972,0.91299945,0.045774415,0.000017839919],"about_ca_topic_score_codex":0.00063071394,"about_ca_topic_score_gemma":0.001129111,"teacher_disagreement_score":0.019395899,"about_ca_system_score_codex":0.00076756923,"about_ca_system_score_gemma":0.0007099549,"threshold_uncertainty_score":0.064885736},"labels":[],"label_agreement":null},{"id":"W2779139333","doi":"10.1137/1.9781611975031.47","title":"Strong Algorithms for the Ordinal Matroid Secretary Problem","year":2018,"lang":"en","type":"preprint","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Matroid; Combinatorics; Mathematics; Secretary problem; Graphic matroid; Matroid partitioning; Rank (graph theory); Algorithm; Discrete mathematics; Competitive analysis; Upper and lower bounds; Mathematical optimization","score_opus":0.11112603762846568,"score_gpt":0.29825884007058834,"score_spread":0.18713280244212266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2779139333","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033546,0.0003670813,0.9505648,0.0014019572,0.00008687099,0.00018164393,0.00021423878,0.0010143911,0.0126230195],"genre_scores_gemma":[0.40915424,0.00045207413,0.5777382,0.00069730997,0.00028354776,0.0005871497,0.0008044787,0.0005164338,0.009766547],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9949588,0.0019038368,0.0003161182,0.0009828284,0.0012686568,0.0005697757],"domain_scores_gemma":[0.98767906,0.0075911307,0.0008436033,0.0021686808,0.0009957775,0.00072182994],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039737304,0.0011307535,0.0012392954,0.0010383461,0.0013153282,0.0041886196,0.003636688,0.002280707,0.0082590785],"category_scores_gemma":[0.023556793,0.00076697837,0.0016010891,0.0020972895,0.0017948587,0.006766587,0.0049310713,0.0040281694,0.0018371948],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005912614,0.00048255836,0.0016237786,0.0004868726,0.00011171221,0.0001153879,0.0005732769,0.10852862,0.0045870002,0.7030078,0.012317847,0.16757381],"study_design_scores_gemma":[0.00014951084,0.0001781096,0.00026687628,0.000038444603,0.00004268457,0.0001531171,0.00011396888,0.4584912,0.003308005,0.5294611,0.007762711,0.000034320063],"about_ca_topic_score_codex":0.0008614143,"about_ca_topic_score_gemma":0.0013937054,"teacher_disagreement_score":0.0082590785,"about_ca_system_score_codex":0.002313805,"about_ca_system_score_gemma":0.002738619,"threshold_uncertainty_score":0.027629375},"labels":[],"label_agreement":null},{"id":"W2779959840","doi":"10.1007/978-3-319-72751-6_8","title":"Energy-Optimal Broadcast in a Tree with Mobile Agents","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Tree (set theory); Node (physics); Mobile agent; Broadcasting (networking); Enhanced Data Rates for GSM Evolution; Set (abstract data type); Root (linguistics); Energy (signal processing); Algorithm; Theoretical computer science; Distributed computing; Combinatorics; Computer network; Mathematics; Artificial intelligence","score_opus":0.021197720684144168,"score_gpt":0.26003828623646036,"score_spread":0.2388405655523162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2779959840","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07798408,0.0013657574,0.89538854,0.0013247636,0.00020727434,0.000111414076,0.00029837,0.00042919352,0.022890655],"genre_scores_gemma":[0.72559434,0.001977696,0.24056749,0.00033431043,0.00024902643,0.00019714159,0.00040346806,0.00032595504,0.030350497],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948967,0.00017829912,0.000023825236,0.000081468745,0.000110742236,0.00011600773],"domain_scores_gemma":[0.99806756,0.0014027428,0.000109623055,0.00009283034,0.00017811677,0.00014923557],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00089044514,0.0006070666,0.001539106,0.00073989615,0.00091237115,0.0015147337,0.0016312227,0.0018160337,0.003958371],"category_scores_gemma":[0.004465859,0.00063455896,0.0006533356,0.0014223218,0.0010570841,0.0018563954,0.0017166752,0.0015293085,0.00076956465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047188808,0.0001256999,0.000308776,0.0003491341,0.000060042603,0.00018331398,0.00027585178,0.7356224,0.00582077,0.20803322,0.008565451,0.040183425],"study_design_scores_gemma":[0.00004952926,0.000046998528,0.00007441727,0.000028352919,0.00001871074,0.000057545534,0.000056291086,0.9076622,0.00054537266,0.089993276,0.0014573148,0.000009967456],"about_ca_topic_score_codex":0.0026117158,"about_ca_topic_score_gemma":0.0026140222,"teacher_disagreement_score":0.003958371,"about_ca_system_score_codex":0.0012749921,"about_ca_system_score_gemma":0.00085948635,"threshold_uncertainty_score":0.013242066},"labels":[],"label_agreement":null},{"id":"W2783332435","doi":"10.1109/ictcs.2017.40","title":"On Utilizing the Pursuit Paradigm to Enhance the Deadlock-Preventing Object Migration Automaton","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Deadlock; Computer science; Automaton; Cellular automaton; Object (grammar); Distributed computing; Theoretical computer science; Field (mathematics); Property (philosophy); Learning automata; State (computer science); Artificial intelligence; Algorithm; Mathematics","score_opus":0.030155251228476985,"score_gpt":0.32944596149850136,"score_spread":0.29929071027002435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783332435","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027738424,0.00015329271,0.9672028,0.00025540226,0.00003044605,0.000033491677,0.0000186543,0.00050633564,0.004061063],"genre_scores_gemma":[0.64067626,0.00034346204,0.35288283,0.00023538833,0.00004088094,0.00017119599,0.000077755125,0.00010637863,0.005465956],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955887,0.00013275535,0.000033878718,0.000100506644,0.00011533456,0.000058626905],"domain_scores_gemma":[0.9988882,0.00051969255,0.00011204365,0.00021013015,0.00018569386,0.00008434269],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007127275,0.0003585749,0.0004464779,0.0004041055,0.0005473214,0.0009189564,0.0011083923,0.000749769,0.0020011228],"category_scores_gemma":[0.00232344,0.00022638192,0.00066622306,0.00033236746,0.0013657407,0.0015408121,0.0016715459,0.0013403663,0.0005371312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002654325,0.00020068263,0.0024599398,0.00028853546,0.000059150923,0.00022030273,0.0006707292,0.41677856,0.045513272,0.3068168,0.0012461261,0.22548059],"study_design_scores_gemma":[0.000014655764,0.00023575804,0.00019270567,0.000017316042,0.000015692212,0.0000820504,0.000033794124,0.94529015,0.006134207,0.04448393,0.0034831967,0.000016517757],"about_ca_topic_score_codex":0.0012346485,"about_ca_topic_score_gemma":0.0017879274,"teacher_disagreement_score":0.0020011228,"about_ca_system_score_codex":0.0005880988,"about_ca_system_score_gemma":0.0010376811,"threshold_uncertainty_score":0.0066944957},"labels":[],"label_agreement":null},{"id":"W278336051","doi":"10.1007/s10489-015-0670-1","title":"A formal proof of the 𝜖-optimality of discretized pursuit algorithms","year":2015,"lang":"en","type":"article","venue":"Applied Intelligence","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Mathematical proof; Computer science; Algorithm; Discretization; Formal proof; Monotonic function; Action (physics); Proof of concept; Mathematics","score_opus":0.05193330201294354,"score_gpt":0.2882998452492054,"score_spread":0.23636654323626183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W278336051","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007498519,0.0012660668,0.9236065,0.0038516023,0.0005772424,0.000070072274,0.00030241,0.00019250454,0.062634975],"genre_scores_gemma":[0.4691773,0.003604772,0.49802727,0.0034836968,0.0017323056,0.00047039866,0.00057875033,0.00038033043,0.02254513],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971716,0.00077859825,0.00019213941,0.000411775,0.0011425405,0.0003034157],"domain_scores_gemma":[0.9924109,0.0051214825,0.00037016193,0.0007891205,0.0010691655,0.00023920667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003387083,0.0012474884,0.0010297054,0.0015078792,0.001473682,0.0031949938,0.002099766,0.0022479445,0.010579699],"category_scores_gemma":[0.017225703,0.0009399922,0.0020928024,0.0014200616,0.00738093,0.005433423,0.0052103517,0.0070558237,0.0017906142],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013419442,0.000014235337,0.000043121963,0.000057600035,0.00000960845,0.000029372794,0.00004902303,0.0030470665,0.00038285367,0.98945624,0.0015825938,0.0053148926],"study_design_scores_gemma":[0.000019990093,0.000018520266,0.00006949218,0.000039211667,0.0000074442496,0.00006114699,0.000018352303,0.01734888,0.00043119446,0.9763672,0.0056062266,0.000012449925],"about_ca_topic_score_codex":0.0011804181,"about_ca_topic_score_gemma":0.000817412,"teacher_disagreement_score":0.010579699,"about_ca_system_score_codex":0.0018896088,"about_ca_system_score_gemma":0.0017555669,"threshold_uncertainty_score":0.035392642},"labels":[],"label_agreement":null},{"id":"W2783784097","doi":"","title":"Cognitive intelligent personal assistants / agents","year":2017,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Personal information management; Personally identifiable information; World Wide Web; Context (archaeology); Human–computer interaction; Cognition; Intelligent agent; Information system; Computer security; Artificial intelligence; Management information systems; Engineering; Psychology","score_opus":0.03627925197326099,"score_gpt":0.28279087176093004,"score_spread":0.24651161978766906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2783784097","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017178481,0.003004004,0.83403915,0.0029917762,0.0006283597,0.0005805705,0.0004189117,0.0036876025,0.1374712],"genre_scores_gemma":[0.38285,0.0049682204,0.52303904,0.0019306984,0.0007973692,0.00087453274,0.0010454925,0.0002363914,0.08425828],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986337,0.00035234293,0.00013132048,0.00032054307,0.00042520437,0.00013686968],"domain_scores_gemma":[0.99820924,0.00052210985,0.00019436586,0.00040383826,0.00046780746,0.00020267135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012258658,0.0011482167,0.00059761666,0.0007430911,0.0011486083,0.004057961,0.002077829,0.0016815077,0.009495476],"category_scores_gemma":[0.004923202,0.0005367691,0.00053092133,0.0008227371,0.0012947583,0.0035276315,0.0023887,0.0013922262,0.00460034],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027352286,0.00037250205,0.0024413934,0.0014237921,0.00020486335,0.0008504296,0.0018367467,0.026880888,0.008601404,0.5107498,0.039737683,0.4066269],"study_design_scores_gemma":[0.00020837461,0.00019076676,0.0009941311,0.00039855484,0.00018234228,0.0011180716,0.0010639522,0.1509739,0.007914004,0.40005586,0.4367691,0.00013098966],"about_ca_topic_score_codex":0.002706744,"about_ca_topic_score_gemma":0.0026326517,"teacher_disagreement_score":0.009495476,"about_ca_system_score_codex":0.0006191727,"about_ca_system_score_gemma":0.001096,"threshold_uncertainty_score":0.03176552},"labels":[],"label_agreement":null},{"id":"W2786984082","doi":"10.1142/s1793830918500258","title":"Asymptotically optimal scheduling of random malleable demands in smart grid","year":2018,"lang":"en","type":"article","venue":"Discrete Mathematics Algorithms and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Scheduling (production processes); Mathematics; Time horizon; Regular polygon; Bounded function; Grid; Computer science","score_opus":0.015262041106588185,"score_gpt":0.27295208666951287,"score_spread":0.2576900455629247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2786984082","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31850165,0.0009336455,0.67311144,0.0012218014,0.00010562033,0.000081570535,0.00027687533,0.00039304252,0.0053743552],"genre_scores_gemma":[0.97171974,0.0003196271,0.025913065,0.0000980193,0.00004659694,0.00005594887,0.00012181889,0.0000670405,0.0016582139],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993098,0.00027878594,0.00003312972,0.00010882238,0.000103917206,0.00016566094],"domain_scores_gemma":[0.99596894,0.0030423442,0.00047412462,0.00013712254,0.0001973318,0.00018022457],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015364125,0.0006936167,0.0013105434,0.0003916854,0.00031965005,0.0007262702,0.0007774897,0.0008196661,0.0017365391],"category_scores_gemma":[0.006727188,0.00058695866,0.00041602392,0.00077013095,0.00083781214,0.0012794714,0.0005898831,0.00087898166,0.00016862847],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013718105,0.00003625353,0.0004022922,0.00005420162,0.00001565567,0.00004404724,0.000021977494,0.98558515,0.000765687,0.009086794,0.00044690716,0.0034038336],"study_design_scores_gemma":[0.0000135038745,0.000021924952,0.00009967351,0.0000020928467,0.000003108413,0.000006901684,0.000009114055,0.9938877,0.00015147823,0.005711432,0.000090525915,0.00000247682],"about_ca_topic_score_codex":0.004512555,"about_ca_topic_score_gemma":0.0028323545,"teacher_disagreement_score":0.004512555,"about_ca_system_score_codex":0.0014808282,"about_ca_system_score_gemma":0.00096830114,"threshold_uncertainty_score":0.010744214},"labels":[],"label_agreement":null},{"id":"W278851003","doi":"10.1007/978-3-642-30347-0_1","title":"Distributed Algorithms by Forgetful Mobile Robots","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Snapshot (computer storage); Robot; Computer science; Mobile robot; Scratch; Distributed computing; Distributed algorithm; Algorithm; Artificial intelligence; Real-time computing; Operating system","score_opus":0.01648801243812546,"score_gpt":0.2559231648571692,"score_spread":0.23943515241904376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W278851003","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017604591,0.0012935501,0.96830946,0.00034421537,0.00031334528,0.000037883387,0.000036383943,0.00068285177,0.011377809],"genre_scores_gemma":[0.61560696,0.002222458,0.33869976,0.0003330887,0.00043769242,0.00031008935,0.00018887037,0.00051200984,0.041688975],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993623,0.00014325074,0.000032860466,0.00015383607,0.00021685779,0.00009088039],"domain_scores_gemma":[0.99847394,0.0006900167,0.0000778963,0.0005258504,0.00014715575,0.000085210195],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006790448,0.00097154564,0.001083434,0.0006402334,0.000771032,0.0014611398,0.0022251871,0.0011489891,0.0054363147],"category_scores_gemma":[0.004384334,0.0007026306,0.00076648814,0.00083667325,0.001741399,0.00289433,0.002763431,0.002132073,0.0012378838],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003700678,0.00006022246,0.0003555208,0.00035472965,0.000078373996,0.00018093627,0.00029443763,0.22638293,0.0077347415,0.570928,0.0070359604,0.18622413],"study_design_scores_gemma":[0.00008770766,0.000090053,0.00015219454,0.00004603279,0.00003492418,0.00017850878,0.00004095858,0.5843449,0.0038356693,0.4002213,0.010942103,0.000025557682],"about_ca_topic_score_codex":0.0006486254,"about_ca_topic_score_gemma":0.00069200137,"teacher_disagreement_score":0.0054363147,"about_ca_system_score_codex":0.00073815166,"about_ca_system_score_gemma":0.000510088,"threshold_uncertainty_score":0.018186212},"labels":[],"label_agreement":null},{"id":"W2793208001","doi":"10.1142/s0218195917500066","title":"Competitive Online Routing on Delaunay Triangulations","year":2017,"lang":"en","type":"article","venue":"International Journal of Computational Geometry & Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Carleton University","funders":"","keywords":"Delaunay triangulation; Constrained Delaunay triangulation; Combinatorics; Bowyer–Watson algorithm; Mathematics; Pitteway triangulation; Competitive analysis; Chew's second algorithm; Discrete mathematics; Upper and lower bounds","score_opus":0.03124044391697462,"score_gpt":0.35422964422401154,"score_spread":0.3229892003070369,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2793208001","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0906415,0.0010226743,0.86593467,0.0011251821,0.00024187201,0.0004884532,0.0007600914,0.0022112064,0.03757435],"genre_scores_gemma":[0.48661235,0.0007049657,0.4921333,0.00042596407,0.00021452928,0.0006404142,0.0017152835,0.0005277835,0.017025324],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9975821,0.0005469437,0.00012425898,0.0004942287,0.00086126983,0.00039121066],"domain_scores_gemma":[0.99481577,0.0025624707,0.0004493186,0.0010215368,0.0007331467,0.0004177097],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012342029,0.0011721256,0.001587176,0.0011357995,0.0016417516,0.0021875915,0.0035811157,0.0019515696,0.012073909],"category_scores_gemma":[0.009645715,0.0007609447,0.000988087,0.0022000063,0.0010262306,0.004318512,0.0034927374,0.0013532072,0.0027034343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009004954,0.0003056236,0.0012680818,0.00050275173,0.00009621181,0.00052045047,0.00033332885,0.55083394,0.010213355,0.20621522,0.022043249,0.20676726],"study_design_scores_gemma":[0.000073302144,0.000106852116,0.00015640566,0.000017512733,0.000019425413,0.00017965084,0.00007882704,0.9203635,0.0022975437,0.06890201,0.0077821505,0.000022827782],"about_ca_topic_score_codex":0.0049896785,"about_ca_topic_score_gemma":0.0058800234,"teacher_disagreement_score":0.012073909,"about_ca_system_score_codex":0.0019720402,"about_ca_system_score_gemma":0.0014765166,"threshold_uncertainty_score":0.040391207},"labels":[],"label_agreement":null},{"id":"W2794549768","doi":"10.4230/lipics.opodis.2017.11","title":"Evacuating an Equilateral Triangle in the Face-to-Face Model","year":2018,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; University of Waterloo; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Concordia University","keywords":"Robot; Upper and lower bounds; Equilateral triangle; Face (sociological concept); Combinatorics; Computer science; Boundary (topology); Mathematics; Artificial intelligence; Geometry; Mathematical analysis","score_opus":0.052625107559147274,"score_gpt":0.33286018274123674,"score_spread":0.28023507518208945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2794549768","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07400103,0.00029384356,0.90078324,0.00072213623,0.00011757762,0.00012396829,0.00031182423,0.0005271527,0.02311923],"genre_scores_gemma":[0.65647995,0.00066405575,0.30467394,0.000453711,0.00007924294,0.00036246428,0.00094826415,0.00036191786,0.0359764],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993305,0.0001734175,0.000024096633,0.00011720316,0.00015595472,0.00019883079],"domain_scores_gemma":[0.999206,0.0003576134,0.00009553092,0.00012799382,0.00008461432,0.0001282832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004951313,0.00064269896,0.00097446615,0.00037282088,0.00084099034,0.000895774,0.002624984,0.00169274,0.011441566],"category_scores_gemma":[0.0026355241,0.0004351935,0.0011702753,0.00052992173,0.0012122788,0.001999219,0.0027583817,0.0017421775,0.002072472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020509209,0.000048199952,0.00034396187,0.000114720955,0.000015119535,0.00040643456,0.00018394367,0.91472346,0.003277767,0.06051034,0.0027402563,0.017430676],"study_design_scores_gemma":[0.00003136147,0.000042249714,0.000063794796,0.000011243635,0.000004081428,0.000082979124,0.00008072467,0.9630359,0.00085102854,0.03369044,0.002094163,0.000012012607],"about_ca_topic_score_codex":0.008393036,"about_ca_topic_score_gemma":0.006185736,"teacher_disagreement_score":0.011441566,"about_ca_system_score_codex":0.0011120617,"about_ca_system_score_gemma":0.0007533977,"threshold_uncertainty_score":0.038275838},"labels":[],"label_agreement":null},{"id":"W2796213503","doi":"10.22215/etd/2017-12063","title":"Foraging in the Presence of Obstacles","year":2017,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Foraging; Treasure; Computer science; Nesting (process); NetLogo; Bounded function; Simple (philosophy); Ant colony; Artificial intelligence; Algorithm; Ecology; Mathematics; Geography; Ant colony optimization algorithms; Engineering; Biology","score_opus":0.03627462314657589,"score_gpt":0.32604772841963553,"score_spread":0.28977310527305966,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2796213503","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50117296,0.00767536,0.44329458,0.0013038812,0.0002975072,0.00011894225,0.00010142118,0.0003453523,0.045690022],"genre_scores_gemma":[0.90401554,0.004941366,0.07999076,0.00013525087,0.000087671746,0.00009390667,0.00009758036,0.00006465823,0.010573113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997825,0.000060610608,0.000011562519,0.000051812258,0.00005072935,0.000042766376],"domain_scores_gemma":[0.9994216,0.00038094888,0.0000626469,0.00005263498,0.000048866565,0.00003331921],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003267213,0.00033418267,0.00067734206,0.00028404823,0.00048535867,0.0010905794,0.000485237,0.000759121,0.0008568929],"category_scores_gemma":[0.0021647832,0.00029733445,0.00057075726,0.00030568533,0.0007420803,0.001053066,0.0010681129,0.00057974627,0.00025891844],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014009402,0.000045074805,0.001649474,0.000405984,0.00009704297,0.00042748003,0.00036746296,0.81455016,0.0150416605,0.12394652,0.0018338364,0.041495208],"study_design_scores_gemma":[0.000032961038,0.0000851815,0.00097484083,0.000048033,0.00002651405,0.00021757606,0.0001583209,0.92742115,0.0020641966,0.06316169,0.0057845335,0.000024945966],"about_ca_topic_score_codex":0.001360757,"about_ca_topic_score_gemma":0.0006455074,"teacher_disagreement_score":0.001360757,"about_ca_system_score_codex":0.00040157005,"about_ca_system_score_gemma":0.00043014952,"threshold_uncertainty_score":0.0029135942},"labels":[],"label_agreement":null},{"id":"W2796790483","doi":"10.1007/s10878-009-9236-7","title":"The robot cleans up","year":2009,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Eulerian path; Enhanced Data Rates for GSM Evolution; Weighting; Theory of computation; Property (philosophy); Computer science; Graph; Robot; Combinatorics; Mathematics; Mathematical optimization; Algorithm; Artificial intelligence; Lagrangian; Physics; Applied mathematics","score_opus":0.011572052617344274,"score_gpt":0.25832733421325754,"score_spread":0.24675528159591326,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2796790483","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12704457,0.0020419639,0.5440989,0.02148742,0.0044741244,0.00031701053,0.0005658242,0.0068083806,0.29316175],"genre_scores_gemma":[0.64835113,0.0013235237,0.09605359,0.0032327126,0.00048566124,0.00017560287,0.0004791657,0.00088084914,0.24901773],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995584,0.0000657984,0.000009946908,0.00013280935,0.0001477636,0.000085358566],"domain_scores_gemma":[0.9995919,0.0000908186,0.000034355362,0.0001229677,0.00007136909,0.000088601155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031456,0.0007250644,0.00083411846,0.0006047004,0.0018891081,0.0020549851,0.0009914171,0.0020257132,0.026316984],"category_scores_gemma":[0.0017091248,0.00048091542,0.0010531192,0.00030308723,0.0019810947,0.0027170544,0.0027800472,0.0024383317,0.009360651],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011926567,0.00045618575,0.0028199079,0.000504785,0.0002631558,0.0031907074,0.001585591,0.052136842,0.11320769,0.40114865,0.08831032,0.33518356],"study_design_scores_gemma":[0.00017179508,0.0016711969,0.0039731083,0.00020832018,0.00020713503,0.0026451345,0.0030953756,0.19410394,0.061584774,0.30887744,0.42312974,0.00033209214],"about_ca_topic_score_codex":0.0022165214,"about_ca_topic_score_gemma":0.0016004309,"teacher_disagreement_score":0.026316984,"about_ca_system_score_codex":0.00038760784,"about_ca_system_score_gemma":0.0011165539,"threshold_uncertainty_score":0.08803904},"labels":[],"label_agreement":null},{"id":"W2799364841","doi":"10.1007/978-3-030-01325-7_14","title":"Symmetric Rendezvous with Advice: How to Rendezvous in a Disk","year":2018,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Ryerson University","keywords":"Rendezvous; Conjecture; Computer science; Energy (signal processing); Simple (philosophy); Point (geometry); Algorithm; Upper and lower bounds; Advice (programming); Line (geometry); Robot; Mathematics; Combinatorics; Geometry; Physics; Artificial intelligence; Mathematical analysis; Statistics","score_opus":0.01755097974014902,"score_gpt":0.27191666665615516,"score_spread":0.25436568691600614,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2799364841","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0988087,0.0012802272,0.82269984,0.0028427185,0.001069906,0.0003572714,0.0009668626,0.028767148,0.04320721],"genre_scores_gemma":[0.5183853,0.00044787265,0.44303596,0.00050895003,0.00013614079,0.00018892536,0.00088904996,0.005123363,0.031284474],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983714,0.00029063973,0.00011755995,0.0004013401,0.00049384043,0.00032528758],"domain_scores_gemma":[0.9960234,0.0010723163,0.00010399522,0.001984932,0.0005787524,0.00023661472],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011737305,0.0010845658,0.0015508462,0.00051758956,0.0018705308,0.002334443,0.0030462733,0.0022813168,0.02288846],"category_scores_gemma":[0.01005628,0.00082584127,0.00083983,0.0007366394,0.0017452668,0.005521158,0.0049075824,0.0023685272,0.0071278443],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031735918,0.00042111013,0.004018658,0.00089760055,0.00016225367,0.0010711919,0.0027420775,0.040204212,0.040116265,0.179733,0.096983545,0.6304764],"study_design_scores_gemma":[0.00053156714,0.0002611331,0.00095708465,0.00023813319,0.00018455143,0.000789637,0.0016848763,0.47058174,0.047723617,0.3866037,0.09027285,0.0001711085],"about_ca_topic_score_codex":0.0057926266,"about_ca_topic_score_gemma":0.008811292,"teacher_disagreement_score":0.02288846,"about_ca_system_score_codex":0.00070582924,"about_ca_system_score_gemma":0.0014150841,"threshold_uncertainty_score":0.0765695},"labels":[],"label_agreement":null},{"id":"W2802261039","doi":"10.1016/j.tcs.2018.04.022","title":"Approximation and complexity of multi-target graph search and the Canadian traveler problem","year":2018,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Graph; Computer science; Approximation algorithm; Theoretical computer science; Mathematics; Combinatorics; Mathematical optimization","score_opus":0.039379010213812085,"score_gpt":0.27466528492848,"score_spread":0.23528627471466795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802261039","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47023442,0.0070403805,0.41841778,0.017181434,0.0005344466,0.0006861132,0.0066994587,0.0016266502,0.077579364],"genre_scores_gemma":[0.8479118,0.001916782,0.12494641,0.00077246607,0.0002797547,0.00032052412,0.004221123,0.0005224761,0.019108804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9970299,0.0009875415,0.00008446668,0.00050238473,0.0005956589,0.0007998903],"domain_scores_gemma":[0.9839041,0.012849059,0.00063688576,0.00085700426,0.0007958742,0.00095714757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033099963,0.001971616,0.0034440134,0.0027306422,0.0026623849,0.004736077,0.0059650764,0.0045484235,0.015581176],"category_scores_gemma":[0.026904738,0.0010778697,0.0017732193,0.0060310923,0.003131175,0.00806679,0.0031536599,0.0042767767,0.00087145786],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010945839,0.00037090207,0.0031064788,0.00039013854,0.00012099086,0.00013269491,0.00031582528,0.8390086,0.0004312427,0.101321615,0.021719845,0.031987034],"study_design_scores_gemma":[0.000108321765,0.000036626974,0.00048084755,0.000028390183,0.00003822671,0.000043908633,0.00013486481,0.9326005,0.00015785107,0.06500015,0.0013506341,0.00001973113],"about_ca_topic_score_codex":0.19771467,"about_ca_topic_score_gemma":0.16757055,"teacher_disagreement_score":0.19771467,"about_ca_system_score_codex":0.012752414,"about_ca_system_score_gemma":0.012122128,"threshold_uncertainty_score":0.39312774},"labels":[],"label_agreement":null},{"id":"W2802275843","doi":"10.1109/access.2018.2827305","title":"On Invoking Transitivity to Enhance the &lt;italic&gt;Pursuit&lt;/italic&gt;-Oriented Object Migration Automata","year":2018,"lang":"en","type":"article","venue":"IEEE Access","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Transitive relation; Computer science; Theoretical computer science; Pairwise comparison; Automaton; Phenomenon; Markov chain; Transitive closure; Algorithm; Discrete mathematics; Combinatorics; Artificial intelligence; Mathematics; Machine learning","score_opus":0.02383690043812528,"score_gpt":0.3278256711858171,"score_spread":0.3039887707476918,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802275843","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020166287,0.0003022182,0.9624111,0.0007538721,0.00012610109,0.00011771121,0.000048465805,0.0012062539,0.014868077],"genre_scores_gemma":[0.4879765,0.00072463346,0.49620128,0.0010159132,0.00023014587,0.00043433747,0.00019885685,0.00059341255,0.012624883],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986104,0.00042769007,0.00012944252,0.00032261488,0.0003331705,0.00017664624],"domain_scores_gemma":[0.9948724,0.0029741237,0.0003073322,0.0010865314,0.0005409674,0.00021868193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020448724,0.0007826001,0.00057252066,0.00073585677,0.0008944277,0.0019018385,0.0014290198,0.0011136762,0.0038354609],"category_scores_gemma":[0.008464599,0.0005681799,0.0012882352,0.00057772326,0.0037776486,0.0047785044,0.0035970276,0.003265749,0.0010934481],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020597302,0.00009941111,0.0008697348,0.00019771619,0.00003024215,0.00021406022,0.00083824445,0.06728351,0.018290533,0.8320239,0.002098658,0.07784813],"study_design_scores_gemma":[0.000060680388,0.00029982574,0.00025831244,0.00007720435,0.000047286336,0.00026031357,0.00013340809,0.4171008,0.018612713,0.54027635,0.022816606,0.000056556673],"about_ca_topic_score_codex":0.0013946354,"about_ca_topic_score_gemma":0.0017598228,"teacher_disagreement_score":0.0038354609,"about_ca_system_score_codex":0.0013905268,"about_ca_system_score_gemma":0.0013001938,"threshold_uncertainty_score":0.012830913},"labels":[],"label_agreement":null},{"id":"W2802892321","doi":"10.1177/0278364918772024","title":"Active sensing for motion planning in uncertain environments via mutual information policies","year":2018,"lang":"en","type":"article","venue":"The International Journal of Robotics Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Scalability; Motion planning; A priori and a posteriori; Computer science; Graph; Path (computing); Mathematical optimization; Enhanced Data Rates for GSM Evolution; Upper and lower bounds; Artificial intelligence; Theoretical computer science; Mathematics","score_opus":0.10789083253299162,"score_gpt":0.4120741131170773,"score_spread":0.3041832805840857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2802892321","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011774045,0.00027793716,0.98504746,0.00026892853,0.00002345295,0.000042952346,0.000040098115,0.00021616662,0.0023089612],"genre_scores_gemma":[0.84568864,0.00042980872,0.15085591,0.00014942508,0.00007363434,0.00033623434,0.00012144349,0.00009585191,0.0022490225],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980965,0.00088342355,0.00008039686,0.00026821456,0.000478275,0.00019310646],"domain_scores_gemma":[0.9935874,0.0052371453,0.0005219688,0.0002233683,0.00027125765,0.00015881188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030005535,0.0014294016,0.0013844703,0.0010581495,0.0007304369,0.0014135998,0.0014667559,0.0013151536,0.0018664713],"category_scores_gemma":[0.008146703,0.0008179215,0.00086283224,0.001017374,0.0024770175,0.002316111,0.002337897,0.0018448557,0.00026217982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000064216234,0.000025771327,0.0001643567,0.000047562655,0.000021714344,0.00003699142,0.000066594526,0.9637637,0.00040369693,0.02646603,0.00035989695,0.008579505],"study_design_scores_gemma":[0.00000878651,0.000020970876,0.000032107062,0.0000063591056,0.0000036375736,0.00000732903,0.0000070658043,0.98236483,0.000234272,0.01705935,0.00025109065,0.0000042181223],"about_ca_topic_score_codex":0.0029284537,"about_ca_topic_score_gemma":0.0022877837,"teacher_disagreement_score":0.0030005535,"about_ca_system_score_codex":0.0019416192,"about_ca_system_score_gemma":0.0019087347,"threshold_uncertainty_score":0.015868664},"labels":[],"label_agreement":null},{"id":"W2803003248","doi":"10.1007/s12083-018-0656-y","title":"Connectivity preserving obstacle avoidance localized motion planning algorithms for mobile wireless sensor networks","year":2018,"lang":"en","type":"article","venue":"Peer-to-Peer Networking and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; Algorithm; Wireless sensor network; Motion planning; Probabilistic logic; Obstacle avoidance; Cellular network; Wireless network; Distributed algorithm; Wireless; Real-time computing; Distributed computing; Computer network; Mobile robot; Artificial intelligence; Telecommunications; Robot","score_opus":0.037207322528434277,"score_gpt":0.32187880180464234,"score_spread":0.28467147927620806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803003248","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036996145,0.0003378099,0.96063787,0.00014529424,0.000029796705,0.000043355943,0.000041656087,0.00026154338,0.0015064846],"genre_scores_gemma":[0.83223474,0.0003529649,0.16403034,0.000074281845,0.000037680336,0.0001901461,0.00014273127,0.00006927257,0.0028678556],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998487,0.00003320875,0.0000069727585,0.000030127647,0.00005773549,0.000023239116],"domain_scores_gemma":[0.99958664,0.00023436346,0.000064399756,0.00003406797,0.000057917485,0.000022644048],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030726197,0.00060253066,0.0005579612,0.0005569285,0.00047894486,0.00043488934,0.0011765418,0.00061221345,0.00078533846],"category_scores_gemma":[0.0016039,0.00042887757,0.0003233887,0.0007291617,0.00056325964,0.0008009578,0.0011361283,0.0006080522,0.00013996934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042044736,0.000021188936,0.0002760517,0.000028231296,0.000014427333,0.00002766013,0.00005548291,0.9560058,0.0015585511,0.004553314,0.00059157,0.03682567],"study_design_scores_gemma":[0.000007135733,0.000028793667,0.00009234091,0.0000027546957,0.000004229266,0.000010558409,0.000009963302,0.996369,0.00038328598,0.0028746696,0.00021446208,0.0000027063068],"about_ca_topic_score_codex":0.0049047796,"about_ca_topic_score_gemma":0.005143767,"teacher_disagreement_score":0.0049047796,"about_ca_system_score_codex":0.0004485,"about_ca_system_score_gemma":0.00069603365,"threshold_uncertainty_score":0.009752452},"labels":[],"label_agreement":null},{"id":"W2803580888","doi":"10.5687/sss.2009.1","title":"On the Differences Between Discretized and Continuous Stochastic Systems as Demonstrated by Learning Automata","year":2009,"lang":"en","type":"article","venue":"Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Discretization; Learning automata; Probabilistic automaton; Probabilistic logic; Computer science; Convergence (economics); Automaton; State space; Finite-state machine; Field (mathematics); Space (punctuation); Artificial intelligence; Probability distribution; Discretization of continuous features; Action (physics); Machine learning; Theoretical computer science; Mathematics; Algorithm; Discretization error; Statistics","score_opus":0.010349744463591498,"score_gpt":0.24501756319603366,"score_spread":0.23466781873244216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2803580888","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04180692,0.0012669361,0.94605285,0.0008455379,0.000114385075,0.000038489037,0.00008028554,0.00028114946,0.009513446],"genre_scores_gemma":[0.87508214,0.0011025089,0.12097278,0.00017555541,0.00013620344,0.00014419381,0.00009506102,0.000074627205,0.0022169796],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977894,0.0011009979,0.00012919927,0.00033310143,0.0005424324,0.00010493614],"domain_scores_gemma":[0.990613,0.0073191347,0.00042861106,0.00093655934,0.00048683232,0.00021573223],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019314325,0.0004560163,0.0006645952,0.0004919436,0.00043683941,0.002383983,0.0011780014,0.0012239009,0.0021943538],"category_scores_gemma":[0.014284673,0.0004358127,0.00063119654,0.0004734712,0.004093451,0.0033548018,0.0013107206,0.0019634585,0.00027647166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005692627,0.000029150724,0.0006312993,0.00009066401,0.000025989353,0.000069155,0.00026264568,0.35480124,0.002232252,0.6261641,0.0004175189,0.015219174],"study_design_scores_gemma":[0.000011418057,0.00003804731,0.00016975978,0.00002101224,0.0000048824068,0.000030882136,0.000023610371,0.76842594,0.00041214091,0.22962485,0.0012210063,0.000016427395],"about_ca_topic_score_codex":0.0019193268,"about_ca_topic_score_gemma":0.0011821019,"teacher_disagreement_score":0.002383983,"about_ca_system_score_codex":0.001344245,"about_ca_system_score_gemma":0.00080893113,"threshold_uncertainty_score":0.010214508},"labels":[],"label_agreement":null},{"id":"W2804176675","doi":"10.1007/978-3-319-92007-8_38","title":"The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions","year":2018,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hierarchy; Action (physics); Computer science; Operator (biology); Scheme (mathematics); Curse of dimensionality; Discretization; Artificial intelligence; Theoretical computer science; Mathematics; Mathematical optimization","score_opus":0.011367387272165116,"score_gpt":0.2856070731466235,"score_spread":0.27423968587445835,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2804176675","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006660016,0.00041206842,0.98489654,0.0001326299,0.000036845875,0.000020069334,0.0000393091,0.00041834087,0.007384156],"genre_scores_gemma":[0.51710147,0.0012464604,0.4606836,0.00016005531,0.0001866563,0.00023303683,0.00019004954,0.00021509797,0.019983556],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994061,0.00011657103,0.000032690958,0.00014723092,0.00023772124,0.000059814738],"domain_scores_gemma":[0.998835,0.00064580893,0.000065721695,0.00029263692,0.000113083224,0.000047704372],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007970056,0.0006020238,0.0008274107,0.00043391145,0.0004326579,0.0010878972,0.0012846006,0.0007439737,0.00510128],"category_scores_gemma":[0.003260315,0.00041601397,0.00063637795,0.00074945996,0.0014529887,0.0016619309,0.0022873343,0.0021409641,0.001116622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014363378,0.00004544754,0.00028091128,0.00023468028,0.000041361596,0.00008528219,0.0001388369,0.2764678,0.0075083985,0.32792392,0.0055076005,0.3816221],"study_design_scores_gemma":[0.000012501731,0.00004329902,0.00017582104,0.000014733717,0.0000072554926,0.0000417017,0.00000848202,0.87569773,0.0014043929,0.11981588,0.0027682106,0.000009957909],"about_ca_topic_score_codex":0.0024970272,"about_ca_topic_score_gemma":0.0019548824,"teacher_disagreement_score":0.00510128,"about_ca_system_score_codex":0.00066174817,"about_ca_system_score_gemma":0.0008563668,"threshold_uncertainty_score":0.017065525},"labels":[],"label_agreement":null},{"id":"W2805215296","doi":"10.1142/s0129054119500102","title":"Tight Bounds for Restricted Grid Scheduling","year":2019,"lang":"en","type":"article","venue":"International Journal of Foundations of Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Villum Fonden; Velux Fonden; Natur og Univers, Det Frie Forskningsråd","keywords":"Computer science; Grid; Scheduling (production processes); Parallel computing; Distributed computing; Mathematics; Mathematical optimization; Geometry","score_opus":0.021411712199889535,"score_gpt":0.32111725181519885,"score_spread":0.2997055396153093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805215296","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07636808,0.011234133,0.82505524,0.0055296044,0.0011317261,0.00033431052,0.001980914,0.0033886747,0.074977376],"genre_scores_gemma":[0.8041944,0.006445646,0.1677045,0.0017900518,0.000940519,0.0006342412,0.0023899449,0.0015976124,0.014303006],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99468756,0.0014462661,0.00018313674,0.00081234315,0.0014108958,0.0014598685],"domain_scores_gemma":[0.9775988,0.0155058205,0.0014057329,0.0029207894,0.0012856488,0.001283298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0054306174,0.002850582,0.0036221931,0.0025209505,0.0018788868,0.0051469845,0.004956706,0.0020009505,0.018671995],"category_scores_gemma":[0.034350876,0.0014001242,0.0015069391,0.006175623,0.002674803,0.008255447,0.004725942,0.0049178693,0.003004817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014263066,0.0004041402,0.001511651,0.0010564508,0.0001774381,0.0002402581,0.00028607098,0.6272854,0.0032518206,0.27187133,0.028710658,0.063778386],"study_design_scores_gemma":[0.00010681861,0.0001414755,0.0004654084,0.00011382868,0.00005824444,0.00010689147,0.00011535491,0.6834593,0.00074255216,0.30751368,0.0071456362,0.000030896063],"about_ca_topic_score_codex":0.00888878,"about_ca_topic_score_gemma":0.0071534286,"teacher_disagreement_score":0.018671995,"about_ca_system_score_codex":0.0048308196,"about_ca_system_score_gemma":0.0037488989,"threshold_uncertainty_score":0.062464},"labels":[],"label_agreement":null},{"id":"W2806794575","doi":"10.1109/syscon.2018.8369551","title":"Architecture for testing learning-based autonomous vehicle control design","year":2018,"lang":"en","type":"article","venue":"2018 Annual IEEE International Systems Conference (SysCon)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Controller (irrigation); Robot; Process (computing); Offline learning; Computer science; Control engineering; Mobile robot; Differential (mechanical device); Vehicle dynamics; Artificial intelligence; Control theory (sociology); Control (management); Engineering; Online learning; Automotive engineering","score_opus":0.06291224565056276,"score_gpt":0.2947151798646511,"score_spread":0.23180293421408837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806794575","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053423744,0.000090790214,0.94020283,0.00010899544,0.000034213663,0.00020558546,0.00003693337,0.0023288967,0.0035679739],"genre_scores_gemma":[0.84033626,0.00005431768,0.15731938,0.00006010848,0.000013384734,0.00034264952,0.00010037766,0.00009146719,0.0016819829],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989542,0.00026538107,0.000060201757,0.00018361016,0.0004497096,0.00008690028],"domain_scores_gemma":[0.9983834,0.0005422132,0.000134675,0.00036492496,0.0005196165,0.000055089073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009372007,0.0006615329,0.00043603795,0.0004112608,0.00031084247,0.0007756737,0.0017558174,0.0008154693,0.0020054204],"category_scores_gemma":[0.003197905,0.00031433936,0.0003938768,0.00016291185,0.0008987902,0.000751966,0.0008408465,0.0013391515,0.00039464465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000132662,0.00018733568,0.0020047983,0.00015558707,0.0000577733,0.00013663709,0.00013470565,0.85363555,0.03594428,0.013311559,0.0006360481,0.09366312],"study_design_scores_gemma":[0.000015299382,0.00016183064,0.00031572543,0.000011333063,0.000008747205,0.000037582762,0.000011776051,0.9821154,0.01269263,0.0034269562,0.0011962814,0.0000064755773],"about_ca_topic_score_codex":0.002496812,"about_ca_topic_score_gemma":0.0018584154,"teacher_disagreement_score":0.002496812,"about_ca_system_score_codex":0.0010111227,"about_ca_system_score_gemma":0.0009486552,"threshold_uncertainty_score":0.0073361993},"labels":[],"label_agreement":null},{"id":"W2807434009","doi":"10.3233/fi-2018-1684","title":"Deterministic Meeting of Sniffing Agents in the Plane","year":2018,"lang":"en","type":"article","venue":"Fundamenta Informaticae","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Sniffing; Plane (geometry); Computer science; Mathematics; Psychology; Geometry; Neuroscience","score_opus":0.05534727282622702,"score_gpt":0.31303479110933063,"score_spread":0.2576875182831036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807434009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.55440855,0.0007872969,0.4232028,0.0017975568,0.00014357486,0.00020436347,0.0011653588,0.0005573743,0.017733186],"genre_scores_gemma":[0.9725776,0.0002708391,0.01644699,0.00010665467,0.0000533266,0.00010943484,0.00057035,0.00004045677,0.009824257],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983063,0.0003590625,0.00009766191,0.00048755202,0.00026343256,0.00048586298],"domain_scores_gemma":[0.993006,0.0031678225,0.0018110324,0.00056448585,0.0005092228,0.00094141194],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015096967,0.0010957452,0.0014805003,0.0007288873,0.0010193426,0.0019362699,0.0033035837,0.002989294,0.0057495404],"category_scores_gemma":[0.0106648505,0.0011556261,0.0011519645,0.00071578915,0.0021265117,0.0027498193,0.0030810048,0.0014773196,0.0011561183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00121852,0.00010914719,0.0114962775,0.00023595316,0.00011066372,0.001447967,0.00068422535,0.8794523,0.005558176,0.08517536,0.0025993048,0.011912192],"study_design_scores_gemma":[0.00006234594,0.000117905984,0.0014132238,0.000017260336,0.000035464986,0.00016231395,0.00017219866,0.9852336,0.00068985106,0.011135145,0.0009200259,0.000040663053],"about_ca_topic_score_codex":0.016331024,"about_ca_topic_score_gemma":0.008909935,"teacher_disagreement_score":0.016331024,"about_ca_system_score_codex":0.0018265228,"about_ca_system_score_gemma":0.0008025989,"threshold_uncertainty_score":0.032471895},"labels":[],"label_agreement":null},{"id":"W2807933378","doi":"10.1007/s00224-019-09955-7","title":"Advice Complexity of Priority Algorithms","year":2019,"lang":"en","type":"article","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; University of Toronto","funders":"","keywords":"Advice (programming); Oracle; Computer science; Reduction (mathematics); Mathematical proof; Function (biology); Algorithm; Matching (statistics); Adversary; Greedy algorithm; Upper and lower bounds; Theoretical computer science; Mathematics; Programming language; Computer security","score_opus":0.03455034673156813,"score_gpt":0.27869131579602946,"score_spread":0.24414096906446134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2807933378","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25536928,0.0024789113,0.62234455,0.018124353,0.000736533,0.00027150474,0.0012387808,0.0015923108,0.09784368],"genre_scores_gemma":[0.8961949,0.0012110935,0.071883306,0.0013256873,0.0010727658,0.00029422695,0.0010657994,0.0006767888,0.026275434],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9910759,0.0029219564,0.00039675628,0.001085122,0.0030213767,0.0014989484],"domain_scores_gemma":[0.91389096,0.07249784,0.001983098,0.005207081,0.0038723575,0.0025487181],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005736406,0.0010619811,0.0024885244,0.0019397967,0.0023296038,0.008472776,0.004384428,0.003982607,0.023823114],"category_scores_gemma":[0.080116734,0.0011102326,0.0016112,0.0027904701,0.003750682,0.015470567,0.0035485143,0.0071131526,0.0020172622],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010028452,0.0002855203,0.0021415139,0.00034444794,0.00007844108,0.00010630956,0.00048820834,0.059057653,0.0014083039,0.8804688,0.013928461,0.04068965],"study_design_scores_gemma":[0.00012968341,0.000046146608,0.00046276988,0.000023254303,0.000041418603,0.00005532087,0.00005903361,0.21497172,0.00049283117,0.7822586,0.0014407742,0.000018432862],"about_ca_topic_score_codex":0.004591542,"about_ca_topic_score_gemma":0.0047110994,"teacher_disagreement_score":0.023823114,"about_ca_system_score_codex":0.0053356965,"about_ca_system_score_gemma":0.005805817,"threshold_uncertainty_score":0.07969624},"labels":[],"label_agreement":null},{"id":"W2808050500","doi":"10.1002/jgt.22546","title":"Bounds on the localization number","year":2020,"lang":"en","type":"preprint","venue":"Journal of Graph Theory","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Degeneracy (biology); Combinatorics; Mathematics; Upper and lower bounds; Conjecture; Chromatic scale; Graph; Discrete mathematics; Constant (computer programming); Hypercube; Computer science","score_opus":0.03417009690688372,"score_gpt":0.2831885300731406,"score_spread":0.24901843316625688,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808050500","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33540222,0.002599847,0.55802673,0.007521045,0.00020959042,0.00024442826,0.0011223751,0.0012727012,0.093601145],"genre_scores_gemma":[0.9503212,0.0007385451,0.03812309,0.00054856465,0.00010834309,0.00026104573,0.00032889057,0.00036857277,0.009201714],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967133,0.0008750785,0.000100728736,0.0008527628,0.0006756114,0.00078254956],"domain_scores_gemma":[0.9784566,0.01499017,0.0014553516,0.002531953,0.00091649324,0.0016494235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030683212,0.0016096176,0.001677098,0.001706378,0.0019388943,0.0030664515,0.0035891933,0.0024919834,0.01555383],"category_scores_gemma":[0.019524043,0.00080244103,0.0010236859,0.001502981,0.005791528,0.0098795565,0.005618446,0.0047886614,0.0017449379],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012348914,0.00032392776,0.005710731,0.0005603424,0.00012759787,0.0004040364,0.00079718523,0.2807363,0.02107675,0.63891226,0.009891098,0.040224902],"study_design_scores_gemma":[0.000119669705,0.00024181278,0.0017252442,0.00016369847,0.00005864803,0.00032441056,0.00022128799,0.51392454,0.00780438,0.46856213,0.0067622457,0.00009193412],"about_ca_topic_score_codex":0.0015818148,"about_ca_topic_score_gemma":0.0013514522,"teacher_disagreement_score":0.01555383,"about_ca_system_score_codex":0.003918129,"about_ca_system_score_gemma":0.0015538514,"threshold_uncertainty_score":0.05203277},"labels":[],"label_agreement":null},{"id":"W2811044723","doi":"10.1007/s00453-018-0461-2","title":"On the Separation and Equivalence of Paging Strategies and Other Online Algorithms","year":2018,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bijection; Paging; Algorithm; Computer science; Theory of computation; Online algorithm; Equivalence (formal languages); Competitive analysis; Set (abstract data type); Context (archaeology); Locality; Theoretical computer science; Mathematics; Discrete mathematics; Upper and lower bounds","score_opus":0.0400453913384496,"score_gpt":0.3232309033706767,"score_spread":0.28318551203222714,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2811044723","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04562306,0.002420341,0.9070158,0.0033857648,0.0004117364,0.00014627054,0.00024306144,0.00047563526,0.040278316],"genre_scores_gemma":[0.72934467,0.0033713214,0.23905922,0.0021235745,0.0014299995,0.0005135432,0.0007340991,0.0009943307,0.0224292],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9911971,0.0040753833,0.0004907565,0.0013294491,0.001867633,0.0010397828],"domain_scores_gemma":[0.9478814,0.04249027,0.0017353661,0.0050340053,0.0016563851,0.0012025448],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008168131,0.0017885758,0.00303192,0.0024372393,0.002152823,0.0057232147,0.005016626,0.004076202,0.0131184],"category_scores_gemma":[0.061214916,0.0013326203,0.0025173954,0.004441705,0.0069380533,0.022517594,0.0076485914,0.011670878,0.0015315303],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026982985,0.0002273006,0.0005190869,0.00015231103,0.000033375527,0.000048925318,0.00031119844,0.020297606,0.00044648637,0.92776334,0.0031686255,0.04676192],"study_design_scores_gemma":[0.000049540224,0.000052842475,0.0001922439,0.000035901077,0.000020071286,0.00004322257,0.000037965303,0.057923008,0.00029864814,0.9395232,0.0018098507,0.000013476354],"about_ca_topic_score_codex":0.0018137842,"about_ca_topic_score_gemma":0.0010686462,"teacher_disagreement_score":0.0131184,"about_ca_system_score_codex":0.0028751162,"about_ca_system_score_gemma":0.0032458447,"threshold_uncertainty_score":0.04388535},"labels":[],"label_agreement":null},{"id":"W2823384615","doi":"10.1007/s10878-018-0324-4","title":"Competitive analysis of randomized online strategies for the multi-agent k-Canadian Traveler Problem","year":2018,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Competitive analysis; Theory of computation; Randomized algorithm; Disjoint sets; Computer science; Graph; Online algorithm; Enhanced Data Rates for GSM Evolution; Node (physics); Combinatorics; Mathematics; Mathematical optimization; Theoretical computer science; Upper and lower bounds; Algorithm; Artificial intelligence","score_opus":0.025514663311642347,"score_gpt":0.2938431342376827,"score_spread":0.26832847092604034,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2823384615","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36504036,0.003450897,0.5348891,0.006134454,0.0004508779,0.001358356,0.0019123855,0.00087859004,0.085884996],"genre_scores_gemma":[0.9390463,0.0010766654,0.035267837,0.00060760044,0.00024031349,0.00052648014,0.00088324276,0.0002888441,0.022062678],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99611306,0.0016466936,0.00011230615,0.00045118327,0.0005709679,0.0011057783],"domain_scores_gemma":[0.97480243,0.019567486,0.0014609412,0.0007185003,0.0015401035,0.0019105077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0060886187,0.0029591531,0.0052935197,0.0027068253,0.0023912499,0.00451467,0.00789987,0.005112553,0.020312825],"category_scores_gemma":[0.028564706,0.0015160209,0.0019517925,0.0028682235,0.003354931,0.005467335,0.0033438588,0.004488035,0.0009940545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009363414,0.00054066256,0.0013352016,0.00038426014,0.00020145153,0.00017923332,0.00024553118,0.8115847,0.00059318694,0.16021013,0.010968384,0.0128208455],"study_design_scores_gemma":[0.000104508246,0.00009980486,0.00022486699,0.00001962448,0.000038515063,0.000023466158,0.00008673669,0.9700702,0.000095353695,0.028433815,0.0007778276,0.000025369047],"about_ca_topic_score_codex":0.07467113,"about_ca_topic_score_gemma":0.056572627,"teacher_disagreement_score":0.07467113,"about_ca_system_score_codex":0.008796894,"about_ca_system_score_gemma":0.010774841,"threshold_uncertainty_score":0.14847296},"labels":[],"label_agreement":null},{"id":"W28791922","doi":"10.1007/978-3-642-35261-4_17","title":"On the Advice Complexity of Buffer Management","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Advice (programming); Computer science; Buffer (optical fiber); Competitive analysis; Computational complexity theory; Online algorithm; Operations research; Mathematical optimization; Upper and lower bounds; Algorithm; Mathematics; Telecommunications","score_opus":0.043840296391982614,"score_gpt":0.2662340101763999,"score_spread":0.2223937137844173,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W28791922","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1068721,0.007890669,0.66159415,0.022764018,0.0009429859,0.0002517813,0.0014429672,0.0014641427,0.19677727],"genre_scores_gemma":[0.7499869,0.006685872,0.18167917,0.0020174487,0.002500248,0.00048754213,0.00143659,0.0014378873,0.05376828],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9944583,0.0014468238,0.00031290177,0.0006912401,0.0022195203,0.0008712933],"domain_scores_gemma":[0.95080787,0.0410784,0.0013948472,0.0038037475,0.0018693754,0.001045737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034664993,0.0012351067,0.001991828,0.0018046072,0.002497375,0.0066250386,0.003849405,0.003543923,0.026561337],"category_scores_gemma":[0.04880272,0.0014945506,0.0019000581,0.0036312772,0.004329226,0.017803188,0.0041571674,0.008479953,0.0022741258],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023851471,0.00011298099,0.0009325436,0.0003118455,0.000049344562,0.00015738436,0.00040884368,0.043877356,0.0010791095,0.8834908,0.01768314,0.05165818],"study_design_scores_gemma":[0.000034489687,0.000013800618,0.00024771053,0.000041998355,0.0000306275,0.00007631262,0.00006120125,0.104030676,0.0003701633,0.8916153,0.0034584748,0.00001926898],"about_ca_topic_score_codex":0.006211006,"about_ca_topic_score_gemma":0.005236727,"teacher_disagreement_score":0.026561337,"about_ca_system_score_codex":0.004593554,"about_ca_system_score_gemma":0.0036817312,"threshold_uncertainty_score":0.08885658},"labels":[],"label_agreement":null},{"id":"W2883365810","doi":"10.1007/s10878-018-0326-2","title":"Client assignment problems for latency minimization","year":2018,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fondation Pour La Conservation Du Saumon Atlantique","keywords":"Interactivity; Computer science; Latency (audio); Server; Approximation algorithm; Theory of computation; Computer network; Algorithm; Operating system","score_opus":0.02113870338034317,"score_gpt":0.2740284831865448,"score_spread":0.25288977980620164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2883365810","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033488348,0.0015661417,0.9336876,0.0023325197,0.00034152344,0.0004202351,0.0011077207,0.000781878,0.02627409],"genre_scores_gemma":[0.5005039,0.003607969,0.41418943,0.0007502658,0.0009886787,0.0013804093,0.0018202385,0.0015257365,0.07523347],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99832696,0.0006351348,0.000067624744,0.00026359485,0.00032054307,0.00038618236],"domain_scores_gemma":[0.99624383,0.0025325015,0.00022204506,0.00028498427,0.00035879808,0.00035781905],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002067251,0.0021954973,0.0023417561,0.0013616385,0.0012414403,0.0033254926,0.003866984,0.0027292804,0.02724522],"category_scores_gemma":[0.009532088,0.0010131656,0.001060462,0.0038728425,0.0010699686,0.0048497203,0.0020273207,0.0036385872,0.0026433028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043702623,0.0005235924,0.0008406341,0.00068620243,0.000120522986,0.00015629546,0.0002276036,0.6636581,0.0025989416,0.17726684,0.03704154,0.116442814],"study_design_scores_gemma":[0.000059888243,0.00010535943,0.00032865175,0.000052005165,0.00004978038,0.00009277388,0.0001245106,0.850799,0.0009897467,0.14147021,0.005905788,0.000022229535],"about_ca_topic_score_codex":0.0044107353,"about_ca_topic_score_gemma":0.0044174073,"teacher_disagreement_score":0.02724522,"about_ca_system_score_codex":0.0027147736,"about_ca_system_score_gemma":0.0030008128,"threshold_uncertainty_score":0.09114432},"labels":[],"label_agreement":null},{"id":"W2884716215","doi":"10.1016/j.tcs.2018.06.045","title":"On asynchronous rendezvous in general graphs","year":2018,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Rendezvous; Asynchronous communication; Traverse; Computer science; Adversary; Characterization (materials science); Time complexity; Theoretical computer science; Discrete mathematics; Mathematics; Combinatorics; Algorithm; Computer network; Computer security; Geography","score_opus":0.010886347146242769,"score_gpt":0.26764632849572767,"score_spread":0.2567599813494849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884716215","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38432494,0.0019873488,0.5423877,0.0028110484,0.00038750924,0.00018133273,0.0005554351,0.000735545,0.06662921],"genre_scores_gemma":[0.9410726,0.0012607636,0.030638728,0.0003047246,0.0002920971,0.00016955886,0.00037915312,0.0003754133,0.025506983],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99901175,0.0003322739,0.000036875583,0.00022751182,0.00016454306,0.00022696808],"domain_scores_gemma":[0.98973864,0.0074160513,0.00075150887,0.00092150096,0.0004711109,0.00070126896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012732168,0.0011298415,0.0017098042,0.0018298607,0.0021737486,0.0021663278,0.002602034,0.0015290035,0.013477307],"category_scores_gemma":[0.01233405,0.0006662199,0.00082705595,0.0020764463,0.0027753043,0.0060790004,0.0035367329,0.0022426313,0.0010490943],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00048125235,0.000062623316,0.0005664758,0.00021156057,0.00003952659,0.00021167824,0.00048334955,0.14566733,0.002133524,0.8306709,0.0049579577,0.014513824],"study_design_scores_gemma":[0.00008379756,0.000039718274,0.00022726636,0.000033728462,0.000030887288,0.000071364964,0.00019865994,0.3086896,0.0006805359,0.6875275,0.0023939165,0.000023009656],"about_ca_topic_score_codex":0.0042452724,"about_ca_topic_score_gemma":0.0045333356,"teacher_disagreement_score":0.013477307,"about_ca_system_score_codex":0.0016062403,"about_ca_system_score_gemma":0.0010074069,"threshold_uncertainty_score":0.045086026},"labels":[],"label_agreement":null},{"id":"W2884836385","doi":"10.1016/j.dam.2018.01.018","title":"The robot crawler graph process","year":2018,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Ryerson University","keywords":"Web crawler; Crawling; Robot; Graph; Mathematics; Random walk; Combinatorics; Theoretical computer science; Discrete mathematics; Computer science; Artificial intelligence; Statistics; World Wide Web","score_opus":0.017971986492906464,"score_gpt":0.2813735515502793,"score_spread":0.26340156505737283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2884836385","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12446008,0.0012482195,0.84386915,0.0043753176,0.000261805,0.00021097239,0.0012130553,0.00072850334,0.023632789],"genre_scores_gemma":[0.8486568,0.0019646282,0.06293102,0.0006375994,0.00031785964,0.0004093436,0.0012318747,0.00038912456,0.08346175],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930537,0.00021463635,0.000020287367,0.00024341788,0.00013021704,0.00008614121],"domain_scores_gemma":[0.9963198,0.0022311541,0.00045959465,0.00025797109,0.00039041316,0.0003410563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011286195,0.00094705226,0.00171185,0.0026345367,0.0008354469,0.0020983736,0.0024792368,0.004025836,0.011730794],"category_scores_gemma":[0.00743873,0.00071555324,0.0011475978,0.0015889027,0.0025059949,0.0037660347,0.002164773,0.0024098654,0.00180445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017855837,0.000076746626,0.0016480777,0.00025997614,0.000096567106,0.0004459711,0.00026003056,0.38273373,0.00243496,0.5804201,0.0075884555,0.023856958],"study_design_scores_gemma":[0.00003598718,0.000041440348,0.00060423114,0.000027072661,0.000027586566,0.000107562235,0.0000680249,0.8596253,0.00046784477,0.13649024,0.002465029,0.00003965085],"about_ca_topic_score_codex":0.008313364,"about_ca_topic_score_gemma":0.005910483,"teacher_disagreement_score":0.011730794,"about_ca_system_score_codex":0.0015474499,"about_ca_system_score_gemma":0.0012402649,"threshold_uncertainty_score":0.0392434},"labels":[],"label_agreement":null},{"id":"W2886502899","doi":"10.48550/arxiv.1808.01984","title":"Time-Dependent Shortest Path Queries Among Growing Discs","year":2018,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Shortest path problem; Combinatorics; Binary logarithm; Path (computing); Computation; Mathematics; Discrete mathematics; Algorithm; Computer science; Graph","score_opus":0.03763391399765716,"score_gpt":0.17436982583267074,"score_spread":0.13673591183501357,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886502899","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41662762,0.0012696753,0.5676048,0.0012421657,0.000181127,0.00033933137,0.002494803,0.0036729432,0.006567507],"genre_scores_gemma":[0.759753,0.00032888373,0.23246326,0.00015896735,0.00005771423,0.00017958746,0.003465763,0.00027557128,0.0033172667],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99863285,0.00020162547,0.00011345263,0.0004842116,0.00036585392,0.00020201755],"domain_scores_gemma":[0.99574834,0.002451168,0.00044987883,0.00074915873,0.00033341604,0.00026807826],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081110076,0.00091619365,0.0014471427,0.0008135108,0.0011233767,0.0015441388,0.0033143533,0.0015984457,0.0031602823],"category_scores_gemma":[0.009087845,0.00054643763,0.00092498603,0.0023964378,0.0008007075,0.003906365,0.0021530709,0.001319455,0.00076534296],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016363772,0.00024668165,0.0045406693,0.00060284435,0.00015072733,0.0006443839,0.00079907675,0.79667616,0.020088457,0.03802094,0.012847929,0.123745754],"study_design_scores_gemma":[0.00008083331,0.000121814875,0.00066259765,0.00001548184,0.000019012248,0.00019969628,0.00024180932,0.96067595,0.005931181,0.028890923,0.0031373773,0.000023282078],"about_ca_topic_score_codex":0.0061065787,"about_ca_topic_score_gemma":0.00624086,"teacher_disagreement_score":0.0061065787,"about_ca_system_score_codex":0.0015822464,"about_ca_system_score_gemma":0.0014561892,"threshold_uncertainty_score":0.012142062},"labels":[],"label_agreement":null},{"id":"W2886931138","doi":"10.1145/3379552","title":"An Experimental Study of Algorithms for Online Bipartite Matching","year":2020,"lang":"en","type":"preprint","venue":"ACM Journal of Experimental Algorithmics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of Toronto; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Greedy algorithm; Bipartite graph; Computer science; Matching (statistics); Algorithm; Preprocessor; Ranking (information retrieval); Online algorithm; Theoretical computer science; Machine learning; Artificial intelligence; Mathematics; Graph","score_opus":0.09766027536202379,"score_gpt":0.3921035343862945,"score_spread":0.2944432590242707,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886931138","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7083427,0.008524172,0.19483125,0.0058243084,0.0022083456,0.0024458824,0.011349304,0.015581801,0.05089239],"genre_scores_gemma":[0.79030144,0.0011015112,0.18650515,0.0010090189,0.00036410693,0.001271289,0.013895031,0.0013048991,0.004247545],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97150505,0.012933149,0.0027587821,0.003988071,0.0063994,0.00241554],"domain_scores_gemma":[0.8803639,0.074462555,0.005766916,0.028837847,0.008531949,0.0020369182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.017587014,0.002433979,0.0019654254,0.0029007252,0.002067728,0.0025660854,0.0053592203,0.0029710452,0.0078102737],"category_scores_gemma":[0.0748284,0.00081814174,0.001602333,0.00529354,0.002369121,0.0068390053,0.0031651845,0.0040668184,0.0022070957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010925724,0.01427413,0.017985463,0.0037632703,0.001154025,0.00045566526,0.0004419758,0.5092623,0.020480435,0.044781897,0.072992064,0.30348295],"study_design_scores_gemma":[0.0018007895,0.0036073227,0.00586882,0.00019643371,0.00023075023,0.0007557326,0.00051367225,0.9066765,0.026925426,0.035679776,0.017625624,0.00011912194],"about_ca_topic_score_codex":0.0030023968,"about_ca_topic_score_gemma":0.0034381612,"teacher_disagreement_score":0.017587014,"about_ca_system_score_codex":0.0041131997,"about_ca_system_score_gemma":0.0029115153,"threshold_uncertainty_score":0.09301019},"labels":[],"label_agreement":null},{"id":"W2888048527","doi":"10.1007/s00446-018-0339-1","title":"Distributed exploration of dynamic rings","year":2018,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Vedecká Grantová Agentúra MŠVVaŠ SR a SAV","keywords":"Computer science; A priori and a posteriori; Focus (optics); Theoretical computer science; Graph; Context (archaeology); Invariant (physics); Topology (electrical circuits); Distributed computing; Mathematics; Combinatorics; Geography","score_opus":0.025652479985556205,"score_gpt":0.28613440334195933,"score_spread":0.26048192335640313,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888048527","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25110447,0.0010530225,0.7323618,0.00072785286,0.00009891801,0.00007095971,0.000075593794,0.0003415589,0.014165806],"genre_scores_gemma":[0.9476522,0.00027889138,0.04452195,0.000052954445,0.00003857544,0.00007601842,0.000051026036,0.00006355994,0.007264754],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941623,0.00024452267,0.000017500253,0.00010421491,0.00010417725,0.000113434915],"domain_scores_gemma":[0.9976428,0.0015458114,0.00015295764,0.00029690945,0.00016878055,0.00019274275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012468303,0.00035919173,0.00116003,0.0005973892,0.0008981883,0.0013826533,0.0011511319,0.00082831987,0.00356863],"category_scores_gemma":[0.0054911203,0.00044843825,0.0005948634,0.0006931551,0.0012615775,0.0022581406,0.0024477795,0.0009025898,0.00025054338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051396526,0.00010031676,0.0009190438,0.00010393133,0.000057475914,0.00012296083,0.00018541672,0.79721355,0.0032912386,0.16500929,0.0015905001,0.0308923],"study_design_scores_gemma":[0.000031456955,0.00003918796,0.000078920944,0.00000539029,0.00000871827,0.00002794645,0.000030194788,0.9472394,0.00042811112,0.05131426,0.0007910903,0.0000052841324],"about_ca_topic_score_codex":0.0009925124,"about_ca_topic_score_gemma":0.0010286097,"teacher_disagreement_score":0.00356863,"about_ca_system_score_codex":0.0007070033,"about_ca_system_score_gemma":0.0008804943,"threshold_uncertainty_score":0.011938214},"labels":[],"label_agreement":null},{"id":"W2890631767","doi":"10.1109/icra.2018.8460726","title":"Re-Deployment Algorithms for Multiple Service Robots to Optimize Task Response","year":2018,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Robot; Task (project management); Computer science; Benchmarking; Service (business); Time horizon; Greedy algorithm; Software deployment; Set (abstract data type); Task analysis; Approximation algorithm; Quality of service; Algorithm; Real-time computing; Mathematical optimization; Distributed computing; Artificial intelligence; Engineering; Mathematics; Computer network","score_opus":0.05856606378913111,"score_gpt":0.32257279700317054,"score_spread":0.26400673321403945,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2890631767","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041367322,0.0007264828,0.9504695,0.0004934362,0.00013089036,0.00024407709,0.000105714455,0.0019545236,0.0045080176],"genre_scores_gemma":[0.51422876,0.00038694325,0.47844613,0.00021050184,0.00008088795,0.00046693586,0.00033804696,0.00043890637,0.005402841],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99915624,0.00020681266,0.00004447894,0.00019964081,0.00014748161,0.00024537134],"domain_scores_gemma":[0.9986671,0.00065884425,0.00018419446,0.00016227148,0.00019779961,0.00012987363],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001361883,0.0022198365,0.0015003699,0.0008631365,0.0007399159,0.0008352403,0.0020604942,0.00146948,0.0049348],"category_scores_gemma":[0.0038811658,0.00062255416,0.00079652196,0.0009499622,0.0006868119,0.0015007965,0.0013274628,0.0013441221,0.0011975083],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021122012,0.00012341421,0.0004898745,0.00010953787,0.000035331326,0.00006592991,0.000093476185,0.9202997,0.002971568,0.005879153,0.003863442,0.06585735],"study_design_scores_gemma":[0.000032280463,0.000048930156,0.0000881468,0.000005928739,0.000008239375,0.000021658256,0.000032707045,0.9956293,0.000655511,0.0026390871,0.0008331778,0.000005072802],"about_ca_topic_score_codex":0.005947905,"about_ca_topic_score_gemma":0.007806243,"teacher_disagreement_score":0.005947905,"about_ca_system_score_codex":0.0017054675,"about_ca_system_score_gemma":0.0021576262,"threshold_uncertainty_score":0.01650852},"labels":[],"label_agreement":null},{"id":"W2898662501","doi":"10.1007/978-3-030-01325-7_17","title":"Explorable Families of Graphs","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Theoretical computer science; Graph; Mathematics; Discrete mathematics; Combinatorics","score_opus":0.02724811559871579,"score_gpt":0.2538213882877647,"score_spread":0.2265732726890489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898662501","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14103003,0.0077675814,0.46075597,0.004169665,0.00040222483,0.00012134301,0.0019076974,0.0009747307,0.38287064],"genre_scores_gemma":[0.76005757,0.009021087,0.09703711,0.0007232754,0.00052909803,0.000385395,0.0025095523,0.0006840787,0.12905283],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99962354,0.00010972623,0.000015393198,0.00009934734,0.00010631592,0.00004568202],"domain_scores_gemma":[0.9986474,0.00081426563,0.00008736479,0.00023442319,0.00009964885,0.0001169391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039212606,0.00060921523,0.0004586457,0.001698914,0.0009222197,0.0017341427,0.00070999574,0.0006602502,0.011763067],"category_scores_gemma":[0.0024601852,0.00051957695,0.00077703793,0.0014790674,0.0013626784,0.0045680017,0.002051629,0.0019529429,0.0012168046],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000019127527,0.000006733657,0.000158529,0.000080150014,0.0000104305045,0.00008855764,0.00025445913,0.0026601125,0.00047994647,0.97125757,0.0050376756,0.019946702],"study_design_scores_gemma":[0.000004780602,0.0000069440566,0.00014457102,0.000037632195,0.0000069549587,0.00018566103,0.000081190556,0.0031919014,0.00022372024,0.97603524,0.020075822,0.0000055780833],"about_ca_topic_score_codex":0.0003624064,"about_ca_topic_score_gemma":0.0005123187,"teacher_disagreement_score":0.011763067,"about_ca_system_score_codex":0.0007276439,"about_ca_system_score_gemma":0.00032023384,"threshold_uncertainty_score":0.039351404},"labels":[],"label_agreement":null},{"id":"W2898707168","doi":"","title":"Decision Support for Search and Rescue Response Planning.","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Fonds de recherche du Québec – Nature et technologies; Université Laval","keywords":"Search and rescue; Disaster response; Computer science; Risk analysis (engineering); Business; Operations research; Engineering; Emergency management; Artificial intelligence; Political science","score_opus":0.07917101514853908,"score_gpt":0.3870047902663798,"score_spread":0.3078337751178407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2898707168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019202251,0.0035557314,0.8810787,0.007867064,0.0007915329,0.00045571057,0.0054925014,0.0022240877,0.0793325],"genre_scores_gemma":[0.5885591,0.0038547085,0.37926632,0.0008680898,0.00024566174,0.00050434115,0.0043826466,0.00025398083,0.022065239],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990557,0.00033496815,0.00006021735,0.00011998422,0.00032151848,0.00010752865],"domain_scores_gemma":[0.99775535,0.0012021642,0.00017629752,0.00019573736,0.0004980737,0.0001723779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014541245,0.0010859532,0.0007922065,0.00082125637,0.00095731765,0.0030024138,0.0015419378,0.0012503125,0.022926705],"category_scores_gemma":[0.0060140938,0.00036395056,0.00070215034,0.0011956465,0.0006281584,0.0017939311,0.0015176003,0.0015153115,0.0030658746],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018943659,0.00014193045,0.0017253588,0.00061297225,0.00007606319,0.00021967432,0.00015095397,0.5964829,0.0017856705,0.14253522,0.05004756,0.20603237],"study_design_scores_gemma":[0.000034269313,0.000045951834,0.00029107113,0.00010608815,0.000028372782,0.000054020555,0.00013085255,0.9021636,0.0007153146,0.05611479,0.040296145,0.000019494024],"about_ca_topic_score_codex":0.050606545,"about_ca_topic_score_gemma":0.052866418,"teacher_disagreement_score":0.050606545,"about_ca_system_score_codex":0.002944278,"about_ca_system_score_gemma":0.005588052,"threshold_uncertainty_score":0.100623965},"labels":[],"label_agreement":null},{"id":"W2899031087","doi":"10.1007/978-3-030-01325-7_20","title":"Broadcast with Energy-Exchanging Mobile Agents Distributed on a Tree","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Mobile agent; Distributed computing; Tree (set theory); Energy (signal processing); Computer network","score_opus":0.01843230181514837,"score_gpt":0.24691683147001994,"score_spread":0.22848452965487157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2899031087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09284144,0.0006235514,0.8940822,0.0005540055,0.00018634163,0.000083993466,0.00014724622,0.00062246673,0.010858686],"genre_scores_gemma":[0.8513148,0.00061738933,0.13308734,0.00011744366,0.00013729377,0.00009882187,0.00019710136,0.00011263705,0.014317279],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963737,0.000102886486,0.00002043678,0.00006965294,0.00010598151,0.000063821506],"domain_scores_gemma":[0.99894375,0.0006354803,0.000073157484,0.00014895576,0.00012723375,0.00007151768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006603291,0.00043299768,0.0009792784,0.0005099387,0.0007309936,0.0012371287,0.0012385655,0.0010704895,0.0025189607],"category_scores_gemma":[0.002622835,0.00039212365,0.00045700526,0.001142431,0.00059764285,0.0013672886,0.0012993625,0.0008790474,0.00059433404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013722517,0.00020880524,0.0010291663,0.0003244638,0.00015901541,0.00043064402,0.00044508852,0.74580514,0.026169749,0.11572999,0.0061474517,0.102178216],"study_design_scores_gemma":[0.00008859541,0.00009361199,0.00013706113,0.000013088339,0.00003555782,0.000087070184,0.000055287725,0.9663314,0.0026036694,0.027816974,0.0027258366,0.000011883191],"about_ca_topic_score_codex":0.0011999707,"about_ca_topic_score_gemma":0.0012449275,"teacher_disagreement_score":0.0025189607,"about_ca_system_score_codex":0.00058893283,"about_ca_system_score_gemma":0.00044785047,"threshold_uncertainty_score":0.008426726},"labels":[],"label_agreement":null},{"id":"W2901708208","doi":"10.48550/arxiv.1811.06420","title":"Latecomers Help to Meet: Deterministic Anonymous Gathering in the Plane","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Point (geometry); Plane (geometry); Anonymity; Computer science; Constant (computer programming); Adversary; Combinatorics; Algorithm; Mathematics; Computer security; Geometry","score_opus":0.08748571325406237,"score_gpt":0.20796471848795586,"score_spread":0.12047900523389349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901708208","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4302189,0.0002578885,0.54576343,0.0007164656,0.000052536772,0.00028728473,0.00051198795,0.0014829593,0.020708505],"genre_scores_gemma":[0.9049971,0.00018925883,0.086485885,0.00008659036,0.000016683463,0.00021425434,0.00050837116,0.000172297,0.007329553],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99813974,0.00051458995,0.0001093577,0.0004587896,0.00028981842,0.00048766457],"domain_scores_gemma":[0.9925338,0.0034803383,0.00097117905,0.0013598547,0.00074221403,0.0009126203],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014896486,0.0007519621,0.0007380969,0.00077971263,0.0024577992,0.0023240456,0.0017273535,0.0015494816,0.004933196],"category_scores_gemma":[0.010983565,0.0007237314,0.0013184249,0.00078232796,0.0033509936,0.0031247993,0.004058316,0.0013580971,0.0012228907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015321977,0.00021725807,0.010096927,0.0002972169,0.00016383601,0.0027126507,0.005706021,0.35693198,0.0094741015,0.5658686,0.0038975673,0.043101635],"study_design_scores_gemma":[0.0002068005,0.00040616852,0.00272409,0.00012500274,0.00014139562,0.00093498843,0.0027598816,0.56745654,0.013408046,0.39397392,0.017707113,0.00015597191],"about_ca_topic_score_codex":0.0045858333,"about_ca_topic_score_gemma":0.0037256833,"teacher_disagreement_score":0.004933196,"about_ca_system_score_codex":0.001638236,"about_ca_system_score_gemma":0.0011771444,"threshold_uncertainty_score":0.016503215},"labels":[],"label_agreement":null},{"id":"W2901887370","doi":"10.1007/978-3-030-04651-4_38","title":"On the Competitiveness of Memoryless Strategies for the k-Canadian Traveller Problem","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Traverse; Competitive analysis; Combinatorics; Generalization; Computer science; Graph; Shortest path problem; Path (computing); Asymptotically optimal algorithm; Node (physics); Randomized algorithm; Enhanced Data Rates for GSM Evolution; Mathematics; Discrete mathematics; Mathematical optimization; Algorithm; Artificial intelligence; Upper and lower bounds; Computer network","score_opus":0.03387326969170144,"score_gpt":0.26185795791360544,"score_spread":0.227984688221904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2901887370","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44202155,0.005349067,0.21161465,0.009979992,0.0007509615,0.0005814256,0.0025521005,0.0010031677,0.3261471],"genre_scores_gemma":[0.8988844,0.003502421,0.042160906,0.0010536835,0.0005610493,0.00055630854,0.0019390688,0.000762166,0.050579894],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99776256,0.0006734296,0.00008534737,0.00036585354,0.00035726646,0.00075548276],"domain_scores_gemma":[0.98482406,0.011144224,0.0007019363,0.0007421667,0.0007955281,0.0017921964],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025603632,0.00263529,0.0042749355,0.0021996745,0.0033870044,0.007402334,0.005286973,0.0041492274,0.03453679],"category_scores_gemma":[0.022526318,0.0009272705,0.0020351172,0.0040562963,0.004756692,0.008924196,0.004155938,0.006101222,0.0020114733],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009861543,0.00025951854,0.0010056414,0.00049096684,0.00011518107,0.00017058004,0.0005629134,0.11823372,0.0011539168,0.8240639,0.025538983,0.027418517],"study_design_scores_gemma":[0.00018707871,0.0001282929,0.00047408027,0.000105511026,0.000058144113,0.00008471697,0.00033903323,0.18618472,0.0003396214,0.8071673,0.004868205,0.000063422616],"about_ca_topic_score_codex":0.031826537,"about_ca_topic_score_gemma":0.022115048,"teacher_disagreement_score":0.03453679,"about_ca_system_score_codex":0.005622358,"about_ca_system_score_gemma":0.008166195,"threshold_uncertainty_score":0.11553705},"labels":[],"label_agreement":null},{"id":"W2905815131","doi":"10.1287/ijoc.2022.1168","title":"Dynamic Relaxations for Online Bipartite Matching","year":2022,"lang":"en","type":"article","venue":"INFORMS journal on computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Matching (statistics); Bipartite graph; Heuristic; Set (abstract data type); Variety (cybernetics); Revenue; Mathematical optimization; Online algorithm; Theoretical computer science; Operations research; Mathematics; Algorithm; Economics; Artificial intelligence","score_opus":0.02570428253769788,"score_gpt":0.30766459370802673,"score_spread":0.2819603111703288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2905815131","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017831735,0.0008281389,0.953716,0.0013304556,0.00017147527,0.00020601379,0.0006322458,0.0002526841,0.025031313],"genre_scores_gemma":[0.61305165,0.0021138552,0.36087793,0.0011342043,0.0005308649,0.0010732841,0.0015530809,0.00054414483,0.019121],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968129,0.0014821895,0.00012491128,0.00057421805,0.0005710356,0.0004347364],"domain_scores_gemma":[0.9887438,0.008720591,0.00076699746,0.0007387864,0.0005360953,0.00049382146],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042637014,0.0016228271,0.0016501687,0.001229318,0.000934151,0.0023889758,0.002528278,0.002049714,0.014393669],"category_scores_gemma":[0.021869298,0.0010830346,0.0018370269,0.0017196833,0.0019634117,0.003923446,0.002352258,0.0046920436,0.0015276143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017402376,0.00025368246,0.0007006492,0.00032619637,0.000069683454,0.00010868236,0.0001975132,0.6258556,0.001010996,0.3312829,0.008663485,0.031356614],"study_design_scores_gemma":[0.000046008856,0.00005692448,0.000175705,0.000054265063,0.000014623042,0.00005432332,0.000060319904,0.7590653,0.00029691856,0.23614658,0.00400894,0.000020149548],"about_ca_topic_score_codex":0.0027872268,"about_ca_topic_score_gemma":0.0021965548,"teacher_disagreement_score":0.014393669,"about_ca_system_score_codex":0.0030610322,"about_ca_system_score_gemma":0.0018700548,"threshold_uncertainty_score":0.048151553},"labels":[],"label_agreement":null},{"id":"W2908766116","doi":"10.1007/978-3-030-11072-7_14","title":"Group Search and Evacuation","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University; Université du Québec en Outaouais","funders":"","keywords":"Computer science; Robot; Domain (mathematical analysis); Mobile robot; Search and rescue; Set (abstract data type); Wireless; Point (geometry); Group (periodic table); Communication in small groups; Line (geometry); Search problem; Artificial intelligence; Distributed computing; Algorithm; Mathematics","score_opus":0.024865138374666428,"score_gpt":0.26685571997669444,"score_spread":0.24199058160202802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2908766116","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018856024,0.015936771,0.4643123,0.0041706837,0.0026632827,0.00014911398,0.00046265288,0.00040187547,0.49304724],"genre_scores_gemma":[0.4130451,0.011763883,0.0841646,0.0009083606,0.0012107473,0.0003989823,0.00069641974,0.0004164405,0.48739547],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998155,0.00007048897,0.000005279085,0.00003177841,0.000045289977,0.00003175254],"domain_scores_gemma":[0.99985886,0.00006737117,0.000014613149,0.000023100783,0.000017989674,0.00001795209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029001097,0.0008935155,0.0009055458,0.0006814922,0.0008661634,0.0014779156,0.0008139993,0.0014992574,0.024947014],"category_scores_gemma":[0.001298473,0.00027855154,0.0006954343,0.0013316757,0.0013437894,0.0016506936,0.0013868404,0.0017633833,0.0031477816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052489144,0.000027583521,0.00011360904,0.00014409379,0.000029958283,0.000058376503,0.00013029628,0.07677257,0.00045088507,0.82951635,0.033655897,0.059047885],"study_design_scores_gemma":[0.000024810968,0.000037252245,0.0001282534,0.000060776005,0.000014848546,0.000069048634,0.00011559678,0.07657451,0.00034942006,0.845775,0.076836996,0.000013477003],"about_ca_topic_score_codex":0.00177211,"about_ca_topic_score_gemma":0.0016119987,"teacher_disagreement_score":0.024947014,"about_ca_system_score_codex":0.00096519117,"about_ca_system_score_gemma":0.00065430335,"threshold_uncertainty_score":0.0834561},"labels":[],"label_agreement":null},{"id":"W2909463622","doi":"10.4095/216197","title":"Figure 53. Thickness maps of the M/S Assemblage","year":2004,"lang":"en","type":"report","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Assemblage (archaeology); Geology; Mathematics; Geography; Geometry; Archaeology","score_opus":0.04309197364259377,"score_gpt":0.298845811115932,"score_spread":0.25575383747333824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2909463622","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43209547,0.0004770647,0.09458659,0.001177532,0.00052507507,0.00036489233,0.033259988,0.012161392,0.42535207],"genre_scores_gemma":[0.87515,0.00037429517,0.05419811,0.00008246195,0.000055625467,0.00015616714,0.009493241,0.0015807499,0.0589093],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997832,0.000010822925,0.00000530945,0.000036949277,0.000108023174,0.000055670615],"domain_scores_gemma":[0.999624,0.00007354958,0.000034678575,0.000041306706,0.00017701014,0.000049473405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014520978,0.00084531185,0.00037333195,0.0027787308,0.00085053005,0.0009924808,0.00041894443,0.00059678283,0.09053438],"category_scores_gemma":[0.000980203,0.0004989514,0.0003809869,0.0016684692,0.00043877424,0.0007388291,0.00068933953,0.0007266084,0.007396328],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031125066,0.00042452925,0.044834234,0.00080896943,0.00018563031,0.002188187,0.0028843277,0.19119394,0.12367855,0.045724943,0.14992599,0.43503818],"study_design_scores_gemma":[0.00028810027,0.00043066952,0.39913395,0.0004158428,0.00021157415,0.001771809,0.004953982,0.23980983,0.07934657,0.01611904,0.25717402,0.00034463746],"about_ca_topic_score_codex":0.024031365,"about_ca_topic_score_gemma":0.019752799,"teacher_disagreement_score":0.09053438,"about_ca_system_score_codex":0.0007125248,"about_ca_system_score_gemma":0.00057161116,"threshold_uncertainty_score":0.3028677},"labels":[],"label_agreement":null},{"id":"W2910174849","doi":"10.1007/s10878-019-00378-1","title":"On the randomized online strategies for the k-Canadian traveler problem","year":2019,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Competitive analysis; Theory of computation; Combinatorics; Graph; Randomized algorithm; Computer science; Disjoint sets; Undirected graph; Node (physics); Online algorithm; Enhanced Data Rates for GSM Evolution; Discrete mathematics; Mathematics; Upper and lower bounds; Mathematical optimization; Algorithm; Artificial intelligence; Physics","score_opus":0.017103845037781597,"score_gpt":0.25547395398773054,"score_spread":0.23837010894994895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2910174849","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31995273,0.0050914646,0.5131422,0.012678383,0.00081161765,0.0022200237,0.00409735,0.0016921229,0.14031412],"genre_scores_gemma":[0.85389036,0.0020873249,0.105281,0.0014537391,0.00038248964,0.00092001155,0.0019745755,0.00051254866,0.033497833],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.996999,0.0013237237,0.000095376476,0.00041332666,0.00035806606,0.0008104801],"domain_scores_gemma":[0.98636407,0.010894162,0.00050715223,0.00062591094,0.000583224,0.001025552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037924214,0.0024850552,0.0048816307,0.0020774116,0.0026239455,0.0041982313,0.0059401374,0.005042648,0.020044299],"category_scores_gemma":[0.019644365,0.0012876838,0.0014982875,0.0038879025,0.003385181,0.0065738186,0.0034272254,0.0045611686,0.0013429392],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0021739446,0.0008663314,0.0013782018,0.0006180443,0.00024035323,0.00022178475,0.00041032865,0.6752768,0.0008659407,0.23471741,0.038754154,0.044476688],"study_design_scores_gemma":[0.00042769944,0.00017633908,0.00037811158,0.00006691589,0.00006515592,0.00005460713,0.00020275782,0.87593985,0.00025813546,0.119112134,0.003258385,0.00005994098],"about_ca_topic_score_codex":0.089285366,"about_ca_topic_score_gemma":0.086610585,"teacher_disagreement_score":0.089285366,"about_ca_system_score_codex":0.007975682,"about_ca_system_score_gemma":0.014356484,"threshold_uncertainty_score":0.17753136},"labels":[],"label_agreement":null},{"id":"W2912100673","doi":"","title":"Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":181,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Vision; Computer science; Library science; Operations research; Autonomous agent; Track (disk drive); Artificial intelligence; Engineering; Sociology","score_opus":0.04896267297995336,"score_gpt":0.27961300150657,"score_spread":0.23065032852661663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2912100673","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012727109,0.090782925,0.27113435,0.027127743,0.08431708,0.00091210403,0.0019532933,0.004696493,0.50634897],"genre_scores_gemma":[0.14872822,0.09014888,0.1429092,0.008298613,0.021697382,0.0014775555,0.010416698,0.0012463047,0.5750772],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980611,0.00051782595,0.00017754525,0.00032660153,0.0007557402,0.00016113532],"domain_scores_gemma":[0.99761957,0.00065180514,0.00014370678,0.00034313125,0.00088656857,0.00035527092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023702122,0.0012921921,0.0015750732,0.0010794249,0.0010945534,0.006706938,0.0020577544,0.002474156,0.0624421],"category_scores_gemma":[0.00531153,0.00038510916,0.00083271164,0.0009381817,0.0012666121,0.0032353236,0.0026287031,0.0027110996,0.025942845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021392926,0.00023801847,0.0011010624,0.00089321093,0.0001734689,0.0005246341,0.00043802813,0.0052627856,0.0033288023,0.05176752,0.5448789,0.39117965],"study_design_scores_gemma":[0.000017965956,0.000051170777,0.0005410977,0.00019563733,0.000044642842,0.00026374732,0.00016261419,0.0065882145,0.0006830026,0.013755725,0.97767067,0.000025554382],"about_ca_topic_score_codex":0.002326186,"about_ca_topic_score_gemma":0.0019137383,"teacher_disagreement_score":0.0624421,"about_ca_system_score_codex":0.0009960876,"about_ca_system_score_gemma":0.0030231304,"threshold_uncertainty_score":0.2088896},"labels":[],"label_agreement":null},{"id":"W2913788502","doi":"10.1109/cdc.2018.8619136","title":"A Patrolling Game for Adversaries with Limited Observation Time","year":2018,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Patrolling; Computer science; Game theory; Markov chain; Graph; Set (abstract data type); Markov process; Mathematical optimization; Computer security; Mathematics; Theoretical computer science; Mathematical economics; Machine learning","score_opus":0.026356897183370132,"score_gpt":0.2431447598914063,"score_spread":0.21678786270803616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913788502","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28497,0.00018710629,0.7069334,0.0007603402,0.000033453085,0.00023797301,0.00030062735,0.00030870066,0.0062684002],"genre_scores_gemma":[0.9362734,0.00011292598,0.058246244,0.000111460795,0.000019308858,0.00020113366,0.00018558747,0.000048040383,0.004801877],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989115,0.000413249,0.00004333008,0.00030715278,0.00014635875,0.00017846146],"domain_scores_gemma":[0.99473876,0.0039622495,0.0005370664,0.00026454663,0.00014088096,0.00035649806],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012785869,0.0013268415,0.0013389558,0.0005735754,0.0006575029,0.0010939837,0.0017127588,0.0021399832,0.0035350514],"category_scores_gemma":[0.0068912106,0.00059473806,0.000850855,0.0005230214,0.0019007175,0.0029589352,0.0016138732,0.002053214,0.00032206016],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024910076,0.000078067766,0.00079462305,0.0000552154,0.000045494682,0.00022190668,0.0000956178,0.9648142,0.0018508068,0.025968378,0.00035351745,0.005473125],"study_design_scores_gemma":[0.00003208661,0.0000603041,0.000120069904,0.0000037873028,0.000006159065,0.00002593583,0.000017587678,0.98754114,0.00026899524,0.011719994,0.00019734298,0.0000066821854],"about_ca_topic_score_codex":0.0049539357,"about_ca_topic_score_gemma":0.0035417597,"teacher_disagreement_score":0.0049539357,"about_ca_system_score_codex":0.0014090174,"about_ca_system_score_gemma":0.0012454648,"threshold_uncertainty_score":0.011825979},"labels":[],"label_agreement":null},{"id":"W2916405216","doi":"10.48550/arxiv.1902.08069","title":"With Great Speed Come Small Buffers: Space-Bandwidth Tradeoffs for Routing","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Combinatorics; Path (computing); Space (punctuation); Burstiness; Sigma; Omega; Network packet; Computer science; Queueing theory; Mathematics; Discrete mathematics; Algorithm; Computer network; Physics","score_opus":0.10956977049957722,"score_gpt":0.19532272471011947,"score_spread":0.08575295421054224,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2916405216","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24973097,0.002342621,0.7279228,0.0062221778,0.00020278354,0.00012724008,0.00036030935,0.0006935895,0.012397518],"genre_scores_gemma":[0.9127112,0.0010391389,0.08111626,0.00037770544,0.00017207449,0.0001243371,0.00011022612,0.00015323302,0.0041957567],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9980032,0.00084379624,0.00008190033,0.0003034742,0.00039623835,0.0003714143],"domain_scores_gemma":[0.9888467,0.008610198,0.00072820095,0.0009803778,0.00036581917,0.00046886515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035535134,0.0011260294,0.0011039281,0.0011584383,0.0011169927,0.0027682146,0.0019136319,0.001984709,0.0046949796],"category_scores_gemma":[0.01779192,0.0006709321,0.00060956716,0.0013515038,0.0021427546,0.009112547,0.0021983217,0.002005495,0.00042517713],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006313823,0.00019628955,0.000992197,0.00018003042,0.000072364346,0.00013596281,0.00022508828,0.722685,0.0058645853,0.2295461,0.003976012,0.035494965],"study_design_scores_gemma":[0.000039883198,0.000117550146,0.00017200656,0.000017363665,0.000025588033,0.00007914313,0.00005995623,0.88972336,0.001163012,0.10738484,0.0012020471,0.000015193204],"about_ca_topic_score_codex":0.0014833644,"about_ca_topic_score_gemma":0.0016296136,"teacher_disagreement_score":0.0046949796,"about_ca_system_score_codex":0.0019172599,"about_ca_system_score_gemma":0.0014186369,"threshold_uncertainty_score":0.018792987},"labels":[],"label_agreement":null},{"id":"W2918194691","doi":"","title":"Fault Tolerance of λ-Optimal Graphs.","year":2018,"lang":"en","type":"article","venue":"Ars Combinatoria","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Mathematics; Fault tolerance; Computer science; Distributed computing","score_opus":0.01390735851180608,"score_gpt":0.257362109362107,"score_spread":0.24345475085030094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2918194691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33122241,0.002182744,0.6144287,0.00284252,0.00033098934,0.00010473393,0.0007851376,0.0014070467,0.046695687],"genre_scores_gemma":[0.9312192,0.0006289006,0.057193354,0.00029623616,0.00009761437,0.000084041225,0.00047288995,0.00020727057,0.009800531],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992094,0.00022078944,0.00003985131,0.0001542875,0.00016625201,0.00020931235],"domain_scores_gemma":[0.99610245,0.0024140356,0.00045697793,0.00052046095,0.00026377288,0.00024235787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008715289,0.0005297162,0.0006859406,0.0009725879,0.0007081257,0.0013697069,0.0012636387,0.0009402372,0.006641257],"category_scores_gemma":[0.009518129,0.00033250664,0.00044676315,0.0011190701,0.0009940857,0.002297728,0.0012661592,0.0012725239,0.00076103135],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00049393304,0.00018792255,0.0022344603,0.00035972556,0.00007379733,0.00016947968,0.00021734947,0.4900825,0.0045907847,0.35380664,0.015582204,0.13220114],"study_design_scores_gemma":[0.000041910498,0.00008073723,0.0005572256,0.00006096302,0.000022201046,0.00011979325,0.00013424027,0.39742234,0.00350162,0.593688,0.004355645,0.000015211843],"about_ca_topic_score_codex":0.0019172161,"about_ca_topic_score_gemma":0.0017879443,"teacher_disagreement_score":0.006641257,"about_ca_system_score_codex":0.0015692523,"about_ca_system_score_gemma":0.00088359165,"threshold_uncertainty_score":0.022217274},"labels":[],"label_agreement":null},{"id":"W2919974563","doi":"10.1007/s10878-007-9126-9","title":"Priority algorithms for the subset-sum problem","year":2008,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Theory of computation; Algorithm; Computer science; Subset sum problem; Mathematics; Combinatorics; Discrete mathematics; Knapsack problem","score_opus":0.0313018334077141,"score_gpt":0.27724368333323646,"score_spread":0.24594184992552237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919974563","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01835753,0.001485539,0.96711206,0.0009497856,0.0003600905,0.00013755423,0.00014930061,0.0005002397,0.010947851],"genre_scores_gemma":[0.35288605,0.0030198793,0.6201304,0.00075938046,0.0011136152,0.00039886005,0.0007453265,0.00070050574,0.020246062],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99799865,0.0007626549,0.00010379957,0.00027163076,0.00054997543,0.0003133525],"domain_scores_gemma":[0.99142224,0.0059450953,0.00036596155,0.0009075438,0.0008042172,0.0005549117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040310053,0.0013404231,0.0027041656,0.0013506493,0.0015592596,0.00364882,0.003401636,0.0015257209,0.01012761],"category_scores_gemma":[0.014024104,0.0007977589,0.0011794217,0.0024816499,0.0010868172,0.005751266,0.002551081,0.0039725206,0.0020690153],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011332829,0.00064343686,0.0007879776,0.0006582321,0.00015104156,0.000085436935,0.00037779287,0.14978568,0.0027299945,0.5032178,0.029065242,0.31136402],"study_design_scores_gemma":[0.00025785345,0.00026856762,0.00019718999,0.000045088203,0.000069494294,0.000118431104,0.000097061275,0.44472024,0.0012557578,0.54536563,0.007575161,0.000029509396],"about_ca_topic_score_codex":0.0017723588,"about_ca_topic_score_gemma":0.0025559003,"teacher_disagreement_score":0.01012761,"about_ca_system_score_codex":0.0017044832,"about_ca_system_score_gemma":0.0024098344,"threshold_uncertainty_score":0.033880234},"labels":[],"label_agreement":null},{"id":"W2922802510","doi":"10.22215/etd/2018-12842","title":"Novel Solutions and Applications of the Object Partitioning Problem","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Benchmark (surveying); Computer science; Block (permutation group theory); Theoretical computer science; Object (grammar); Big data; Process (computing); Automaton; Cellular automaton; Distributed computing; Data mining; Algorithm; Artificial intelligence; Programming language; Mathematics; Geography; Combinatorics","score_opus":0.023386249619743005,"score_gpt":0.2739348956252917,"score_spread":0.2505486460055487,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2922802510","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033631105,0.0045909113,0.9297542,0.0023621104,0.00043067758,0.00010573894,0.00013858844,0.00022988077,0.028756773],"genre_scores_gemma":[0.422839,0.0064642862,0.54698175,0.00071399997,0.00075387605,0.00038042516,0.0006332014,0.00024542882,0.020988096],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993032,0.00022713435,0.000044656063,0.00018209155,0.00016160196,0.00008124748],"domain_scores_gemma":[0.9988695,0.00073131925,0.00009476506,0.00011778562,0.00012429447,0.00006227565],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009514825,0.00081025256,0.000676437,0.00055363023,0.00085992017,0.0015823292,0.0011473617,0.0016620418,0.0047709728],"category_scores_gemma":[0.0043497025,0.00038427414,0.00092934776,0.00088390236,0.0011105711,0.002170461,0.0020625433,0.001864895,0.00061511825],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000085726504,0.000120791636,0.00079377147,0.0005128785,0.0000715875,0.00022397148,0.00033225608,0.27174377,0.0031844988,0.5809731,0.008781491,0.1331761],"study_design_scores_gemma":[0.000033933764,0.0000678998,0.00023938483,0.00008449719,0.000027062302,0.00019025563,0.00015334472,0.54538953,0.0014556136,0.42738807,0.024951164,0.000019253068],"about_ca_topic_score_codex":0.0010547136,"about_ca_topic_score_gemma":0.001151251,"teacher_disagreement_score":0.0047709728,"about_ca_system_score_codex":0.0008040116,"about_ca_system_score_gemma":0.00086025905,"threshold_uncertainty_score":0.015960455},"labels":[],"label_agreement":null},{"id":"W2923289556","doi":"","title":"A new dog learns old tricks: RL finds classic optimization algorithms","year":2019,"lang":"en","type":"article","venue":"International Conference on Learning Representations","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Optimization algorithm; Algorithm; Mathematical optimization; Mathematics","score_opus":0.04493808541385731,"score_gpt":0.3381104561314346,"score_spread":0.2931723707175773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2923289556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048512407,0.0014246234,0.9331961,0.0021596164,0.00048630295,0.000083258055,0.000082665225,0.0016756544,0.012379462],"genre_scores_gemma":[0.662826,0.0006090869,0.31544378,0.0010921197,0.000483449,0.00018805522,0.00016412046,0.00058036787,0.018613094],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993144,0.00023023882,0.000041867068,0.0002089211,0.0001412006,0.00006338714],"domain_scores_gemma":[0.99745053,0.0014461104,0.00015224771,0.00057089765,0.0002581336,0.00012209752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002395501,0.0012072639,0.0016233635,0.00088584755,0.0005813155,0.0017341807,0.0020747248,0.0036118787,0.0067179725],"category_scores_gemma":[0.010002784,0.0008027235,0.0007612329,0.0006584379,0.0024347014,0.0048299255,0.0024503036,0.0026872824,0.0013833308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045876368,0.00028233117,0.0025787638,0.00039829206,0.00028165602,0.00018508156,0.00027369094,0.47095832,0.004040535,0.11025961,0.014289633,0.3959934],"study_design_scores_gemma":[0.00006663352,0.00009826341,0.00015726291,0.00003513219,0.000032453936,0.00008162545,0.000028108188,0.93972915,0.0008650038,0.056401905,0.0024892362,0.000015265754],"about_ca_topic_score_codex":0.0015183375,"about_ca_topic_score_gemma":0.0016723091,"teacher_disagreement_score":0.0067179725,"about_ca_system_score_codex":0.0007839406,"about_ca_system_score_gemma":0.0010029433,"threshold_uncertainty_score":0.022473872},"labels":[],"label_agreement":null},{"id":"W2924103313","doi":"10.1109/tnnls.2019.2900639","title":"A Conclusive Analysis of the Finite-Time Behavior of the Discretized Pursuit Learning Automaton","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks and Learning Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Monotonic function; Discretization; Markov chain; Automaton; Property (philosophy); Convergence (economics); Combinatorial analysis; Computer science; Finite-state machine; Asymptotic analysis; Monotone polygon; Mathematical economics; Dilemma; Mathematics; Applied mathematics; Theoretical computer science; Algorithm; Combinatorics; Machine learning; Epistemology; Mathematical analysis; Economics; Philosophy","score_opus":0.007687722662617119,"score_gpt":0.22373970002921673,"score_spread":0.21605197736659962,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2924103313","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.104434036,0.00072221766,0.8791142,0.0012140003,0.000091667614,0.000047271344,0.00015873794,0.0003418202,0.013875999],"genre_scores_gemma":[0.94726497,0.0003297347,0.04786563,0.00017579604,0.00003858612,0.00009096474,0.00011889115,0.000058982372,0.004056383],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99953413,0.00010133329,0.00002372811,0.0001233263,0.00015545617,0.00006203371],"domain_scores_gemma":[0.9943797,0.004075908,0.00038203035,0.00039407652,0.0005649221,0.00020326434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000827015,0.00031521474,0.00056757155,0.0004136257,0.00050309097,0.00089208415,0.0007474892,0.0008167128,0.004550499],"category_scores_gemma":[0.010908042,0.00020327498,0.0006628367,0.00025848852,0.0017449005,0.0014104217,0.0009356051,0.0022770478,0.00037933537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012216967,0.000047934453,0.0027222617,0.00034388056,0.00005485009,0.00028713557,0.00053569046,0.36741495,0.018064436,0.5818541,0.0014714535,0.027081145],"study_design_scores_gemma":[0.0000054278403,0.000050881783,0.00040683383,0.00003261531,0.000008845428,0.00006588053,0.00004487138,0.91021943,0.0015770713,0.08672352,0.0008497363,0.000014765153],"about_ca_topic_score_codex":0.0020515518,"about_ca_topic_score_gemma":0.0012714784,"teacher_disagreement_score":0.004550499,"about_ca_system_score_codex":0.0011204327,"about_ca_system_score_gemma":0.0010602575,"threshold_uncertainty_score":0.015222907},"labels":[],"label_agreement":null},{"id":"W2927658665","doi":"10.1007/11970125_10","title":"A Randomized Algorithm for Online Unit Clustering","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Computer science; Online algorithm; Partition (number theory); Cluster analysis; Randomized algorithm; Upper and lower bounds; Extension (predicate logic); Algorithm; Set (abstract data type); Partition problem; Combinatorics; Mathematics; Artificial intelligence","score_opus":0.050693750502957165,"score_gpt":0.31263577829739636,"score_spread":0.2619420277944392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2927658665","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00803305,0.00031173357,0.98163027,0.00046564947,0.00023520699,0.00036454908,0.00038361823,0.0035622744,0.005013724],"genre_scores_gemma":[0.06960627,0.00017124818,0.91857535,0.00031629505,0.00017535704,0.00083905814,0.0011199911,0.0006415389,0.008554957],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9966016,0.0010416317,0.00018750971,0.00089480786,0.00079629815,0.00047812646],"domain_scores_gemma":[0.9942227,0.0027307675,0.00030723464,0.001628246,0.00067846105,0.00043265548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028844732,0.0022845578,0.004184288,0.0021008933,0.0027126535,0.0026711673,0.009429392,0.0041281907,0.019919528],"category_scores_gemma":[0.011148502,0.0016299022,0.0023140053,0.004961993,0.0018631908,0.005288242,0.006267627,0.0038040045,0.0066353744],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017810772,0.00088259985,0.0006524802,0.00048274745,0.00018260506,0.000104455634,0.00024024166,0.29553425,0.005276692,0.08461415,0.05337032,0.5568785],"study_design_scores_gemma":[0.00036864728,0.00015485684,0.00018658205,0.000026485304,0.00004378711,0.000084138104,0.000059367536,0.93702316,0.0017966889,0.055966225,0.0042515597,0.00003853571],"about_ca_topic_score_codex":0.0068755974,"about_ca_topic_score_gemma":0.0094039375,"teacher_disagreement_score":0.019919528,"about_ca_system_score_codex":0.0037121768,"about_ca_system_score_gemma":0.0050793886,"threshold_uncertainty_score":0.0666374},"labels":[],"label_agreement":null},{"id":"W2931307493","doi":"10.1007/s00453-024-01207-6","title":"Exploration of High-Dimensional Grids by Finite State Machines","year":2024,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"State (computer science); Computer science; Distributed computing; Algorithm","score_opus":0.015531657022182508,"score_gpt":0.25657313443856766,"score_spread":0.24104147741638515,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2931307493","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2193323,0.000583738,0.7693055,0.00079128565,0.00008369786,0.00007334466,0.00023055743,0.0006337153,0.008965953],"genre_scores_gemma":[0.87182564,0.0002542928,0.124898285,0.00009640505,0.00002976736,0.00016304023,0.00025010336,0.00010965363,0.0023728593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995664,0.00021267394,0.000023809824,0.00006999318,0.00007208316,0.00005507451],"domain_scores_gemma":[0.9950045,0.0042989454,0.00017039968,0.00025394757,0.00013456271,0.00013768903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092674064,0.0005458817,0.0010770813,0.0008056981,0.00082012196,0.0015983528,0.0013723321,0.0012732695,0.00395229],"category_scores_gemma":[0.0059318366,0.0007609874,0.001061842,0.00078438595,0.0022385386,0.0023412805,0.0023423666,0.0014856743,0.00034820684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010872259,0.0000378205,0.00064526155,0.00006653143,0.000026395463,0.00006663321,0.00008687767,0.9540993,0.0007003536,0.035105605,0.00050251844,0.008553983],"study_design_scores_gemma":[0.000012817186,0.000011137251,0.000034763925,0.000005949165,0.000002184678,0.000004826794,0.000013506672,0.97239155,0.00013845481,0.027190937,0.00019134313,0.0000024824108],"about_ca_topic_score_codex":0.003578726,"about_ca_topic_score_gemma":0.004364835,"teacher_disagreement_score":0.00395229,"about_ca_system_score_codex":0.0008949733,"about_ca_system_score_gemma":0.0008131895,"threshold_uncertainty_score":0.013221741},"labels":[],"label_agreement":null},{"id":"W2932187539","doi":"10.1109/irc.2019.00051","title":"Identifying Hazardous Shapes in the Plane","year":2019,"lang":"en","type":"article","venue":"2019 Third IEEE International Conference on Robotic Computing (IRC)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Computer science; Mobile robot; Artificial intelligence; A priori and a posteriori; Regular polygon; Hazardous waste; Line (geometry); Set (abstract data type); Combinatorics; Algorithm; Mathematics; Engineering; Geometry; Programming language","score_opus":0.07119261139089722,"score_gpt":0.3251178967372028,"score_spread":0.2539252853463056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2932187539","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11074983,0.0004767372,0.88246924,0.00039822512,0.000043319473,0.00018590163,0.00048961485,0.001312971,0.0038742234],"genre_scores_gemma":[0.4048821,0.000691549,0.588032,0.00013591575,0.000051820436,0.00013096831,0.0021227887,0.00029052186,0.003662235],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99888676,0.00017144738,0.00005175769,0.00041880494,0.0003124918,0.00015870873],"domain_scores_gemma":[0.9981153,0.00085773476,0.00032420884,0.0003272725,0.00025589566,0.000119566095],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074391946,0.0011510229,0.0015125581,0.0018451649,0.0010404711,0.0021864553,0.0020321405,0.0018909969,0.0022846567],"category_scores_gemma":[0.0050509106,0.0010797991,0.0012668546,0.0017874135,0.0013873026,0.0030522442,0.002914191,0.0013543378,0.0017196515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084899104,0.00015884894,0.01611014,0.0003643489,0.00012765599,0.0011354544,0.001026602,0.5999029,0.016528072,0.028874697,0.0049471534,0.32997522],"study_design_scores_gemma":[0.000029109913,0.00010815985,0.0021614535,0.00005358357,0.00003690304,0.0006358908,0.00073810644,0.9519449,0.010752519,0.026860697,0.006624865,0.00005375785],"about_ca_topic_score_codex":0.0057070088,"about_ca_topic_score_gemma":0.004902127,"teacher_disagreement_score":0.0057070088,"about_ca_system_score_codex":0.00064829044,"about_ca_system_score_gemma":0.0013399101,"threshold_uncertainty_score":0.011347532},"labels":[],"label_agreement":null},{"id":"W2933135745","doi":"10.1007/s10044-019-00817-z","title":"On enhancing the deadlock-preventing object migration automaton using the pursuit paradigm","year":2019,"lang":"en","type":"article","venue":"Pattern Analysis and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Deadlock; Computer science; Cellular automaton; Automaton; Object (grammar); Property (philosophy); Field (mathematics); Distributed computing; Theoretical computer science; Learning automata; Artificial intelligence; State (computer science); Algorithm; Mathematics","score_opus":0.014976528653831232,"score_gpt":0.27659150646443487,"score_spread":0.2616149778106036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2933135745","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05831023,0.00016947201,0.93676984,0.00021426803,0.000051947503,0.00003657195,0.000028100167,0.0009914458,0.0034281365],"genre_scores_gemma":[0.69665056,0.00029571904,0.2984682,0.00016534286,0.000026445397,0.000087609835,0.00008959631,0.00017115018,0.0040454227],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995633,0.00011019422,0.000029913857,0.00008331535,0.00013639273,0.00007682254],"domain_scores_gemma":[0.9990829,0.00042918514,0.00007236562,0.00019771955,0.00015934388,0.00005844044],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072435103,0.00039954204,0.0005465559,0.00040531618,0.000534488,0.00085447915,0.0011981301,0.0006984683,0.0018117141],"category_scores_gemma":[0.002002687,0.0002177538,0.00065300503,0.0004319046,0.0008640486,0.0015150453,0.0015550775,0.0009854791,0.00037065663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006031217,0.00031055574,0.0021442566,0.0003013948,0.00007213477,0.0001954527,0.00030054632,0.51359403,0.06794382,0.19696337,0.0017987686,0.21577264],"study_design_scores_gemma":[0.00001486262,0.00014483804,0.0001157964,0.000009161827,0.000019337353,0.00005716119,0.000027478574,0.95429575,0.009822426,0.034127213,0.0013559349,0.00001008854],"about_ca_topic_score_codex":0.0015899955,"about_ca_topic_score_gemma":0.0020460035,"teacher_disagreement_score":0.0018117141,"about_ca_system_score_codex":0.00042642324,"about_ca_system_score_gemma":0.0010109729,"threshold_uncertainty_score":0.006060779},"labels":[],"label_agreement":null},{"id":"W2937446061","doi":"10.48550/arxiv.1904.04374","title":"Collision-aware Task Assignment for Multi-Robot Systems","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Bidding; Robot; Collision avoidance; Task (project management); Collision; Computer science; Function (biology); Reduction (mathematics); Binary number; Mathematical optimization; Distributed computing; Artificial intelligence; Engineering; Mathematics; Computer security","score_opus":0.16850559888178573,"score_gpt":0.23224778061514362,"score_spread":0.06374218173335788,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937446061","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022456948,0.00033241403,0.97470903,0.00020540696,0.000049519225,0.00005463691,0.00003255622,0.00014765224,0.0020118696],"genre_scores_gemma":[0.81627107,0.00027488702,0.17976892,0.00008684114,0.00006242936,0.000196685,0.0000870872,0.00008200934,0.003170107],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991615,0.00029344193,0.000032083717,0.0001529397,0.00020557335,0.00015449358],"domain_scores_gemma":[0.9991517,0.00041482775,0.00013808686,0.0000919144,0.000115188996,0.000088344415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010112119,0.00081657583,0.0011197509,0.00048932136,0.00088704395,0.00091690186,0.0015215867,0.00085895095,0.0020776074],"category_scores_gemma":[0.0022990361,0.0005533891,0.000565429,0.0009111879,0.0007892287,0.0012658252,0.0016994649,0.0011578833,0.00028784582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041918145,0.00004205244,0.00020377232,0.000045468358,0.000015679792,0.00004806347,0.0000400705,0.97355145,0.0010750641,0.009348392,0.00062817015,0.014959923],"study_design_scores_gemma":[0.000013258463,0.000026147167,0.000072035706,0.0000025689567,0.000003089149,0.000016923452,0.000014861312,0.99092394,0.0002469915,0.00813678,0.0005396,0.0000038163694],"about_ca_topic_score_codex":0.0030917164,"about_ca_topic_score_gemma":0.0023072418,"teacher_disagreement_score":0.0030917164,"about_ca_system_score_codex":0.00093253114,"about_ca_system_score_gemma":0.0014456565,"threshold_uncertainty_score":0.006950319},"labels":[],"label_agreement":null},{"id":"W2938806477","doi":"10.4230/lipics.icalp.2019.137","title":"Energy Consumption of Group Search on a Line","year":2019,"lang":"en","type":"preprint","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Université de Sherbrooke; Carleton University; Toronto Metropolitan University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Bounded function; Line (geometry); Energy (signal processing); Computer science; Energy consumption; Constant (computer programming); Algorithm; Mathematics; Artificial intelligence; Engineering; Geometry; Electrical engineering","score_opus":0.050881177732604296,"score_gpt":0.30483765629693776,"score_spread":0.25395647856433345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2938806477","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8144142,0.00076909654,0.16744779,0.00063106697,0.000055519045,0.00009835783,0.00027043876,0.00027746658,0.016036006],"genre_scores_gemma":[0.9842881,0.00011732766,0.013189794,0.000034045417,0.000006470887,0.000061879065,0.00009943624,0.000028911556,0.002174027],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995442,0.00013697828,0.000014671348,0.00007818293,0.00008998525,0.00013597804],"domain_scores_gemma":[0.9990466,0.00060162623,0.00010555435,0.000091521804,0.0000818011,0.00007281906],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005154192,0.0005487436,0.00074316974,0.00044231015,0.0005375581,0.0009437447,0.0011680205,0.001167604,0.004073307],"category_scores_gemma":[0.002368579,0.00027061612,0.00041636708,0.000790009,0.0006599007,0.0015626872,0.0008636918,0.00041760452,0.00038736864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005712793,0.0000903068,0.00097132573,0.000070527334,0.00003857049,0.00013847378,0.00006607534,0.9754136,0.0033705838,0.0050070714,0.0006933938,0.013568686],"study_design_scores_gemma":[0.000027422617,0.0001696646,0.000432316,0.000004918049,0.000010205235,0.000042144344,0.000071355855,0.9945147,0.0008136041,0.003586672,0.0003199006,0.0000070674228],"about_ca_topic_score_codex":0.0024010374,"about_ca_topic_score_gemma":0.0014004336,"teacher_disagreement_score":0.004073307,"about_ca_system_score_codex":0.0009943628,"about_ca_system_score_gemma":0.00042714828,"threshold_uncertainty_score":0.013626516},"labels":[],"label_agreement":null},{"id":"W2942755285","doi":"10.1007/s00453-020-00728-0","title":"Online Bin Covering with Advice","year":2020,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natur og Univers, Det Frie Forskningsråd","keywords":"Advice (programming); Bin; Competitive analysis; Online algorithm; Bin packing problem; Binary logarithm; Mathematics; Theory of computation; Combinatorics; Computer science; Algorithm; Discrete mathematics; Upper and lower bounds","score_opus":0.02001191323843362,"score_gpt":0.2351358559611555,"score_spread":0.21512394272272187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2942755285","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12687622,0.0017176417,0.7000688,0.004470019,0.0011601183,0.0005099005,0.0045244377,0.033600427,0.12707241],"genre_scores_gemma":[0.5940423,0.0004473539,0.3528437,0.0008537732,0.00035682492,0.00023094156,0.003553113,0.0020436908,0.0456283],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99870884,0.00027532846,0.00004757977,0.0002399612,0.00041109353,0.00031713146],"domain_scores_gemma":[0.9972717,0.0011534027,0.00009301951,0.0010754182,0.00025559482,0.00015082683],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007740676,0.0011771467,0.0012809907,0.0010669947,0.0010137309,0.0016090139,0.001699918,0.0017121237,0.044095907],"category_scores_gemma":[0.0069903075,0.000573846,0.0009826289,0.0018196581,0.00069035194,0.002975495,0.0025608283,0.0019608599,0.007815674],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017846376,0.0007255591,0.0029344312,0.00046270713,0.00011249757,0.00033451666,0.00017227179,0.117383115,0.0058615655,0.04368151,0.13508444,0.69146276],"study_design_scores_gemma":[0.0002131458,0.000120783836,0.00066316477,0.00006111403,0.00007445812,0.00026279566,0.00007463315,0.8028854,0.005805732,0.16455777,0.025256937,0.000023976801],"about_ca_topic_score_codex":0.0040182564,"about_ca_topic_score_gemma":0.008803337,"teacher_disagreement_score":0.044095907,"about_ca_system_score_codex":0.0009932994,"about_ca_system_score_gemma":0.0019820253,"threshold_uncertainty_score":0.14751548},"labels":[],"label_agreement":null},{"id":"W2944911880","doi":"10.1007/978-3-030-19823-7_38","title":"Optimizing Self-organizing Lists-on-Lists Using Enhanced Object Partitioning","year":2019,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Context (archaeology); Object (grammar); Hierarchy; Data structure; De facto; Theoretical computer science; Hierarchical clustering; Information retrieval; Field (mathematics); Cluster analysis; Data mining; Artificial intelligence; Programming language; Geography; Mathematics","score_opus":0.013421304868717567,"score_gpt":0.266610094672609,"score_spread":0.2531887898038914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944911880","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08709462,0.00060027145,0.90035117,0.00014355632,0.00010916587,0.000115539675,0.00014938775,0.0022641846,0.009172092],"genre_scores_gemma":[0.55502784,0.00021575506,0.4358622,0.00009478618,0.0000599504,0.00019700988,0.00043558207,0.00041191536,0.0076950244],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99973065,0.00006334645,0.000013800089,0.000044435088,0.00008869851,0.000059093723],"domain_scores_gemma":[0.99939656,0.00030077042,0.000043613283,0.00009632591,0.0001213712,0.000041311367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036187717,0.0006935466,0.0010575827,0.0006071178,0.00073344045,0.0010257742,0.0018609539,0.0008394787,0.004872538],"category_scores_gemma":[0.0010298162,0.00047837864,0.00046641545,0.0011217993,0.00032500672,0.0012732017,0.0011037524,0.00053252996,0.0007764739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026121942,0.00024092654,0.0005324091,0.0001472628,0.000054216413,0.00005332529,0.000077451215,0.7801761,0.012054316,0.0072885924,0.005379391,0.19373475],"study_design_scores_gemma":[0.00001320939,0.00005103499,0.00009214279,0.0000029267976,0.000007684626,0.000014933026,0.000015573849,0.9960239,0.0017589265,0.0014422756,0.0005727677,0.0000045943057],"about_ca_topic_score_codex":0.0033300298,"about_ca_topic_score_gemma":0.005906921,"teacher_disagreement_score":0.004872538,"about_ca_system_score_codex":0.0007035767,"about_ca_system_score_gemma":0.0007018292,"threshold_uncertainty_score":0.016300261},"labels":[],"label_agreement":null},{"id":"W2944983791","doi":"10.1016/j.jcss.2024.103545","title":"Online computation with untrusted advice","year":2024,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche; Centro de Modelamiento Matemático, Facultad de Ciencias Físicas y Matemáticas","keywords":"Advice (programming); Bidding; Adversarial system; Computer science; Online algorithm; Competitive analysis; Computation; Generalization; Bin packing problem; Pareto principle; Mathematical optimization; Bin; Algorithm; Artificial intelligence; Upper and lower bounds; Mathematics; Business; Marketing","score_opus":0.020594512805411674,"score_gpt":0.28330973365175727,"score_spread":0.2627152208463456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944983791","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20037864,0.0013867713,0.7426826,0.006818865,0.0011781054,0.00018460148,0.00070793385,0.00925497,0.037407555],"genre_scores_gemma":[0.88189924,0.00017977534,0.104760796,0.00046597805,0.00029863892,0.00009316096,0.00023385936,0.0005076632,0.0115608685],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962708,0.001174603,0.00022005574,0.00064242864,0.001024636,0.0006675679],"domain_scores_gemma":[0.9712848,0.016932085,0.0005996459,0.009073777,0.0015171106,0.0005925646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027267742,0.00065782166,0.001460226,0.00069247273,0.0015198888,0.0026270233,0.0020902627,0.002407805,0.013003216],"category_scores_gemma":[0.031328943,0.00070766156,0.00081683573,0.0012568388,0.002047903,0.0058501964,0.0030667053,0.0034369621,0.0021478178],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0034172055,0.0009270944,0.006581051,0.00049581315,0.00024776626,0.000813777,0.0006894471,0.316593,0.007118534,0.23396155,0.043809865,0.38534492],"study_design_scores_gemma":[0.00014678476,0.00005922327,0.00023068604,0.00002320566,0.000042977954,0.00008955854,0.00003767096,0.7756844,0.0027065896,0.21852647,0.0024375026,0.000014897555],"about_ca_topic_score_codex":0.0034784868,"about_ca_topic_score_gemma":0.0056571634,"teacher_disagreement_score":0.013003216,"about_ca_system_score_codex":0.0013380934,"about_ca_system_score_gemma":0.003293227,"threshold_uncertainty_score":0.043500125},"labels":[],"label_agreement":null},{"id":"W2944999878","doi":"10.7146/brics.v11i2.21827","title":"Cache-Oblivious Data Structures and Algorithms for Undirected Breadth-First Search and Shortest Paths","year":2004,"lang":"en","type":"article","venue":"BRICS Report Series","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Computer science; Combinatorics; Data structure; Algorithm; Theoretical computer science; Mathematics","score_opus":0.07440722122927845,"score_gpt":0.3161123087104155,"score_spread":0.24170508748113706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2944999878","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014400789,0.0012283529,0.9704945,0.00065545953,0.00013644421,0.00018479589,0.0010327436,0.006501222,0.005365586],"genre_scores_gemma":[0.13472457,0.0007986458,0.8523794,0.0004499176,0.00015437095,0.00075741974,0.0033298768,0.0012883455,0.0061174585],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967906,0.0005127493,0.00033896026,0.00067546143,0.0012512376,0.00043091478],"domain_scores_gemma":[0.9931114,0.001890052,0.0005555378,0.0030706965,0.0011917527,0.00018061053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017676945,0.001537374,0.0013284779,0.0024557435,0.0015730925,0.0025313026,0.004815597,0.0015284618,0.008883283],"category_scores_gemma":[0.0093303835,0.001023823,0.0015196024,0.005905655,0.001674228,0.008901916,0.0038656835,0.0036637015,0.00348104],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009574224,0.00047785576,0.0019377574,0.0011909447,0.0002233769,0.00015414601,0.0007408225,0.16268423,0.01592791,0.24991494,0.041463096,0.52432746],"study_design_scores_gemma":[0.00032751643,0.00031333475,0.0004387932,0.00016884589,0.00012925088,0.00023770996,0.00019935961,0.5895755,0.022741541,0.34697634,0.038764384,0.00012746165],"about_ca_topic_score_codex":0.00604635,"about_ca_topic_score_gemma":0.0079241805,"teacher_disagreement_score":0.008883283,"about_ca_system_score_codex":0.0031560413,"about_ca_system_score_gemma":0.004903646,"threshold_uncertainty_score":0.029717505},"labels":[],"label_agreement":null},{"id":"W2946277238","doi":"10.65109/shqf6416","title":"Efficient Allocation of Free Stuff","year":2019,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Constant (computer programming); Approximation algorithm; Matching (statistics); Zero (linguistics); Class (philosophy); Value (mathematics); Mathematics; Greedy algorithm; Mathematical optimization; Mathematical economics; Computer science; Combinatorics; Discrete mathematics; Artificial intelligence; Statistics","score_opus":0.013164327364169923,"score_gpt":0.24283661761563527,"score_spread":0.22967229025146535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946277238","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2662655,0.0011707628,0.6975538,0.0019083339,0.00019683108,0.0004356874,0.00070071005,0.001319947,0.030448353],"genre_scores_gemma":[0.8795071,0.00035736943,0.10809458,0.00023920748,0.00009720096,0.00015743844,0.00034449692,0.00016659322,0.011035882],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99754816,0.0010699377,0.00010281206,0.0005206296,0.0002860031,0.00047242024],"domain_scores_gemma":[0.9913327,0.0055255108,0.000726322,0.0014485084,0.00025694896,0.0007100464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029801144,0.0011628229,0.0019174718,0.0008514366,0.0010460868,0.0022872256,0.0035717292,0.0023018925,0.012830814],"category_scores_gemma":[0.013996517,0.0008878468,0.00092240295,0.0017450774,0.0014003122,0.0068833474,0.002307796,0.0018455418,0.0017017195],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0023108553,0.0013428162,0.003007578,0.00054588815,0.00023877628,0.00034353233,0.00037830134,0.5226465,0.0043474357,0.27803013,0.012400825,0.1744074],"study_design_scores_gemma":[0.00009940357,0.00014904707,0.0003118762,0.000021003485,0.000031048807,0.00008953418,0.00006555654,0.8539756,0.0009992819,0.14124608,0.0029930708,0.00001852952],"about_ca_topic_score_codex":0.0019543765,"about_ca_topic_score_gemma":0.002180881,"teacher_disagreement_score":0.012830814,"about_ca_system_score_codex":0.002114015,"about_ca_system_score_gemma":0.0013178983,"threshold_uncertainty_score":0.04292339},"labels":[],"label_agreement":null},{"id":"W2947061402","doi":"10.22215/etd/2018-13392","title":"On Designing Adaptive Data Structures with Adaptive Data \"Sub\"-Structures","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Hierarchy; Probabilistic logic; Reinforcement learning; Automaton; Locality; Object (grammar); Process (computing); Transitive relation; State (computer science); Adaptation (eye); Artificial intelligence; Theoretical computer science; Data mining; Algorithm; Programming language; Mathematics","score_opus":0.09424601612719963,"score_gpt":0.3231868164055095,"score_spread":0.22894080027830988,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2947061402","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012031796,0.0017360743,0.9794693,0.00064766745,0.000110802685,0.000121624485,0.000069599046,0.00051343173,0.0052997316],"genre_scores_gemma":[0.12323008,0.0032977052,0.8665905,0.0007090961,0.00023045647,0.00045720593,0.0003383889,0.00048209977,0.0046644793],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988329,0.00028836436,0.00011433492,0.0001863586,0.00047378446,0.00010426539],"domain_scores_gemma":[0.9964425,0.0016982699,0.00028152502,0.0009443762,0.0005323233,0.00010104231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015644773,0.00073362596,0.0007540682,0.000633965,0.00057107914,0.0016444261,0.0017761245,0.0009269808,0.0029944426],"category_scores_gemma":[0.007199011,0.0006025695,0.0005677422,0.001350396,0.0018935106,0.0062082987,0.0021720943,0.0020595274,0.0012878132],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019073025,0.00019519539,0.00217909,0.0011643168,0.00009636921,0.00010996844,0.00055775844,0.13364501,0.0372524,0.43699443,0.012948604,0.3746661],"study_design_scores_gemma":[0.00007959043,0.00034595162,0.00083591894,0.00031833528,0.0000902913,0.00035052167,0.00026222132,0.50883794,0.032076105,0.35843697,0.09829602,0.00007018025],"about_ca_topic_score_codex":0.00067854056,"about_ca_topic_score_gemma":0.0012802393,"teacher_disagreement_score":0.0029944426,"about_ca_system_score_codex":0.0007408967,"about_ca_system_score_gemma":0.0012496725,"threshold_uncertainty_score":0.010017455},"labels":[],"label_agreement":null},{"id":"W2949079286","doi":"10.48550/arxiv.1410.2295","title":"Local Policies for Efficiently Patrolling a Triangulated Region by a Robot Swarm","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Patrolling; Robot; Computer science; Workspace; Triangulation; Focus (optics); Mobile robot; Swarm behaviour; Graph; Distributed computing; Simple (philosophy); Mathematical optimization; Artificial intelligence; Theoretical computer science; Mathematics; Geography","score_opus":0.07641307542284566,"score_gpt":0.206084841274995,"score_spread":0.12967176585214935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949079286","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03720322,0.00015923296,0.96029377,0.00013189374,0.000013806189,0.0000636747,0.000031633073,0.00023190277,0.001870902],"genre_scores_gemma":[0.6498104,0.0002566608,0.346704,0.000058073892,0.00002774679,0.0003309006,0.00011014353,0.00013371672,0.002568356],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994855,0.0001867042,0.000023589595,0.000102202095,0.00011767059,0.00008426806],"domain_scores_gemma":[0.9975344,0.0015084088,0.00037751347,0.00027640347,0.00014344971,0.00015975432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012191191,0.00066325563,0.00073537487,0.0006498818,0.00052661286,0.00072227826,0.001209194,0.0008248829,0.0016991462],"category_scores_gemma":[0.0046787616,0.00043354408,0.000550626,0.00052892667,0.001149714,0.0010950832,0.0015432694,0.0006515265,0.00032476513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000049662023,0.000035305973,0.00064553285,0.000058631464,0.000019062298,0.000031290456,0.000066041,0.9624566,0.0018300943,0.014690272,0.000505816,0.019611765],"study_design_scores_gemma":[0.000011174167,0.000050987936,0.00007964183,0.0000058491773,0.000004406189,0.000013409078,0.000019609366,0.9930171,0.0006447619,0.005692468,0.00045617938,0.0000044595567],"about_ca_topic_score_codex":0.0019664573,"about_ca_topic_score_gemma":0.001678626,"teacher_disagreement_score":0.0019664573,"about_ca_system_score_codex":0.0010234767,"about_ca_system_score_gemma":0.00074690714,"threshold_uncertainty_score":0.0074258447},"labels":[],"label_agreement":null},{"id":"W2949226015","doi":"10.1145/3323165.3323182","title":"Using Time to Break Symmetry","year":2019,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rendezvous; Time complexity; Computer science; A priori and a posteriori; Graph; Node (physics); PSPACE; Task (project management); Symmetry breaking; Symmetry (geometry); Algorithm; Theoretical computer science; Mathematics; Computational complexity theory; Physics","score_opus":0.02393281051641785,"score_gpt":0.27492755519306006,"score_spread":0.2509947446766422,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949226015","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037305735,0.00037120463,0.9479754,0.0006790634,0.0001607815,0.00018949318,0.00014167339,0.00088144495,0.012295236],"genre_scores_gemma":[0.60621613,0.00061887066,0.38275743,0.00039618905,0.00014526065,0.00063082407,0.0004186606,0.00045985036,0.008356807],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99432606,0.0021629224,0.00038787682,0.0014437654,0.00087067403,0.0008087244],"domain_scores_gemma":[0.9872436,0.0069081495,0.0013630671,0.0031332206,0.0007964869,0.0005554226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003226219,0.0013031419,0.0012188362,0.001024671,0.0018741917,0.00310243,0.0022308296,0.0013153196,0.005854724],"category_scores_gemma":[0.020441357,0.00072646776,0.001951133,0.0012423014,0.00465492,0.008032523,0.004932679,0.0028800373,0.0011319218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005243337,0.000107166175,0.0010163311,0.0002465846,0.0000783215,0.00022257779,0.00059722236,0.17339669,0.006102373,0.7440125,0.0027922771,0.070903696],"study_design_scores_gemma":[0.00012011426,0.00021918483,0.0001685558,0.0000644385,0.000050179777,0.00013507824,0.00014613269,0.2648391,0.00636501,0.71571827,0.012122096,0.000051935156],"about_ca_topic_score_codex":0.0024918185,"about_ca_topic_score_gemma":0.0017444704,"teacher_disagreement_score":0.005854724,"about_ca_system_score_codex":0.002463963,"about_ca_system_score_gemma":0.003159564,"threshold_uncertainty_score":0.019586027},"labels":[],"label_agreement":null},{"id":"W2949270856","doi":"10.1137/1.9781611973105.88","title":"Online submodular welfare maximization: Greedy is optimal","year":2013,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Submodular set function; Greedy algorithm; Competitive analysis; Maximization; Monotone polygon; Online algorithm; Mathematical optimization; Greedy randomized adaptive search procedure; Competitive equilibrium; Mathematics; Computer science; Mathematical economics; Upper and lower bounds","score_opus":0.03280591326405214,"score_gpt":0.26941727256939507,"score_spread":0.23661135930534294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949270856","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24098417,0.0017305573,0.6937338,0.0072394297,0.0002694979,0.0004592409,0.001239448,0.0019084738,0.052435394],"genre_scores_gemma":[0.8362554,0.0009438039,0.15431167,0.00148938,0.00035599785,0.0003879796,0.0006076209,0.00042733457,0.0052208044],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99589384,0.0015824325,0.00011683776,0.000858584,0.0007055602,0.0008427463],"domain_scores_gemma":[0.98787165,0.00868222,0.00080917013,0.001480106,0.00044169897,0.0007151716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00445822,0.001626035,0.0026370198,0.0008753389,0.0013442503,0.004643232,0.0025756373,0.003215023,0.0063155284],"category_scores_gemma":[0.019572956,0.0007220553,0.0012220627,0.0020200373,0.0020808557,0.0060784724,0.0025767083,0.0032336356,0.001115612],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0031090514,0.0015591691,0.0047418107,0.0010338298,0.000407513,0.00031649508,0.00040597207,0.34236035,0.013663258,0.428558,0.034295835,0.16954872],"study_design_scores_gemma":[0.00020344682,0.00021721295,0.000562269,0.00006331622,0.000071169736,0.00036154836,0.0001082508,0.72417206,0.0047619524,0.2647643,0.0046848985,0.000029487548],"about_ca_topic_score_codex":0.0014063757,"about_ca_topic_score_gemma":0.001661548,"teacher_disagreement_score":0.0063155284,"about_ca_system_score_codex":0.0027790386,"about_ca_system_score_gemma":0.0036941636,"threshold_uncertainty_score":0.02357757},"labels":[],"label_agreement":null},{"id":"W2949433202","doi":"10.48550/arxiv.1404.7325","title":"Tight Bounds for Restricted Grid Scheduling","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Syddansk Universitet; University of Waterloo; University of Toronto; Danmarks Frie Forskningsfond; Villum Fonden","keywords":"Bin; Bin packing problem; Grid; Upper and lower bounds; Competitive analysis; Matching (statistics); Online algorithm; Scheduling (production processes); Integer (computer science); Computer science; Mathematics; Mathematical optimization; Combinatorics; Algorithm; Statistics","score_opus":0.08947936903725882,"score_gpt":0.2088021905716253,"score_spread":0.11932282153436648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949433202","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0755634,0.017374547,0.7924715,0.0068265875,0.0010575801,0.00022962278,0.002070841,0.0030449347,0.10136101],"genre_scores_gemma":[0.8211547,0.009486469,0.1472366,0.0018036128,0.0010983505,0.0005666285,0.002671964,0.0014213407,0.01456022],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99511176,0.0013765102,0.00017216316,0.00069878466,0.0014160109,0.0012248144],"domain_scores_gemma":[0.98223555,0.012366295,0.001018669,0.00247613,0.001066273,0.0008370322],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047013676,0.0024336595,0.0029688738,0.002863276,0.0016898924,0.005197678,0.003993926,0.0019408272,0.016349664],"category_scores_gemma":[0.02898352,0.0012902416,0.0014458824,0.0057041734,0.0025914218,0.0070947693,0.004307211,0.0050508818,0.0030133387],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010344975,0.0003155769,0.0014508483,0.0008667741,0.00017633464,0.00021804927,0.00027821798,0.550307,0.003143635,0.3513659,0.028162694,0.062680416],"study_design_scores_gemma":[0.00008770288,0.00008473858,0.0005176783,0.00013000294,0.000053020256,0.00008880789,0.00010995864,0.54723245,0.0007909117,0.4419377,0.00893951,0.000027445494],"about_ca_topic_score_codex":0.007566753,"about_ca_topic_score_gemma":0.0059979553,"teacher_disagreement_score":0.016349664,"about_ca_system_score_codex":0.0042714253,"about_ca_system_score_gemma":0.0026960429,"threshold_uncertainty_score":0.05469513},"labels":[],"label_agreement":null},{"id":"W2949499079","doi":"10.48550/arxiv.1709.06214","title":"Deterministic rendezvous with detection using beeps","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Rendezvous; Node (physics); Computer science; Mobile agent; Computer network; Real-time computing; Distributed computing; Engineering","score_opus":0.1397833646239472,"score_gpt":0.214835737831567,"score_spread":0.07505237320761982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949499079","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017291535,0.00026113522,0.97406274,0.00023010864,0.00007264878,0.000086121465,0.00011932643,0.0007205067,0.0071558454],"genre_scores_gemma":[0.82047737,0.00043218568,0.16510193,0.00027619803,0.00007257083,0.0004290337,0.00026958762,0.00022656802,0.012714601],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9976184,0.0005366655,0.0001306613,0.0005863431,0.00067317626,0.00045477177],"domain_scores_gemma":[0.9950352,0.0026870251,0.00054198236,0.0010755954,0.00040837808,0.00025181525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012108133,0.0012153601,0.0013020203,0.00071065925,0.0012159559,0.0019470813,0.0029539904,0.001848286,0.004271036],"category_scores_gemma":[0.0066012377,0.0007484751,0.001144807,0.0008231225,0.0020349196,0.0030082087,0.0039651524,0.0019794125,0.0009114675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041996743,0.00008182196,0.0012519428,0.00025348313,0.0000823064,0.0005404186,0.00047129084,0.62306565,0.011004806,0.32263923,0.0037107535,0.036478393],"study_design_scores_gemma":[0.000043660853,0.000059632028,0.0001092155,0.000015078717,0.000018647277,0.00012350896,0.00004195021,0.92790395,0.0027878108,0.06455946,0.004301586,0.000035483466],"about_ca_topic_score_codex":0.0048512784,"about_ca_topic_score_gemma":0.004416908,"teacher_disagreement_score":0.0048512784,"about_ca_system_score_codex":0.0014894372,"about_ca_system_score_gemma":0.0012931746,"threshold_uncertainty_score":0.014288008},"labels":[],"label_agreement":null},{"id":"W2949738152","doi":"10.1137/1.9781611973082.131","title":"The Dichotomy of List Homomorphisms for Digraphs","year":2011,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Homomorphism; Digraph; Conjecture; Combinatorics; Computer science; Discrete mathematics; Mathematics","score_opus":0.046986232809474275,"score_gpt":0.27724674275607,"score_spread":0.2302605099465957,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949738152","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5753122,0.0014513148,0.35648614,0.008278176,0.0001371147,0.00020413903,0.0016956395,0.00088310306,0.055552226],"genre_scores_gemma":[0.94074214,0.0006472001,0.047235698,0.0009083684,0.00017146314,0.00025787405,0.0014345669,0.00010526751,0.008497421],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99803275,0.00052097265,0.00015528989,0.0005502112,0.00040858908,0.00033220544],"domain_scores_gemma":[0.991803,0.006064108,0.0005014577,0.00074687955,0.00042979335,0.00045487942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018257456,0.00032869456,0.0007138399,0.0013990953,0.0019977412,0.0044910572,0.0011254482,0.0013258822,0.0073043164],"category_scores_gemma":[0.008683186,0.000534018,0.0009386628,0.0015623233,0.0030003649,0.008926444,0.0025548963,0.003729971,0.00069481024],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001774855,0.00012851693,0.0016709984,0.00017348256,0.000021477827,0.00013157705,0.0008219959,0.0047470075,0.0019985659,0.96198595,0.0027853441,0.025357638],"study_design_scores_gemma":[0.00006236826,0.000049641116,0.0006350721,0.000035149227,0.000016167463,0.00014318764,0.00032117433,0.016097872,0.001389185,0.97698146,0.004249858,0.000018969326],"about_ca_topic_score_codex":0.0012238333,"about_ca_topic_score_gemma":0.0011241625,"teacher_disagreement_score":0.0073043164,"about_ca_system_score_codex":0.0023891223,"about_ca_system_score_gemma":0.0012134094,"threshold_uncertainty_score":0.024435341},"labels":[],"label_agreement":null},{"id":"W2949907273","doi":"10.48550/arxiv.1212.4211","title":"The quadratic balanced optimization problem","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Knapsack problem; Heuristic; Pairwise comparison; Mathematical optimization; Simple (philosophy); Quadratic equation; Quadratic assignment problem; Mathematics; Continuous knapsack problem; Optimization problem; Matrix (chemical analysis); Quadratic programming; Sequence (biology); Computer science; Algorithm","score_opus":0.06536104432498288,"score_gpt":0.19309573322668527,"score_spread":0.1277346889017024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2949907273","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013429371,0.001013633,0.9465858,0.0012046112,0.00022732194,0.00012302645,0.0010050185,0.0002684399,0.03614292],"genre_scores_gemma":[0.47386605,0.0031363207,0.46790254,0.001047523,0.00043737152,0.0007961311,0.004051189,0.00059697445,0.048165858],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986975,0.0004268875,0.00004850844,0.00028975974,0.0003466853,0.00019063316],"domain_scores_gemma":[0.9993352,0.00031709226,0.00007962403,0.00006615123,0.00012951474,0.000072474235],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011798813,0.001211783,0.0008112283,0.000565197,0.0005422462,0.0015885805,0.0012136151,0.0012336746,0.012568404],"category_scores_gemma":[0.003275602,0.00039603157,0.0005543623,0.0011705529,0.0008253181,0.0020905233,0.001770057,0.0016439761,0.0020765134],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015150291,0.00018474046,0.00086537364,0.0004081347,0.00006929333,0.00022534827,0.00009627778,0.5609984,0.0038042194,0.3051157,0.029249065,0.09883195],"study_design_scores_gemma":[0.00004549681,0.00011454915,0.00037612632,0.000037441256,0.000016276954,0.00016663101,0.000055495144,0.79021335,0.0008667541,0.17074503,0.037342686,0.000020148791],"about_ca_topic_score_codex":0.002388811,"about_ca_topic_score_gemma":0.0018703474,"teacher_disagreement_score":0.012568404,"about_ca_system_score_codex":0.0009822742,"about_ca_system_score_gemma":0.0011672659,"threshold_uncertainty_score":0.042045534},"labels":[],"label_agreement":null},{"id":"W2950401695","doi":"10.48550/arxiv.1305.2108","title":"On Advice Complexity of the k-server Problem under Sparse Metrics","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Treewidth; Advice (programming); Combinatorics; Competitive analysis; Binary logarithm; Mathematics; Online algorithm; Metric space; Discrete mathematics; Upper and lower bounds; Tree (set theory); Omega; Metric (unit); Path (computing); Sequence (biology); Graph; Algorithm; Computer science; Pathwidth; Line graph","score_opus":0.16325824152864088,"score_gpt":0.21404882625197952,"score_spread":0.05079058472333864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950401695","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6802332,0.0018351298,0.27860454,0.011568638,0.0001802659,0.00034719636,0.0018553454,0.0016963242,0.023679378],"genre_scores_gemma":[0.8789935,0.0012845593,0.107728854,0.0008894687,0.0003949957,0.00043866463,0.0016526274,0.00050847034,0.008108698],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99671507,0.0011171782,0.00019660602,0.00060906605,0.0006097449,0.00075231824],"domain_scores_gemma":[0.9661958,0.028079566,0.001493254,0.0018665711,0.0010149799,0.0013497035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002582992,0.0012548431,0.002097639,0.0008133345,0.0013193318,0.0033196202,0.0031907447,0.0030325325,0.010119085],"category_scores_gemma":[0.02860627,0.00059146027,0.0009884716,0.0021667825,0.0022424262,0.007931853,0.0026354904,0.0033065886,0.0014092408],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036181766,0.0005746771,0.009929563,0.0012648124,0.00020596932,0.0005801924,0.0011423251,0.63334185,0.014843889,0.22023176,0.020303342,0.093963414],"study_design_scores_gemma":[0.00017255182,0.00011994005,0.0011331366,0.000025156438,0.00003913137,0.00016782086,0.000131089,0.8683017,0.0012596807,0.12756462,0.0010582443,0.000026899701],"about_ca_topic_score_codex":0.005982394,"about_ca_topic_score_gemma":0.004630347,"teacher_disagreement_score":0.010119085,"about_ca_system_score_codex":0.0027314723,"about_ca_system_score_gemma":0.0021741425,"threshold_uncertainty_score":0.033851683},"labels":[],"label_agreement":null},{"id":"W2950424720","doi":"10.1145/2438645.2438649","title":"Delays Induce an Exponential Memory Gap for Rendezvous in Trees","year":2013,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche; Natural Sciences and Engineering Research Council of Canada; Institut national de recherche en informatique et en automatique (INRIA)","keywords":"Rendezvous; Exponential function; Computer science; Psychology; Mathematics; Physics; Astronomy; Mathematical analysis","score_opus":0.05484617889239228,"score_gpt":0.29676872146558664,"score_spread":0.24192254257319434,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950424720","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81744117,0.0012646625,0.16584682,0.00181702,0.00007116166,0.00007331436,0.00048074542,0.0013599703,0.011645146],"genre_scores_gemma":[0.9795569,0.00040562215,0.017118022,0.00021112569,0.000045152497,0.00013125068,0.00020802858,0.00020191936,0.00212183],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99830246,0.00025568332,0.00011081563,0.00039436485,0.000319154,0.0006174466],"domain_scores_gemma":[0.97350514,0.02064152,0.0018326888,0.0025303673,0.0006056208,0.0008846691],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011977182,0.0007744701,0.0011962474,0.00075380993,0.0012869445,0.002427951,0.0019111908,0.0012974592,0.005008502],"category_scores_gemma":[0.015160474,0.00061597745,0.0009340771,0.0007703676,0.0022584079,0.0073952186,0.0033810025,0.0023379037,0.0005910635],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.005797451,0.00050805847,0.0077521275,0.0012816117,0.00024411123,0.0014305699,0.002283473,0.42295176,0.089437515,0.38185763,0.006072299,0.080383405],"study_design_scores_gemma":[0.00024620892,0.0004993551,0.0017480226,0.000099356985,0.00015457251,0.00070715934,0.0005153238,0.5800928,0.036721904,0.37483376,0.004305626,0.00007594765],"about_ca_topic_score_codex":0.0010785274,"about_ca_topic_score_gemma":0.0011296828,"teacher_disagreement_score":0.005008502,"about_ca_system_score_codex":0.0016184996,"about_ca_system_score_gemma":0.0011734404,"threshold_uncertainty_score":0.016755044},"labels":[],"label_agreement":null},{"id":"W2950450215","doi":"10.1142/s0129054121500209","title":"Search on a Line by Byzantine Robots","year":2021,"lang":"en","type":"preprint","venue":"International Journal of Foundations of Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Carleton University; Toronto Metropolitan University; Université du Québec en Outaouais","funders":"National Science Foundation","keywords":"Robot; Line (geometry); Computer science; Algorithm; Fault tolerance; Mobile robot; Distributed computing; Artificial intelligence; Mathematics; Geometry","score_opus":0.050519827703159915,"score_gpt":0.3664393369516543,"score_spread":0.3159195092484944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950450215","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17639993,0.00075419806,0.81590044,0.0012025466,0.00010077474,0.00011102213,0.000198845,0.00056829967,0.0047639725],"genre_scores_gemma":[0.7897853,0.00051688467,0.20181689,0.00018778382,0.00008008763,0.00024017622,0.00024730043,0.00014740754,0.006978093],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992756,0.0002605534,0.000033271,0.00021033577,0.00011051881,0.000109667846],"domain_scores_gemma":[0.9963689,0.0026020687,0.0004719743,0.0002198863,0.00019526453,0.00014184395],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011669219,0.0010875579,0.0015278086,0.0005800044,0.0007513973,0.0010299796,0.001987219,0.0016501468,0.0038752677],"category_scores_gemma":[0.0071212538,0.00046747216,0.0005844025,0.0010555021,0.0015407417,0.002718741,0.0011912964,0.00124867,0.00053929427],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033928794,0.00007386563,0.00056427537,0.00019017441,0.00005203534,0.00021768035,0.00010260276,0.95579046,0.002062353,0.021790016,0.0011990509,0.017618142],"study_design_scores_gemma":[0.00006206376,0.00008612797,0.00009556336,0.000009591026,0.000010755031,0.000053329917,0.000024308134,0.97631454,0.00085500395,0.021772448,0.00070835964,0.000007901243],"about_ca_topic_score_codex":0.0018635305,"about_ca_topic_score_gemma":0.0012149856,"teacher_disagreement_score":0.0038752677,"about_ca_system_score_codex":0.0009515882,"about_ca_system_score_gemma":0.0006683841,"threshold_uncertainty_score":0.01296401},"labels":[],"label_agreement":null},{"id":"W2950585818","doi":"10.48550/arxiv.1709.06217","title":"Deterministic meeting of sniffing agents in the plane","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Null (SQL); Plane (geometry); Set (abstract data type); Computer science; Reading (process); Monotone polygon; Moment (physics); Constant (computer programming); Mathematics; Geometry; Physics; Data mining","score_opus":0.17791746566357755,"score_gpt":0.2409973909572207,"score_spread":0.06307992529364315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950585818","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56073433,0.0007728054,0.41816565,0.0018402179,0.00013654519,0.000204713,0.0011649699,0.0005391446,0.01644157],"genre_scores_gemma":[0.9737969,0.00026452774,0.01576595,0.000107605825,0.000054784738,0.00010910271,0.0005883419,0.000039555933,0.0092732785],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982698,0.00037460556,0.000098888326,0.00050795934,0.00025936143,0.00048944796],"domain_scores_gemma":[0.9925755,0.0034372073,0.0019163479,0.0005832051,0.00053761574,0.0009500209],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016404237,0.0011063467,0.0015576725,0.00073829165,0.0010314347,0.001937044,0.003432309,0.0030156777,0.0055178395],"category_scores_gemma":[0.0114328535,0.0012206342,0.0011375254,0.0007504266,0.0021990028,0.0029205475,0.0031495148,0.0015137835,0.0011364119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011663832,0.00010676628,0.012228131,0.0002234736,0.000109675944,0.0013447155,0.000685442,0.8868068,0.0046555055,0.078827165,0.002425249,0.011420661],"study_design_scores_gemma":[0.00006230757,0.00010952936,0.0015030466,0.000017045868,0.000034509245,0.00014603755,0.00016817171,0.9858251,0.0005956851,0.010664033,0.0008347667,0.000039773535],"about_ca_topic_score_codex":0.017976746,"about_ca_topic_score_gemma":0.009858659,"teacher_disagreement_score":0.017976746,"about_ca_system_score_codex":0.0018374074,"about_ca_system_score_gemma":0.0008336119,"threshold_uncertainty_score":0.03574425},"labels":[],"label_agreement":null},{"id":"W2950689051","doi":"10.48550/arxiv.1410.1077","title":"Optimal Distributed Searching in the Plane with and without Uncertainty","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Visibility; Search and rescue; Drone; Computer science; Robot; Task (project management); Plane (geometry); Artificial intelligence; Search problem; Mathematical optimization; Algorithm; Mathematics; Engineering; Geography; Geometry","score_opus":0.05306328905859759,"score_gpt":0.2027070210942009,"score_spread":0.14964373203560333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950689051","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15466435,0.001210317,0.83089024,0.0014257545,0.00006378132,0.000048103775,0.00025957753,0.00008562465,0.011352183],"genre_scores_gemma":[0.9408472,0.00060353737,0.05416064,0.00011651996,0.00005953869,0.00010183349,0.00014389641,0.000031651594,0.0039351904],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99923766,0.00033046128,0.0000289548,0.00016883946,0.00011102284,0.00012314566],"domain_scores_gemma":[0.99822754,0.0011500675,0.0002924684,0.00009238752,0.00012709065,0.000110418485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001274089,0.0008693505,0.0013835806,0.0006716762,0.00041433133,0.0015212744,0.0012455715,0.0017265691,0.0012024135],"category_scores_gemma":[0.0051701684,0.00054894865,0.0006964165,0.0010022039,0.0016767995,0.0016949291,0.001355922,0.0008812614,0.00017899196],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000057457204,0.000015835458,0.000183163,0.000028074119,0.000018906021,0.0000489303,0.00002601106,0.9606667,0.0003299669,0.03646267,0.00024313753,0.0019191328],"study_design_scores_gemma":[0.000019944317,0.000028065815,0.0000727654,0.0000040741947,0.0000043552113,0.000014481156,0.000017000228,0.9776587,0.000091727234,0.021865964,0.00021777583,0.000005109717],"about_ca_topic_score_codex":0.0033893278,"about_ca_topic_score_gemma":0.0012743088,"teacher_disagreement_score":0.0033893278,"about_ca_system_score_codex":0.0014116485,"about_ca_system_score_gemma":0.00082612457,"threshold_uncertainty_score":0.010242283},"labels":[],"label_agreement":null},{"id":"W2950744132","doi":"10.1016/j.tcs.2018.02.020","title":"Scheduling maintenance jobs in networks","year":2018,"lang":"en","type":"preprint","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Einstein Stiftung Berlin; Deutsche Forschungsgemeinschaft; Alexander von Humboldt-Stiftung","keywords":"Preemption; Scheduling (production processes); Computer science; Time complexity; Mathematical optimization; Job shop scheduling; Simple (philosophy); Distributed computing; Mathematics; Algorithm; Computer network","score_opus":0.01711956884023272,"score_gpt":0.27661183589703037,"score_spread":0.2594922670567976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950744132","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39046213,0.002244542,0.58429587,0.0028887193,0.0005637896,0.00026990776,0.00041484548,0.000884214,0.017975938],"genre_scores_gemma":[0.94377923,0.0005321001,0.046322975,0.00012000343,0.00020402062,0.00006903729,0.00022736541,0.00016584371,0.008579433],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999516,0.00014848581,0.000021259175,0.00011896799,0.00007244243,0.00012285452],"domain_scores_gemma":[0.9981964,0.0012066708,0.00015037984,0.00016501415,0.00013870177,0.00014273582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010881724,0.0007577658,0.0009441157,0.0006334761,0.00079429476,0.0015391514,0.0013319179,0.0014150775,0.0054490343],"category_scores_gemma":[0.005752567,0.0005869799,0.00042219987,0.0009256635,0.0007108312,0.0018474488,0.00075935613,0.0010280601,0.00049781246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015014987,0.00021993447,0.0015804128,0.00050751324,0.000076752556,0.00016899104,0.00019572015,0.8278246,0.0063305744,0.044657685,0.011448501,0.10548774],"study_design_scores_gemma":[0.000040525705,0.00007936825,0.00033545104,0.000013869653,0.000024628278,0.000038509843,0.000053714924,0.9584247,0.0014602909,0.037843477,0.0016785555,0.0000069560588],"about_ca_topic_score_codex":0.0027990404,"about_ca_topic_score_gemma":0.002493368,"teacher_disagreement_score":0.0054490343,"about_ca_system_score_codex":0.0010383342,"about_ca_system_score_gemma":0.0010441099,"threshold_uncertainty_score":0.018228829},"labels":[],"label_agreement":null},{"id":"W2950850611","doi":"10.48550/arxiv.1303.3564","title":"Distributed Dominating Sets on Grids","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dominating set; Bounded function; Grid; Combinatorics; Mathematics; Set (abstract data type); Basis (linear algebra); Distributed algorithm; Discrete mathematics; Computer science; Distributed computing; Graph; Geometry","score_opus":0.07876331928276233,"score_gpt":0.2016524052663855,"score_spread":0.12288908598362318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950850611","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009398839,0.0008724388,0.98165107,0.0004425793,0.00018331924,0.00016631407,0.00013259005,0.00038696223,0.0067659025],"genre_scores_gemma":[0.3546507,0.0015832136,0.6315293,0.0004307844,0.0002169081,0.00057975564,0.00059722597,0.0001830062,0.010229072],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980724,0.00077648775,0.00011179925,0.00037265636,0.0005071791,0.00015944068],"domain_scores_gemma":[0.99829537,0.00087033585,0.00009763738,0.0003645269,0.00024808486,0.0001240543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001433371,0.0008607231,0.0014902544,0.0006721654,0.0011086003,0.0014963441,0.0019786733,0.00078583363,0.0021200508],"category_scores_gemma":[0.0040535717,0.00047324627,0.0007658073,0.0013771482,0.0008686371,0.0017827367,0.0022816532,0.0011891299,0.00072404876],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002271781,0.0000926677,0.0005529182,0.0003823526,0.00010647024,0.00016914512,0.00026903235,0.5983084,0.005077001,0.2341987,0.013837867,0.14677829],"study_design_scores_gemma":[0.0000936506,0.00011025912,0.0001728577,0.00003679858,0.000027518236,0.00013928505,0.00009592021,0.78246605,0.0030635614,0.1829145,0.030856837,0.000022740976],"about_ca_topic_score_codex":0.0013281178,"about_ca_topic_score_gemma":0.0015456341,"teacher_disagreement_score":0.0021200508,"about_ca_system_score_codex":0.0012133099,"about_ca_system_score_gemma":0.001093745,"threshold_uncertainty_score":0.008803248},"labels":[],"label_agreement":null},{"id":"W2950969151","doi":"10.48550/arxiv.1301.7119","title":"How to Meet Asynchronously at Polynomial Cost","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Polynomial; Mathematics","score_opus":0.07055463355348017,"score_gpt":0.18986844584912577,"score_spread":0.1193138122956456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950969151","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15769982,0.0002966192,0.8081158,0.0038719976,0.00024631014,0.00041737765,0.00086352206,0.004096362,0.024392115],"genre_scores_gemma":[0.58163476,0.00030879118,0.39918664,0.00035026384,0.00012669199,0.00049757515,0.0016533012,0.00079467136,0.01544727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9972109,0.0007457294,0.0002082568,0.0007216595,0.00066681806,0.0004467062],"domain_scores_gemma":[0.9892434,0.007066567,0.00092446175,0.0016024809,0.00062266877,0.00054046995],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014848822,0.0011890121,0.0011643087,0.00051376544,0.0015112536,0.0025336323,0.0023288059,0.0016848216,0.013259519],"category_scores_gemma":[0.013366325,0.00080974016,0.0011968389,0.0009405104,0.0012695754,0.0052251327,0.0025922183,0.0018755489,0.0029275876],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017534989,0.0004698022,0.0035120435,0.00088880205,0.00021900715,0.0005060891,0.0010622037,0.54858685,0.0185018,0.15676983,0.026236178,0.24149394],"study_design_scores_gemma":[0.00037379193,0.00015066178,0.0005141904,0.000028732402,0.00007820398,0.00020829827,0.00025988734,0.7984871,0.006055831,0.18311134,0.010695223,0.00003678626],"about_ca_topic_score_codex":0.003341287,"about_ca_topic_score_gemma":0.0043760203,"teacher_disagreement_score":0.013259519,"about_ca_system_score_codex":0.0014429402,"about_ca_system_score_gemma":0.001960174,"threshold_uncertainty_score":0.04435754},"labels":[],"label_agreement":null},{"id":"W2951101008","doi":"10.48550/arxiv.1410.8756","title":"Contraction Obstructions for Connected Graph Searching","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mitacs; University of British Columbia","funders":"","keywords":"Monotone polygon; Mathematics; Combinatorics; Connected component; Finite set; Bounded function; Contraction (grammar); Strongly connected component; Graph; Discrete mathematics; Mixed graph; Induced subgraph; Line graph; Voltage graph","score_opus":0.08985249067486402,"score_gpt":0.21259637295848705,"score_spread":0.12274388228362303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951101008","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5852794,0.00051945104,0.37609398,0.0015069179,0.000069461224,0.00018095237,0.0005505329,0.00043384192,0.035365358],"genre_scores_gemma":[0.9478488,0.0003019447,0.04395346,0.00022360313,0.000064178574,0.0002147841,0.0004288889,0.00012470885,0.006839496],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986318,0.00037105643,0.00007024663,0.00029132055,0.0003321884,0.00030343837],"domain_scores_gemma":[0.9921354,0.005035428,0.0006762562,0.0006848136,0.00024182492,0.0012261573],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014086834,0.0007322301,0.0014115457,0.0014587513,0.0012554216,0.0023469152,0.0016431552,0.0012877629,0.007229542],"category_scores_gemma":[0.010290856,0.0005312628,0.001635782,0.0012856048,0.0034876112,0.004703533,0.003358953,0.002772525,0.00042063053],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00030253967,0.00011527285,0.0016841254,0.00019853793,0.000052218038,0.00026588704,0.00043105157,0.05738326,0.004035573,0.92096746,0.0016595887,0.012904439],"study_design_scores_gemma":[0.000066515,0.00010058208,0.0008423896,0.000034641464,0.00003453657,0.00017180061,0.00013891357,0.2553347,0.0012921956,0.73902583,0.0029246167,0.000033363147],"about_ca_topic_score_codex":0.0013646394,"about_ca_topic_score_gemma":0.0013925511,"teacher_disagreement_score":0.007229542,"about_ca_system_score_codex":0.0013947496,"about_ca_system_score_gemma":0.0009990551,"threshold_uncertainty_score":0.02418518},"labels":[],"label_agreement":null},{"id":"W2951207568","doi":"10.48550/arxiv.1306.1956","title":"Rendezvous of Two Robots with Constant Memory","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Rendezvous; Robot; Asynchronous communication; Computer science; Constant (computer programming); Transmission (telecommunications); State (computer science); Mobile robot; Class (philosophy); Finite-state machine; Distributed computing; Artificial intelligence; Computer network; Algorithm; Telecommunications; Engineering; Programming language","score_opus":0.07363641634376226,"score_gpt":0.19393732967384414,"score_spread":0.12030091333008187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951207568","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8271089,0.00056457735,0.15933849,0.00049039844,0.000050490853,0.000040773048,0.00007642403,0.00023307846,0.012096935],"genre_scores_gemma":[0.9870051,0.00014409881,0.009709654,0.000034889843,0.000015903752,0.00003908394,0.000045884757,0.00002530505,0.0029801046],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99916637,0.00020650298,0.00003530283,0.00019108642,0.00015248127,0.00024835955],"domain_scores_gemma":[0.995802,0.0025253887,0.0007474795,0.00043052845,0.00016653194,0.00032808963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010552432,0.00069878454,0.00094474235,0.0006235276,0.0010163506,0.0015234164,0.0017210516,0.0015167805,0.0038526834],"category_scores_gemma":[0.0073669837,0.00042884552,0.000761389,0.000498234,0.00322794,0.0031101066,0.0034422465,0.0010698986,0.00029203197],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008519556,0.00013041125,0.0022628475,0.00019444252,0.00009274179,0.00073820184,0.00059508265,0.7194663,0.0107990205,0.2535988,0.00062050764,0.010649711],"study_design_scores_gemma":[0.0001233309,0.0001979283,0.0004850379,0.000019782367,0.000035208177,0.000096580006,0.000223972,0.92269605,0.004532221,0.070576884,0.000979939,0.000033022894],"about_ca_topic_score_codex":0.003208994,"about_ca_topic_score_gemma":0.0012886057,"teacher_disagreement_score":0.0038526834,"about_ca_system_score_codex":0.0010830129,"about_ca_system_score_gemma":0.0004970476,"threshold_uncertainty_score":0.012888551},"labels":[],"label_agreement":null},{"id":"W2951591595","doi":"10.1145/3323165.3323173","title":"Approximation of Scheduling with Calibrations on Multiple Machines (Brief Announcement)","year":2019,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China; City University of Hong Kong; National Science Foundation","keywords":"Computer science; Scheduling (production processes); Approximation algorithm; Schedule; Time complexity; Job shop scheduling; Constant (computer programming); Mathematical optimization; Running time; Algorithm; Parallel computing; Mathematics; Programming language; Operating system","score_opus":0.015338870186721887,"score_gpt":0.2356097280264979,"score_spread":0.220270857839776,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951591595","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02050432,0.003388842,0.9660591,0.0015497799,0.0003335843,0.00010274056,0.00021665177,0.00073197274,0.007112957],"genre_scores_gemma":[0.56359774,0.0047074095,0.41937536,0.00060695194,0.0010715429,0.00035678264,0.0007618181,0.00041982735,0.009102626],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99753284,0.0010015834,0.000093176975,0.00050040294,0.00051158277,0.0003603686],"domain_scores_gemma":[0.9959714,0.002495329,0.00052364427,0.00055674044,0.00023802227,0.0002148499],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030916696,0.0015263306,0.0018435472,0.0009959115,0.0006305694,0.0014963889,0.0024475479,0.0017341495,0.00476258],"category_scores_gemma":[0.011214107,0.001236614,0.001859386,0.0029816236,0.0015202196,0.0029848518,0.0019580147,0.0040871943,0.0009275666],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029720273,0.000097802294,0.0005799589,0.00024737362,0.00006894763,0.00008314879,0.000072521725,0.8821936,0.001606724,0.061500315,0.006867762,0.046384618],"study_design_scores_gemma":[0.000040537772,0.000067919726,0.00024818597,0.00001944523,0.000013479442,0.000047764122,0.000010407715,0.9573689,0.00044986958,0.038720574,0.0030005437,0.00001241183],"about_ca_topic_score_codex":0.0036207808,"about_ca_topic_score_gemma":0.0020851812,"teacher_disagreement_score":0.00476258,"about_ca_system_score_codex":0.0025296551,"about_ca_system_score_gemma":0.0015378607,"threshold_uncertainty_score":0.018353999},"labels":[],"label_agreement":null},{"id":"W2951631472","doi":"10.1016/j.tcs.2020.06.034","title":"Gathering in the plane of location-aware robots in the presence of spies","year":2020,"lang":"en","type":"preprint","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Computer science; Trajectory; Cartesian coordinate system; Mobile robot; Set (abstract data type); Adversary; Competitive analysis; Upper and lower bounds; Artificial intelligence; Distributed computing; Mathematics; Computer security; Geometry","score_opus":0.03225027025388177,"score_gpt":0.2892882062314384,"score_spread":0.25703793597755664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951631472","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30850798,0.00087064883,0.6709558,0.0011369792,0.00007675206,0.00010993229,0.00031011272,0.0002506565,0.017781096],"genre_scores_gemma":[0.91531336,0.00074524625,0.07446315,0.00012212878,0.00009157987,0.00010125199,0.00032119686,0.00006676245,0.008775375],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991454,0.00029984838,0.000028379067,0.00020866994,0.00018034164,0.00013737722],"domain_scores_gemma":[0.99747854,0.0013930663,0.00051618146,0.00016856939,0.00021126808,0.00023228765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010192989,0.0009888512,0.0013842368,0.0011705725,0.0014197194,0.0025553217,0.0016021056,0.0021937222,0.0018627119],"category_scores_gemma":[0.006124258,0.0010307236,0.00080905017,0.0012611726,0.0019765378,0.003306768,0.0037908433,0.001493443,0.0004215715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066300365,0.00011466005,0.0023822845,0.00019602604,0.00012638794,0.00061338616,0.0005709808,0.8874967,0.0066318014,0.079383254,0.0024429068,0.019378552],"study_design_scores_gemma":[0.000026012,0.000087906286,0.00054351083,0.000015887796,0.000019735004,0.00013039929,0.0002259116,0.96379495,0.0008480965,0.033338685,0.0009497584,0.000019183613],"about_ca_topic_score_codex":0.0064198086,"about_ca_topic_score_gemma":0.0036533265,"teacher_disagreement_score":0.0064198086,"about_ca_system_score_codex":0.000943728,"about_ca_system_score_gemma":0.00077280885,"threshold_uncertainty_score":0.012764871},"labels":[],"label_agreement":null},{"id":"W2951649450","doi":"","title":"Distributed Computing by Mobile Robots: Solving the Uniform Circle Formation Problem","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Asynchronous communication; Robot; Computer science; Mobile robot; Simple (philosophy); Set (abstract data type); Rigidity (electromagnetism); Distributed computing; Plane (geometry); Theoretical computer science; Topology (electrical circuits); Mathematics; Artificial intelligence; Combinatorics; Geometry; Engineering","score_opus":0.036903703057255315,"score_gpt":0.18972526201599554,"score_spread":0.15282155895874022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951649450","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3050475,0.0004469927,0.68243366,0.0010589916,0.0000554687,0.000112251146,0.00008569125,0.00028918398,0.0104703],"genre_scores_gemma":[0.88830614,0.00012441174,0.10882036,0.00006233464,0.000024678284,0.00012432692,0.000074557436,0.000033436747,0.0024298234],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994404,0.00023950482,0.000023321589,0.00013493671,0.0000732361,0.00008850176],"domain_scores_gemma":[0.9983236,0.001137321,0.00014269562,0.00018999292,0.00009881352,0.00010760163],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008700229,0.00039911547,0.00082517386,0.00029374872,0.00062392093,0.00071878795,0.00093376654,0.0008213064,0.0016823186],"category_scores_gemma":[0.004169688,0.0002797601,0.00042437174,0.0005210631,0.0012627894,0.0011090778,0.0015348201,0.00068409834,0.00020318932],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019342038,0.000058433776,0.0012667127,0.00012879967,0.00003768266,0.00014456928,0.000189798,0.892681,0.0019227398,0.07854644,0.0014709351,0.023359556],"study_design_scores_gemma":[0.00005794223,0.00003480825,0.00012414275,0.000005997123,0.000005576734,0.000021599006,0.000048706333,0.957265,0.00088038424,0.04073702,0.0008142829,0.0000045466345],"about_ca_topic_score_codex":0.0024764931,"about_ca_topic_score_gemma":0.0018198192,"teacher_disagreement_score":0.0024764931,"about_ca_system_score_codex":0.0006364399,"about_ca_system_score_gemma":0.0008716671,"threshold_uncertainty_score":0.0056278706},"labels":[],"label_agreement":null},{"id":"W2951723330","doi":"10.48550/arxiv.1306.0771","title":"The Frequent Items Problem in Online Streaming under Various Performance Measures","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Danmarks Frie Forskningsfond; University of Waterloo","keywords":"Competitive analysis; Computer science; Order (exchange); Competitive advantage; Interval (graph theory); Operations research; Mathematics; Marketing; Upper and lower bounds; Business","score_opus":0.08208682290811997,"score_gpt":0.19777937430079204,"score_spread":0.11569255139267207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951723330","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17305131,0.006998323,0.7935152,0.0030720055,0.00032972018,0.00040003832,0.00084405893,0.0004888173,0.021300606],"genre_scores_gemma":[0.78171766,0.0033398382,0.20721182,0.0004185663,0.0015904775,0.00054173736,0.0011651907,0.00030810916,0.003706657],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9834184,0.008303766,0.0006832326,0.0019673393,0.0043582153,0.0012690224],"domain_scores_gemma":[0.8854773,0.09668926,0.0053883954,0.003896592,0.006017149,0.0025313422],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019191375,0.0021938768,0.003660667,0.0037172276,0.0017887453,0.0061787576,0.004023548,0.002758778,0.0044452637],"category_scores_gemma":[0.079214014,0.00062094646,0.0014074852,0.005759092,0.0025393267,0.011880664,0.0028963306,0.003301939,0.00063717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002032498,0.0013367286,0.008782482,0.0014748,0.00047088246,0.0003101491,0.0006096461,0.33376145,0.0031569821,0.4765556,0.010912774,0.16059606],"study_design_scores_gemma":[0.00006529513,0.00048808628,0.0016252367,0.00007839115,0.00009388189,0.00034129916,0.00029810358,0.8140306,0.0012950668,0.17926177,0.0023702055,0.000052131043],"about_ca_topic_score_codex":0.0013287732,"about_ca_topic_score_gemma":0.00088158227,"teacher_disagreement_score":0.019191375,"about_ca_system_score_codex":0.0034983633,"about_ca_system_score_gemma":0.0023861818,"threshold_uncertainty_score":0.10149485},"labels":[],"label_agreement":null},{"id":"W2951748104","doi":"10.1016/j.tcs.2018.10.018","title":"Gathering in dynamic rings","year":2018,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rendezvous; Traverse; Computer science; Constructive; Focus (optics); Characterization (materials science); Class (philosophy); Interval (graph theory); Time complexity; Set (abstract data type); Network topology; Topology (electrical circuits); Theoretical computer science; Mathematics; Algorithm; Combinatorics; Artificial intelligence; Computer network; Process (computing)","score_opus":0.008158914473346624,"score_gpt":0.26923965560583335,"score_spread":0.26108074113248675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951748104","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2166945,0.0017096543,0.67964447,0.0035350139,0.00026509658,0.00025936493,0.0006130201,0.001086069,0.09619282],"genre_scores_gemma":[0.8655599,0.0011729723,0.082474075,0.00029487026,0.00032387604,0.00018034257,0.0004994232,0.00026858642,0.04922602],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982552,0.00065656705,0.000072876785,0.00034640633,0.00033956644,0.0003294303],"domain_scores_gemma":[0.9946142,0.002829487,0.00065312505,0.000925084,0.00038028823,0.0005979624],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020509015,0.0006087965,0.001455119,0.0018785862,0.0030069835,0.0033603914,0.0015037261,0.001208578,0.014392539],"category_scores_gemma":[0.008887503,0.0007418798,0.0010376737,0.002078633,0.002120072,0.0079231,0.004108587,0.0024512236,0.0017996038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018839525,0.00006268435,0.00037040736,0.00012230597,0.0000291845,0.00008698719,0.00030381005,0.021400359,0.0011953504,0.951996,0.005121669,0.019123018],"study_design_scores_gemma":[0.000047648722,0.0000768352,0.0002756565,0.000036762678,0.00003812854,0.0001879656,0.0001896877,0.1186953,0.0013456601,0.86821854,0.010862661,0.00002515945],"about_ca_topic_score_codex":0.0008323979,"about_ca_topic_score_gemma":0.00078373635,"teacher_disagreement_score":0.014392539,"about_ca_system_score_codex":0.0013928781,"about_ca_system_score_gemma":0.0008740116,"threshold_uncertainty_score":0.048147798},"labels":[],"label_agreement":null},{"id":"W2951833857","doi":"10.48550/arxiv.1303.5740","title":"High Level Path Planning with Uncertainty","year":2013,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Motion planning; Shortest path problem; Computer science; Longest path problem; Path (computing); Mathematical optimization; Graph; Markov decision process; Any-angle path planning; Process (computing); Markov process; Theoretical computer science; Artificial intelligence; Mathematics","score_opus":0.1240046288587581,"score_gpt":0.19752356758093065,"score_spread":0.07351893872217255,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951833857","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0048697935,0.00017952741,0.9926103,0.000118827746,0.000015685942,0.000018521465,0.00009530701,0.00021207005,0.0018800294],"genre_scores_gemma":[0.3482021,0.000725998,0.6461261,0.00012809178,0.00005173984,0.00016761597,0.0005743835,0.00018506992,0.0038389643],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990939,0.00029207862,0.0000516922,0.00023294869,0.0002318284,0.00009757989],"domain_scores_gemma":[0.9990625,0.0006316945,0.00006516354,0.00011475255,0.00008311794,0.000042785618],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080675835,0.0008851253,0.000990935,0.00059607194,0.0006082704,0.0012761451,0.0011286975,0.00096700026,0.0027880643],"category_scores_gemma":[0.002453001,0.00052877085,0.0010559165,0.0011922227,0.0012870382,0.0020532375,0.0021204522,0.0016698501,0.00043959793],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000039943738,0.00001724467,0.0002631434,0.0001116913,0.000031729123,0.000061172956,0.00006553068,0.8158741,0.0008138553,0.14460349,0.0016973384,0.03642072],"study_design_scores_gemma":[0.0000066702964,0.000015981705,0.000060567476,0.00000942907,0.000007918831,0.000019069403,0.00001583767,0.8773876,0.0004732256,0.119836606,0.0021596618,0.0000073633537],"about_ca_topic_score_codex":0.0053073824,"about_ca_topic_score_gemma":0.004922368,"teacher_disagreement_score":0.0053073824,"about_ca_system_score_codex":0.0013248387,"about_ca_system_score_gemma":0.0014870522,"threshold_uncertainty_score":0.010552943},"labels":[],"label_agreement":null},{"id":"W2951958562","doi":"10.20382/jocg.v8i1a7","title":"Competitive local routing with constraints","year":2016,"lang":"en","type":"article","venue":"University of Southern Denmark Research Portal (University of Southern Denmark)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Exploratory Research for Advanced Technology; Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Danmarks Frie Forskningsfond","keywords":"Routing (electronic design automation); Computer science; Computer network","score_opus":0.023354628743987627,"score_gpt":0.23012677153492506,"score_spread":0.20677214279093742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951958562","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11055553,0.0011934428,0.82716835,0.0015328035,0.00015536035,0.00063883135,0.0022241878,0.0034857462,0.05304569],"genre_scores_gemma":[0.60802394,0.0006248184,0.36212984,0.000609909,0.00012255239,0.0007790595,0.0032530432,0.000716075,0.023740606],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977823,0.00045841458,0.0001138395,0.0006150198,0.00053730473,0.0004931592],"domain_scores_gemma":[0.995883,0.001747078,0.00038463547,0.0012005059,0.0005147379,0.00026999277],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009833772,0.0014705509,0.0019134732,0.0008990595,0.002149517,0.003208715,0.004051366,0.0021210911,0.017956192],"category_scores_gemma":[0.00691199,0.0007507971,0.0010443327,0.0027164589,0.0011999855,0.0052710385,0.0041001006,0.0017773261,0.003744097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015044904,0.00042385602,0.0019408939,0.0009944615,0.0001488876,0.00058076973,0.0006055801,0.5427736,0.012454128,0.19803256,0.04099731,0.19954355],"study_design_scores_gemma":[0.00015262158,0.00024169125,0.0003817514,0.000039418872,0.00005421036,0.0004045948,0.00018506157,0.8735766,0.0045247413,0.10436053,0.01601605,0.0000627726],"about_ca_topic_score_codex":0.0064258766,"about_ca_topic_score_gemma":0.012376386,"teacher_disagreement_score":0.017956192,"about_ca_system_score_codex":0.0028973978,"about_ca_system_score_gemma":0.0025207107,"threshold_uncertainty_score":0.06006944},"labels":[],"label_agreement":null},{"id":"W2952262284","doi":"","title":"On the push&pull protocol for rumour spreading","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Combinatorics; Vertex (graph theory); Logarithm; Asynchronous communication; Binary logarithm; Omega; Discrete mathematics; Mathematics; Graph; Computer science; Physics; Telecommunications","score_opus":0.1495498912844622,"score_gpt":0.2382169472345855,"score_spread":0.08866705595012331,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952262284","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027885444,0.0011818699,0.9486522,0.0021557992,0.00034812881,0.00041924,0.00031169332,0.0010171394,0.018028475],"genre_scores_gemma":[0.6032358,0.0038271914,0.36329272,0.0018977852,0.0011119148,0.002129584,0.0011326813,0.0007391953,0.022633143],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9947213,0.0019485048,0.00028213544,0.00086810364,0.0015316322,0.00064847263],"domain_scores_gemma":[0.9836623,0.010663961,0.0010058847,0.0027180992,0.0012434837,0.00070634874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0051754713,0.0017723123,0.0021712398,0.0019470406,0.00315768,0.0028653434,0.0036172147,0.0026711014,0.005827099],"category_scores_gemma":[0.02338555,0.0010881163,0.0019998194,0.0023793017,0.0047952193,0.01081347,0.0068194997,0.0060655344,0.0021826955],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014841546,0.00022486268,0.001115432,0.0005029135,0.00014697881,0.0007916042,0.0012729939,0.12938416,0.013539627,0.7889601,0.011361131,0.05121598],"study_design_scores_gemma":[0.00027308695,0.00022565552,0.00030552133,0.000092117065,0.00010046749,0.00029316425,0.00018555262,0.596736,0.0039739087,0.3846928,0.012987976,0.0001337077],"about_ca_topic_score_codex":0.004114708,"about_ca_topic_score_gemma":0.0026393787,"teacher_disagreement_score":0.005827099,"about_ca_system_score_codex":0.0026533194,"about_ca_system_score_gemma":0.0028068812,"threshold_uncertainty_score":0.02737081},"labels":[],"label_agreement":null},{"id":"W2952321143","doi":"10.23638/dmtcs-21-3-20","title":"Search-and-Fetch with 2 Robots on a Disk: Wireless and Face-to-Face Communication Models","year":2019,"lang":"en","type":"article","venue":"Discrete Mathematics & Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; McMaster University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Face (sociological concept); Wireless; Mathematics; Robot; Fetch; Computer science; Artificial intelligence; Telecommunications; Sociology; Geology; Social science","score_opus":0.019253888759540833,"score_gpt":0.26933908011555946,"score_spread":0.25008519135601864,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952321143","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10336371,0.0012353484,0.8718308,0.0029101362,0.00019963864,0.00022190291,0.00042008574,0.00032038664,0.019497966],"genre_scores_gemma":[0.85244995,0.0014068796,0.11405672,0.00048827723,0.00030432086,0.0006126343,0.00030877793,0.00017650104,0.030195814],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978308,0.0007585801,0.00008345094,0.0004631671,0.00039945001,0.0004644822],"domain_scores_gemma":[0.98849773,0.008103013,0.0013397713,0.0009868958,0.00053756754,0.0005349771],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022246798,0.0015780599,0.0021922865,0.0010795144,0.0016442711,0.0024766522,0.005847133,0.0044083656,0.009783964],"category_scores_gemma":[0.012791843,0.000826236,0.0014101671,0.0016122406,0.0025687034,0.007957116,0.0039202883,0.0029372144,0.0016336542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045569675,0.00018978918,0.0006051394,0.0002488601,0.0000461058,0.00043543847,0.00035956752,0.81784654,0.0015138134,0.15819374,0.003557699,0.016547564],"study_design_scores_gemma":[0.000037471425,0.000072342074,0.00007151604,0.0000110446335,0.000010941077,0.0000820555,0.000095814285,0.96279436,0.00039310273,0.035505924,0.0009078971,0.000017498236],"about_ca_topic_score_codex":0.003403295,"about_ca_topic_score_gemma":0.0024973203,"teacher_disagreement_score":0.009783964,"about_ca_system_score_codex":0.0017407816,"about_ca_system_score_gemma":0.00097167655,"threshold_uncertainty_score":0.03273058},"labels":[],"label_agreement":null},{"id":"W2952754000","doi":"10.7155/jgaa.00421","title":"Lower Bounds for Graph Exploration Using Local Policies","year":2017,"lang":"en","type":"preprint","venue":"Journal of Graph Algorithms and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bounded function; Graph; Computer science; Abstraction; Exponential function; Theoretical computer science; Enhanced Data Rates for GSM Evolution; Robot; Combinatorics; Mathematics; Discrete mathematics; Mathematical optimization; Artificial intelligence","score_opus":0.06704610915214952,"score_gpt":0.3427686469278052,"score_spread":0.27572253777565564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952754000","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030139575,0.0066808895,0.90122765,0.004225761,0.00038095887,0.00031914716,0.0011564129,0.0023923838,0.053477235],"genre_scores_gemma":[0.6563401,0.007266785,0.30342895,0.0020364765,0.0009685309,0.001617159,0.0024082505,0.0035951675,0.022338483],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9916283,0.0021613857,0.00033189307,0.0014583769,0.0019731603,0.0024468023],"domain_scores_gemma":[0.9373668,0.049460344,0.0026504002,0.0054109944,0.002126956,0.0029845424],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0069780517,0.00438269,0.0033406944,0.0030135307,0.002225152,0.007212249,0.007059452,0.003563166,0.023016695],"category_scores_gemma":[0.0517272,0.0014473206,0.0035269894,0.0038074178,0.0040748413,0.015768975,0.0071909246,0.011144319,0.0046209567],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009308908,0.00054452557,0.0033691507,0.0016079581,0.00024828737,0.00026851453,0.0007336831,0.4906038,0.005535916,0.3858626,0.020012874,0.09028184],"study_design_scores_gemma":[0.0000669436,0.00017523851,0.00042336946,0.00022424037,0.00012476121,0.00021182437,0.00013624091,0.7151151,0.00222585,0.27581146,0.005431301,0.00005375121],"about_ca_topic_score_codex":0.002117627,"about_ca_topic_score_gemma":0.0036671164,"teacher_disagreement_score":0.023016695,"about_ca_system_score_codex":0.005323283,"about_ca_system_score_gemma":0.004038329,"threshold_uncertainty_score":0.07699853},"labels":[],"label_agreement":null},{"id":"W2952798587","doi":"10.48550/arxiv.cs/0605070","title":"Curve Shortening and the Rendezvous Problem for Mobile Autonomous Robots","year":2006,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Rendezvous; Mobile robot; Computer science; Robot; Artificial intelligence; Aerospace engineering; Engineering; Spacecraft","score_opus":0.03893205192265286,"score_gpt":0.28080729971336515,"score_spread":0.2418752477907123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952798587","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3196099,0.0021953278,0.6605311,0.0017404307,0.00008725529,0.000078734156,0.00012924813,0.00020634064,0.015421598],"genre_scores_gemma":[0.8890421,0.0012363318,0.09773206,0.00006079471,0.00007578359,0.00009417687,0.00017434474,0.00007675562,0.01150762],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997838,0.0000699296,0.000009377148,0.000054066735,0.00005268037,0.000030081766],"domain_scores_gemma":[0.99949193,0.00028950835,0.000086566055,0.000040594794,0.000033993347,0.000057336023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005465684,0.00048226715,0.0005524518,0.0005961975,0.00069153064,0.00075041514,0.0006394434,0.0010165524,0.0016015924],"category_scores_gemma":[0.0021122573,0.00026636332,0.00038832347,0.0006831546,0.0018476986,0.0013887065,0.0011310941,0.00064710557,0.00018746841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014387692,0.000038756603,0.0011855535,0.00011132174,0.000026950474,0.00016440664,0.0002788696,0.75758845,0.0027268757,0.18463296,0.0020735662,0.051028464],"study_design_scores_gemma":[0.000030348696,0.000050598315,0.00037578534,0.000013688051,0.000007878698,0.00006256638,0.00009504725,0.87080324,0.00095486216,0.123720296,0.0038728355,0.000012758959],"about_ca_topic_score_codex":0.0035843875,"about_ca_topic_score_gemma":0.0021629795,"teacher_disagreement_score":0.0035843875,"about_ca_system_score_codex":0.0010069448,"about_ca_system_score_gemma":0.00054579426,"threshold_uncertainty_score":0.00730592},"labels":[],"label_agreement":null},{"id":"W2952864736","doi":"10.48550/arxiv.1506.07952","title":"Tradeoffs Between Cost and Information for Rendezvous and Treasure Hunt","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Treasure; Rendezvous; Advice (programming); Combinatorics; Omega; Upper and lower bounds; Binary logarithm; Traverse; Mathematics; Discrete mathematics; Computer science; Physics; Mathematical analysis; Geography","score_opus":0.1335887771927533,"score_gpt":0.21038719835329264,"score_spread":0.07679842116053934,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952864736","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48080364,0.0069313403,0.4395822,0.011729028,0.00034620348,0.00035388608,0.0015021114,0.0017873673,0.0569642],"genre_scores_gemma":[0.9056376,0.0025050552,0.08493782,0.00049350655,0.00018237626,0.00022325481,0.00048808975,0.0005260825,0.0050061964],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9964749,0.001061349,0.00014343845,0.0006088108,0.0008136151,0.0008978687],"domain_scores_gemma":[0.91851234,0.0715976,0.002207141,0.00460175,0.0012286451,0.0018525008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035906925,0.0015770663,0.0017840024,0.0015200147,0.0013265224,0.003072916,0.004216849,0.0033277597,0.007745855],"category_scores_gemma":[0.05032088,0.0011003494,0.0009582822,0.0015885488,0.0027467364,0.011969768,0.0031511257,0.0030539627,0.0008677813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030258303,0.00045350002,0.0035051221,0.0010270142,0.00017176426,0.00040178624,0.0006121282,0.7311722,0.019484999,0.14759192,0.00724322,0.08531048],"study_design_scores_gemma":[0.00013587633,0.0003531786,0.0014652178,0.00011418508,0.00010847746,0.00037762724,0.00029966835,0.8730238,0.0071680024,0.11399979,0.002869169,0.00008504869],"about_ca_topic_score_codex":0.0028751064,"about_ca_topic_score_gemma":0.0046858704,"teacher_disagreement_score":0.007745855,"about_ca_system_score_codex":0.0031586166,"about_ca_system_score_gemma":0.001743328,"threshold_uncertainty_score":0.025912464},"labels":[],"label_agreement":null},{"id":"W2952911535","doi":"10.48550/arxiv.1407.1428","title":"Fast Rendezvous with Advice","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Advice (programming); Psychology; Computer science; Engineering; Aerospace engineering","score_opus":0.04878298937957758,"score_gpt":0.1774679760883414,"score_spread":0.1286849867087638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2952911535","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23966567,0.000853434,0.734264,0.00086327584,0.000109014225,0.00024620304,0.0006215482,0.0056245644,0.017752279],"genre_scores_gemma":[0.73695225,0.00032721282,0.2506897,0.00019660885,0.000043935644,0.0002501269,0.0008313297,0.00051196147,0.010196958],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983602,0.00025023578,0.000076008255,0.00047563817,0.00034437358,0.0004933903],"domain_scores_gemma":[0.99563533,0.0027796926,0.00036058604,0.0007008132,0.00025754713,0.00026603925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010349888,0.0013767022,0.0012607283,0.0005222527,0.0010627442,0.0011944597,0.0020812557,0.0015434074,0.005988465],"category_scores_gemma":[0.0075436523,0.0006932526,0.00082101306,0.00061131554,0.0017300583,0.0029147132,0.0028355308,0.0016501718,0.0012111565],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002461794,0.00020313093,0.0033351583,0.00070412416,0.00012369466,0.0005929427,0.0009926112,0.77069974,0.033894967,0.0647568,0.007656525,0.11457855],"study_design_scores_gemma":[0.00022819811,0.00030077944,0.0006922253,0.00005068127,0.00003543857,0.00024224287,0.00024232305,0.9130873,0.013143384,0.06519001,0.006752233,0.000035209763],"about_ca_topic_score_codex":0.0068481257,"about_ca_topic_score_gemma":0.006517705,"teacher_disagreement_score":0.0068481257,"about_ca_system_score_codex":0.0012242134,"about_ca_system_score_gemma":0.0013970748,"threshold_uncertainty_score":0.020033479},"labels":[],"label_agreement":null},{"id":"W2953217343","doi":"10.48550/arxiv.1807.08640","title":"Average Case - Worst Case Tradeoffs for Evacuating 2 Robots from the Disk in the Face-to-Face Model","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Face (sociological concept); Computer science; Simple (philosophy); Robot; Mathematical optimization; Algorithm; Mathematics; Artificial intelligence","score_opus":0.16573077380450865,"score_gpt":0.24106450923262598,"score_spread":0.07533373542811733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953217343","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23756318,0.0018439116,0.7265666,0.0044001103,0.00030287783,0.00031663984,0.00086395897,0.00087315746,0.027269641],"genre_scores_gemma":[0.8544996,0.00069645303,0.137676,0.0005693407,0.00020438117,0.0003161725,0.0004997109,0.00045371498,0.0050846124],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9908228,0.004079266,0.00029324894,0.0014759997,0.0015367463,0.0017919121],"domain_scores_gemma":[0.96332455,0.028153585,0.0017801841,0.003941677,0.0012099047,0.001590103],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009910207,0.0021210397,0.0025192017,0.0010061982,0.0018263801,0.003886224,0.0049802233,0.0028662442,0.009036905],"category_scores_gemma":[0.034826815,0.0011746958,0.0015856548,0.0014177226,0.0020879554,0.008681146,0.0029317846,0.003218535,0.0010074548],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00123947,0.00035698846,0.0010570799,0.00023802668,0.000105791354,0.00011717005,0.00011449151,0.9135019,0.0021430186,0.04756148,0.0046218536,0.02894266],"study_design_scores_gemma":[0.00004216352,0.00021245019,0.000388378,0.000020796339,0.000037671343,0.00012384099,0.000117446936,0.95597684,0.0009767249,0.041311752,0.0007660171,0.000025769003],"about_ca_topic_score_codex":0.003455725,"about_ca_topic_score_gemma":0.004391415,"teacher_disagreement_score":0.009910207,"about_ca_system_score_codex":0.0032389928,"about_ca_system_score_gemma":0.0030065074,"threshold_uncertainty_score":0.05241084},"labels":[],"label_agreement":null},{"id":"W2953266086","doi":"10.48550/arxiv.1211.6039","title":"Rendezvous of two robots with visible bits","year":2012,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Rendezvous; Asynchronous communication; Computer science; Robot; Constant (computer programming); Topology (electrical circuits); Zero (linguistics); Algorithm; Mathematics; Artificial intelligence; Combinatorics; Physics","score_opus":0.09170811491101132,"score_gpt":0.20737843513345372,"score_spread":0.1156703202224424,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953266086","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5233005,0.00033377268,0.4639235,0.0007238004,0.000053083604,0.00008393613,0.0001567779,0.00029519506,0.011129456],"genre_scores_gemma":[0.9460236,0.00012057754,0.048572138,0.000060158603,0.000017078584,0.00008261599,0.00010652954,0.000049702394,0.004967662],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987382,0.00045420436,0.00004570045,0.00028821002,0.00019473852,0.0002788692],"domain_scores_gemma":[0.9963548,0.0024569004,0.00049368636,0.00032220563,0.00014565124,0.00022684118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011422782,0.00090910273,0.0009898178,0.0005403877,0.0011421862,0.0010884202,0.0015394285,0.0015790181,0.0029029674],"category_scores_gemma":[0.006669124,0.0004933733,0.000964588,0.00065022416,0.0026813517,0.0024061014,0.002042371,0.0011972864,0.00036542205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007357914,0.00011731059,0.0013836884,0.00014618083,0.00007589398,0.00031922437,0.0002533822,0.818868,0.0057929116,0.16018648,0.0008609126,0.011260335],"study_design_scores_gemma":[0.00013637562,0.0001134485,0.0002215578,0.000011127199,0.00002037967,0.00005264939,0.000082511695,0.9062537,0.0030078988,0.08920568,0.0008741618,0.000020554638],"about_ca_topic_score_codex":0.0033986482,"about_ca_topic_score_gemma":0.002279455,"teacher_disagreement_score":0.0033986482,"about_ca_system_score_codex":0.0012462812,"about_ca_system_score_gemma":0.0007132367,"threshold_uncertainty_score":0.009711325},"labels":[],"label_agreement":null},{"id":"W2953288228","doi":"10.48550/arxiv.1508.02471","title":"Time Versus Cost Tradeoffs for Deterministic Rendezvous in Networks","year":2015,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Benchmark (surveying); Upper and lower bounds; Node (physics); Computer science; Integer (computer science); Enhanced Data Rates for GSM Evolution; Binary logarithm; Set (abstract data type); Mathematics; Combinatorics; Discrete mathematics; Algorithm; Physics; Artificial intelligence","score_opus":0.16660370196039329,"score_gpt":0.23248044396620623,"score_spread":0.06587674200581295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953288228","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43765318,0.0027562298,0.5284455,0.0040324093,0.000106786276,0.00032510984,0.0006633822,0.0013112182,0.024706082],"genre_scores_gemma":[0.8787882,0.0010800504,0.11431891,0.00018590994,0.000072134586,0.0002904314,0.00029325244,0.00040736425,0.004563804],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99436224,0.0022880558,0.00025447438,0.00080164685,0.0011893002,0.0011043072],"domain_scores_gemma":[0.9594308,0.033546932,0.002025818,0.0030308967,0.0008486278,0.0011169427],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005789165,0.0013047875,0.0015023341,0.0014805547,0.0018518083,0.0038163592,0.0025759267,0.0024463676,0.005009697],"category_scores_gemma":[0.03434842,0.0009945083,0.001152544,0.0017508994,0.003454044,0.009372331,0.0027139387,0.0017041642,0.00054743985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012424552,0.00015372729,0.0013517158,0.00026930138,0.00006664247,0.00010391616,0.00038862176,0.8479661,0.008378031,0.10771392,0.0015296196,0.030835947],"study_design_scores_gemma":[0.00008878604,0.00017223609,0.00053215213,0.000032827946,0.0000383026,0.00010201673,0.00020334066,0.91602683,0.0031439988,0.07821673,0.0014067532,0.0000360432],"about_ca_topic_score_codex":0.0038825565,"about_ca_topic_score_gemma":0.0045575458,"teacher_disagreement_score":0.005789165,"about_ca_system_score_codex":0.0046856147,"about_ca_system_score_gemma":0.0021448946,"threshold_uncertainty_score":0.03399664},"labels":[],"label_agreement":null},{"id":"W2962742438","doi":"","title":"Square Formation by Asynchronous Oblivious Robots.","year":2016,"lang":"en","type":"article","venue":"Canadian Conference on Computational Geometry","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Computer science; Asynchronous communication; Correctness; Mobile robot; Square (algebra); Theoretical computer science; Degenerate energy levels; Algorithm; Mathematics; Artificial intelligence; Geometry; Physics","score_opus":0.02441196527484058,"score_gpt":0.24285998804405776,"score_spread":0.21844802276921718,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2962742438","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04741784,0.00020421688,0.9424537,0.0002990276,0.00006494713,0.000102463564,0.000048665752,0.00023847634,0.009170639],"genre_scores_gemma":[0.75752765,0.00038598233,0.22938558,0.00016057915,0.00005438592,0.00024032147,0.00016406486,0.000085861626,0.011995643],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994815,0.00015455,0.000026446742,0.00012199298,0.00013926551,0.000076260345],"domain_scores_gemma":[0.9988048,0.00055329717,0.00021613947,0.0002316718,0.00008904384,0.00010511177],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005658781,0.0003826301,0.00038152226,0.00030198367,0.00061965233,0.0006054282,0.0009577665,0.0005481351,0.0022870372],"category_scores_gemma":[0.0029925513,0.0002640623,0.0005784809,0.00033719832,0.0017457247,0.001407459,0.0020959608,0.00074647844,0.00056976586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019835471,0.00004078948,0.0010536513,0.00016326035,0.00004116405,0.00026448152,0.0004579608,0.34890673,0.012231578,0.58996964,0.0020807546,0.044591628],"study_design_scores_gemma":[0.000075186515,0.00012319555,0.00025532313,0.000014547298,0.00001786637,0.00018001648,0.00013269823,0.6879071,0.006811157,0.29701927,0.007444638,0.000018969271],"about_ca_topic_score_codex":0.0011948865,"about_ca_topic_score_gemma":0.0010981571,"teacher_disagreement_score":0.0022870372,"about_ca_system_score_codex":0.0005249825,"about_ca_system_score_gemma":0.0005980018,"threshold_uncertainty_score":0.007650852},"labels":[],"label_agreement":null},{"id":"W2962770134","doi":"10.1109/icdcs.2016.59","title":"Live Exploration of Dynamic Rings","year":2016,"lang":"en","type":"article","venue":"IRIS Research product catalog (Sapienza University of Rome)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science","score_opus":0.05704449905809044,"score_gpt":0.3056773927221618,"score_spread":0.24863289366407137,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2962770134","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40653446,0.0013892804,0.5742485,0.00075554935,0.00004956566,0.00014721142,0.00036383438,0.000405158,0.016106347],"genre_scores_gemma":[0.93166715,0.0004722812,0.06099743,0.00006718729,0.00003620986,0.0000991429,0.00020865852,0.000068158566,0.0063837087],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99909437,0.00035910137,0.00003257422,0.00020254255,0.00012800685,0.00018331292],"domain_scores_gemma":[0.9952473,0.0031817157,0.0005239587,0.00053522,0.00018695601,0.00032485373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013579872,0.0004786457,0.00084244646,0.00048311977,0.0009133466,0.0011378531,0.0013289707,0.0010856873,0.0042300005],"category_scores_gemma":[0.0067837834,0.00044991355,0.0006828096,0.0005089347,0.0012355578,0.00359405,0.0026422169,0.00083714613,0.0002888451],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008949109,0.00013246809,0.0031946404,0.00033878765,0.000098527584,0.00064090174,0.00075906364,0.78361815,0.007079038,0.14478014,0.0026107363,0.055852566],"study_design_scores_gemma":[0.00004868191,0.00017781359,0.0006259481,0.00003145623,0.00002536526,0.00027404123,0.00029498825,0.8933735,0.002580827,0.09907302,0.0034744528,0.000019926478],"about_ca_topic_score_codex":0.0008484433,"about_ca_topic_score_gemma":0.0008462052,"teacher_disagreement_score":0.0042300005,"about_ca_system_score_codex":0.00048703936,"about_ca_system_score_gemma":0.00041972194,"threshold_uncertainty_score":0.014150739},"labels":[],"label_agreement":null},{"id":"W2963114728","doi":"10.1016/j.ic.2016.09.005","title":"Mutual visibility by luminous robots without collisions","year":2016,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":95,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Visibility; Robot; Computer science; Convergence (economics); Computer vision; Plane (geometry); Artificial intelligence; Point (geometry); Topology (electrical circuits); Mathematics; Physics; Geometry; Optics; Combinatorics; Economics","score_opus":0.012703689453455598,"score_gpt":0.2644667625921533,"score_spread":0.25176307313869767,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963114728","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2665323,0.0006249535,0.71692944,0.00097467285,0.000098583245,0.000053667365,0.00010689144,0.00022725461,0.0144521445],"genre_scores_gemma":[0.96448344,0.00015764115,0.02931669,0.00010223782,0.000057738318,0.000056786706,0.0000680181,0.00008938473,0.0056681125],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99828255,0.0005999012,0.00006342747,0.0003503953,0.00035188164,0.00035190428],"domain_scores_gemma":[0.9903674,0.0067333635,0.0012338803,0.0006685582,0.00039050242,0.00060628017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017387037,0.0008715608,0.002027507,0.0010073723,0.0016001839,0.0027648387,0.0021068198,0.002858772,0.0031521672],"category_scores_gemma":[0.01678981,0.001451728,0.0011088232,0.0012412972,0.0031381247,0.0048764125,0.0068169236,0.001860683,0.000416534],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015801153,0.00016155308,0.0032879114,0.00029657708,0.00022875372,0.0006985832,0.0012277665,0.5632069,0.00536092,0.38608593,0.0026894382,0.035175495],"study_design_scores_gemma":[0.00007925597,0.00010534715,0.00070291106,0.000026447911,0.00003830157,0.0001697622,0.00017206285,0.7393546,0.0014744112,0.25672716,0.001112565,0.00003708232],"about_ca_topic_score_codex":0.0024256965,"about_ca_topic_score_gemma":0.001434801,"teacher_disagreement_score":0.0031521672,"about_ca_system_score_codex":0.0010184491,"about_ca_system_score_gemma":0.00091498275,"threshold_uncertainty_score":0.010545015},"labels":[],"label_agreement":null},{"id":"W2963281409","doi":"10.1109/icca.2011.6138087","title":"Optimal sensor configurations for rectangular target detection","year":2011,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"Defence Research and Development Canada","keywords":"Orientation (vector space); Symmetry (geometry); Computer science; Feature (linguistics); Mathematical optimization; Algorithm; Mathematics; Artificial intelligence; Geometry","score_opus":0.044473489210898526,"score_gpt":0.256583193109017,"score_spread":0.21210970389811848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963281409","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.110694736,0.00067357614,0.87697923,0.0003289087,0.000046305573,0.000100738966,0.00027379746,0.00040103478,0.010501613],"genre_scores_gemma":[0.8173872,0.00029128508,0.1800247,0.00010404955,0.000015305814,0.00015755172,0.0002185102,0.000056865283,0.0017444534],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991503,0.00027310674,0.000046708705,0.00021347424,0.00017120273,0.00014525186],"domain_scores_gemma":[0.9987208,0.0006447361,0.00024207737,0.00012606122,0.00018347836,0.00008281343],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011254819,0.0007200008,0.00083696353,0.00086351816,0.0003837093,0.00074323744,0.0006707352,0.0008730748,0.0028880292],"category_scores_gemma":[0.0049458873,0.00073961343,0.00039612502,0.00062553684,0.0011160765,0.0011383845,0.0015117755,0.00049740024,0.000713163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009519616,0.000082719176,0.002220953,0.00023102992,0.000067064226,0.00039437978,0.0002913882,0.8064934,0.026986608,0.077147126,0.0029258654,0.08220741],"study_design_scores_gemma":[0.00011866582,0.00021991653,0.0009921339,0.000048624897,0.00003042758,0.00027334623,0.00014329045,0.9286499,0.008408779,0.059110142,0.001945214,0.00005952082],"about_ca_topic_score_codex":0.0007396843,"about_ca_topic_score_gemma":0.0009113216,"teacher_disagreement_score":0.0028880292,"about_ca_system_score_codex":0.0005431442,"about_ca_system_score_gemma":0.0007017115,"threshold_uncertainty_score":0.0096613765},"labels":[],"label_agreement":null},{"id":"W2963349456","doi":"10.2139/ssrn.3423199","title":"A Competitive Analysis of Online Knapsack Problems with Unit Density","year":2019,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Knapsack problem; Competitive analysis; Generalization; Truncation (statistics); Mathematics; Online algorithm; Mathematical optimization; Continuous knapsack problem; Randomized algorithm; Computer science; Algorithm; Statistics; Upper and lower bounds","score_opus":0.017275219296385296,"score_gpt":0.26440358099012995,"score_spread":0.24712836169374466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963349456","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13544531,0.008700775,0.7106888,0.004548659,0.0008152147,0.0006070619,0.00096392917,0.00059387565,0.13763627],"genre_scores_gemma":[0.86116636,0.00435591,0.09066474,0.0010357986,0.001769921,0.00083566806,0.0008984261,0.0007995936,0.03847349],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.995419,0.001771056,0.00012381408,0.0003995502,0.0014055278,0.0008810806],"domain_scores_gemma":[0.97278196,0.02123307,0.0012390801,0.0012723411,0.0019746455,0.0014988696],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004785619,0.0026411945,0.003032322,0.0033520577,0.0018065159,0.0055533685,0.0076819537,0.0041206973,0.027055418],"category_scores_gemma":[0.03179419,0.001497257,0.0022453973,0.004595294,0.0030432048,0.008453161,0.0043787328,0.005130773,0.0019183333],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006678612,0.00079387444,0.0015459708,0.00087211415,0.0001456924,0.00021746827,0.00031517606,0.36336556,0.002244786,0.55640227,0.022889059,0.050540116],"study_design_scores_gemma":[0.00004071128,0.00014510164,0.00040653357,0.00005264132,0.000038253427,0.000072887975,0.00010907358,0.891225,0.00028446232,0.105174795,0.0024247845,0.000025788875],"about_ca_topic_score_codex":0.0062615327,"about_ca_topic_score_gemma":0.004531283,"teacher_disagreement_score":0.027055418,"about_ca_system_score_codex":0.0038217194,"about_ca_system_score_gemma":0.0024704542,"threshold_uncertainty_score":0.090509355},"labels":[],"label_agreement":null},{"id":"W2963486750","doi":"10.1145/3154273.3154309","title":"Line recovery by programmable particles","year":2018,"lang":"en","type":"article","venue":"CINECA IRIS Institutial research information system (University of Pisa)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Focus (optics); Computer science; Line (geometry); Computer graphics (images); Physics; Geometry; Optics; Mathematics","score_opus":0.06092425143105846,"score_gpt":0.29481657362507296,"score_spread":0.2338923221940145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963486750","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07798519,0.00019310747,0.9185075,0.00023776783,0.00005942365,0.00006322093,0.00004087993,0.00033967843,0.0025732627],"genre_scores_gemma":[0.92429435,0.00019045924,0.068815015,0.00010906843,0.000037010515,0.00009412487,0.00009746445,0.00009874762,0.006263766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925596,0.0002099763,0.000031816107,0.00017995301,0.0001865503,0.00013575745],"domain_scores_gemma":[0.9976636,0.0009941725,0.00039517062,0.00057323533,0.00022072895,0.00015306706],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010128432,0.00058206,0.0006892781,0.00041087714,0.0007041784,0.0008628211,0.0011635432,0.0011573,0.0022833135],"category_scores_gemma":[0.0045500714,0.0003313475,0.0006517622,0.00045326672,0.002024842,0.0014624267,0.0022474579,0.0010378471,0.00043602253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023523501,0.000041466366,0.0007851232,0.00006817961,0.000032017615,0.0002671018,0.00015052156,0.897679,0.008014414,0.05201089,0.0009362935,0.039779752],"study_design_scores_gemma":[0.00003434907,0.000117414376,0.00013770716,0.000006187807,0.000007228735,0.00007495567,0.000056493023,0.9698673,0.0037666147,0.024695158,0.0012233616,0.000013225718],"about_ca_topic_score_codex":0.0014760597,"about_ca_topic_score_gemma":0.0006858348,"teacher_disagreement_score":0.0022833135,"about_ca_system_score_codex":0.0006756967,"about_ca_system_score_gemma":0.00052088604,"threshold_uncertainty_score":0.007638395},"labels":[],"label_agreement":null},{"id":"W2963492177","doi":"10.1145/3293611.3331608","title":"Symmetry Breaking in the Plane","year":2019,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"","keywords":"Robot; Rendezvous; Visibility; Mobile robot; Euclidean geometry; Plane (geometry); RADIUS; Plane symmetry; Constant (computer programming); Euclidean distance; Symmetry (geometry); Computer science; Mathematics; Topology (electrical circuits); Combinatorics; Physics; Artificial intelligence; Geometry; Optics; Computer network","score_opus":0.013402439020270806,"score_gpt":0.2461457968931118,"score_spread":0.232743357872841,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963492177","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38356578,0.0018306801,0.5452564,0.0032482198,0.00033678053,0.00012791136,0.00055338163,0.00020974013,0.06487115],"genre_scores_gemma":[0.95998365,0.0010143329,0.03394429,0.00028401977,0.00021990969,0.00012797624,0.00038487877,0.00007643268,0.0039643743],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99672395,0.0013237321,0.00015340067,0.0005396273,0.00065388845,0.0006055103],"domain_scores_gemma":[0.98693305,0.008623469,0.0017083834,0.0014872256,0.0007224864,0.0005253369],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029025269,0.0006287526,0.0011139065,0.00078591646,0.0015737907,0.0032095755,0.0015366612,0.0014596505,0.0042628977],"category_scores_gemma":[0.016516244,0.0005027278,0.0015145484,0.0007777772,0.00465646,0.004942296,0.0023797068,0.0030624906,0.0005332873],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010556858,0.00003183573,0.00045712938,0.00006249758,0.000027181663,0.00013503032,0.00011378634,0.03511144,0.00077021867,0.9578684,0.0009373695,0.0043794266],"study_design_scores_gemma":[0.00005208188,0.000044244083,0.00016774968,0.000020373474,0.0000089157775,0.00007173076,0.00007114684,0.094385535,0.00046189124,0.90322953,0.0014705936,0.000016144326],"about_ca_topic_score_codex":0.0021824671,"about_ca_topic_score_gemma":0.00076048146,"teacher_disagreement_score":0.0042628977,"about_ca_system_score_codex":0.0016022377,"about_ca_system_score_gemma":0.0011856491,"threshold_uncertainty_score":0.015350163},"labels":[],"label_agreement":null},{"id":"W2963782874","doi":"10.4230/lipics.icalp.2017.55","title":"Further Approximations for Demand Matching: Matroid Constraints and Minor-Closed Graphs","year":2017,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Mathematics; Approximation algorithm; Combinatorics; Matroid; Discrete mathematics; Rounding; Polynomial-time approximation scheme; Vertex (graph theory); Linear programming relaxation; Knapsack problem; Graph; Mathematical optimization; Linear programming; Computer science","score_opus":0.023494034116332947,"score_gpt":0.2828776831977924,"score_spread":0.25938364908145944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963782874","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.087361045,0.0014145115,0.8860344,0.002698142,0.00014574963,0.00017222953,0.0007475711,0.0011063183,0.020319972],"genre_scores_gemma":[0.52407694,0.0009630358,0.46113577,0.0011637126,0.00028320478,0.0002584748,0.0014289999,0.0006800449,0.0100097535],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978192,0.0006862885,0.00008300643,0.00051763054,0.0005527135,0.00034108342],"domain_scores_gemma":[0.9935575,0.003364038,0.00066095276,0.0016387516,0.0004141931,0.00036455598],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024495977,0.0018354083,0.0017063243,0.0010401173,0.0010290027,0.0032443146,0.0034622883,0.002262274,0.010268559],"category_scores_gemma":[0.015382332,0.0007902819,0.0019591397,0.0028686435,0.0012993284,0.0073880884,0.002593872,0.005375813,0.0014226929],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080353743,0.0007277465,0.0024392153,0.0005478225,0.00013585712,0.00035238874,0.00086100755,0.49974573,0.008182337,0.3554545,0.016280038,0.114469774],"study_design_scores_gemma":[0.00005562301,0.00008809794,0.00029050693,0.00005004985,0.000027816268,0.00015561597,0.00015960193,0.78272605,0.0017400827,0.20873755,0.0059528085,0.000016154187],"about_ca_topic_score_codex":0.003864516,"about_ca_topic_score_gemma":0.0044618957,"teacher_disagreement_score":0.010268559,"about_ca_system_score_codex":0.0026932636,"about_ca_system_score_gemma":0.001591601,"threshold_uncertainty_score":0.034351766},"labels":[],"label_agreement":null},{"id":"W2963799965","doi":"10.1007/s00446-021-00406-6","title":"TuringMobile: a turing machine of oblivious mobile robots with limited visibility and its applications","year":2022,"lang":"en","type":"article","venue":"IRIS Research product catalog (Sapienza University of Rome)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Snapshot (computer storage); Robot; Computer science; Mobile robot; Turing machine; Euclidean geometry; Distributed computing; Visibility; Theoretical computer science; Artificial intelligence; Algorithm; Computation; Mathematics; Geography; Operating system; Geometry","score_opus":0.032574999950468086,"score_gpt":0.28619097255514225,"score_spread":0.25361597260467417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963799965","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10047848,0.0023915626,0.85541576,0.0028997927,0.0005390572,0.0001758268,0.0005368448,0.003997716,0.033564992],"genre_scores_gemma":[0.86342984,0.00080526253,0.11807322,0.000466885,0.00019767872,0.00031575296,0.0003726626,0.00040317804,0.01593549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993943,0.00019900285,0.000026168696,0.0001280481,0.0001454297,0.00010696982],"domain_scores_gemma":[0.9987909,0.00057301024,0.00009724527,0.00026475883,0.00011879645,0.00015519653],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005615839,0.0006446599,0.00091046543,0.00065451476,0.0011165524,0.0019256328,0.0015042874,0.001739954,0.0047458373],"category_scores_gemma":[0.00501724,0.00048683537,0.0008619476,0.0007123937,0.0027602385,0.0031562694,0.0033612873,0.0024311268,0.0010153232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002959198,0.00005921419,0.000447186,0.00030427775,0.00004935716,0.00026799997,0.0002953062,0.10313618,0.007471101,0.8408494,0.008189119,0.038634833],"study_design_scores_gemma":[0.00004405836,0.00011742881,0.00019017726,0.000037829363,0.000018558563,0.00017450198,0.000040216568,0.40299407,0.0049377913,0.5786671,0.012736413,0.00004173017],"about_ca_topic_score_codex":0.00081296294,"about_ca_topic_score_gemma":0.00068989524,"teacher_disagreement_score":0.0047458373,"about_ca_system_score_codex":0.0008106789,"about_ca_system_score_gemma":0.00135826,"threshold_uncertainty_score":0.015876412},"labels":[],"label_agreement":null},{"id":"W2963874364","doi":"10.1017/s0269964818000256","title":"OPTIMAL SELECTION OF THE <i>k</i>-TH BEST CANDIDATE","year":2019,"lang":"en","type":"article","venue":"Probability in the Engineering and Informational Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Optimal stopping; Combinatorics; Mathematics; Selection (genetic algorithm); Stopping rule; Discrete mathematics; Statistics; Mathematical optimization; Computer science; Artificial intelligence","score_opus":0.010612130471167417,"score_gpt":0.2182559173910074,"score_spread":0.20764378691983998,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963874364","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32746813,0.0015037894,0.65024126,0.0028368258,0.00014739549,0.00021355505,0.0003986881,0.00046832568,0.01672199],"genre_scores_gemma":[0.8372685,0.000410557,0.15633757,0.00032133568,0.000087509805,0.00016879638,0.00041892013,0.000159869,0.0048269075],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99771607,0.0008328278,0.000169171,0.0005656886,0.0003409649,0.0003752961],"domain_scores_gemma":[0.99041873,0.006430662,0.0009717184,0.0006042105,0.0008278481,0.00074676704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038490873,0.0004990855,0.0016707829,0.0010250214,0.0008390161,0.002269759,0.0015229644,0.0013057889,0.0041451766],"category_scores_gemma":[0.017387498,0.00049009675,0.0007714454,0.00093627383,0.001637291,0.0022607162,0.0012551963,0.0011012738,0.0008052315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003213218,0.0007512423,0.026866985,0.00094684266,0.00036668777,0.0007837248,0.00095381984,0.48829505,0.015859501,0.16348669,0.014995011,0.28348127],"study_design_scores_gemma":[0.00015463562,0.0005512087,0.0038663459,0.00014222489,0.0000900712,0.00033432813,0.00034331615,0.90748227,0.01042206,0.073644795,0.0028975592,0.00007125687],"about_ca_topic_score_codex":0.0012062144,"about_ca_topic_score_gemma":0.0011393331,"teacher_disagreement_score":0.0041451766,"about_ca_system_score_codex":0.00094697595,"about_ca_system_score_gemma":0.0025363162,"threshold_uncertainty_score":0.020356178},"labels":[],"label_agreement":null},{"id":"W2963874686","doi":"","title":"Min-Max Latency Walks: Approximation Algorithms for Monitoring Vertex-Weighted Graphs","year":2012,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Vertex (graph theory); Combinatorics; Neighbourhood (mathematics); Approximation algorithm; Feedback vertex set; Mathematics; Vertex cover; Graph; Binary logarithm; Discrete mathematics","score_opus":0.091024929247383,"score_gpt":0.2135351025754776,"score_spread":0.1225101733280946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963874686","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0248125,0.0005937318,0.97064036,0.00030076504,0.00004372273,0.00013117165,0.0002671498,0.0017709871,0.001439573],"genre_scores_gemma":[0.38618582,0.00064255483,0.6075616,0.00021491776,0.00007355645,0.00042473624,0.0011559211,0.00047706743,0.0032637867],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9986914,0.00041508014,0.000080571925,0.00034410154,0.00024299935,0.00022590211],"domain_scores_gemma":[0.9968706,0.0018671696,0.00038424254,0.00049901736,0.00016839018,0.00021062004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017333298,0.0023329584,0.0015762271,0.0013687713,0.0009804037,0.0018345279,0.0030071794,0.0019289762,0.0029479787],"category_scores_gemma":[0.008197383,0.0010188596,0.0009854236,0.0028545856,0.001032061,0.004720647,0.0021871908,0.001857394,0.00095997],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005457075,0.00025479775,0.0017605482,0.00024860312,0.00008744635,0.00009969444,0.00019602086,0.8496197,0.0023299644,0.028481415,0.004626563,0.111749455],"study_design_scores_gemma":[0.000036532296,0.000049622075,0.00011115947,0.000012910924,0.000013220085,0.00004435953,0.000034562563,0.960358,0.00062456646,0.037904497,0.00080275425,0.000007768309],"about_ca_topic_score_codex":0.00388472,"about_ca_topic_score_gemma":0.0056750854,"teacher_disagreement_score":0.00388472,"about_ca_system_score_codex":0.0017321915,"about_ca_system_score_gemma":0.001554447,"threshold_uncertainty_score":0.012567937},"labels":[],"label_agreement":null},{"id":"W2963945095","doi":"10.1016/j.tcs.2019.07.018","title":"Energy-optimal broadcast and exploration in a tree using mobile agents","year":2019,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tree (set theory); Node (physics); Computer science; Enhanced Data Rates for GSM Evolution; Mobile agent; Root (linguistics); Set (abstract data type); Broadcasting (networking); Energy (signal processing); Algorithm; Mathematics; Combinatorics; Theoretical computer science; Distributed computing; Computer network; Artificial intelligence","score_opus":0.023103416894729476,"score_gpt":0.2757461246963497,"score_spread":0.2526427078016202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963945095","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2401027,0.0008275246,0.749135,0.0007560819,0.000094100935,0.000103722894,0.00013951532,0.0003535709,0.008487774],"genre_scores_gemma":[0.8766828,0.00030558812,0.11702478,0.00008018711,0.000044908968,0.000102108235,0.000095927666,0.00009953148,0.0055640005],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996278,0.00013958428,0.000017132252,0.000057737157,0.000063395,0.00009423943],"domain_scores_gemma":[0.9971692,0.0021751404,0.0001527412,0.00012016093,0.0001750864,0.00020771411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009253761,0.000501026,0.0014210877,0.00092928356,0.0008438323,0.0010205528,0.0013419323,0.0016984871,0.002202085],"category_scores_gemma":[0.004865237,0.0005882717,0.0006885651,0.0011430542,0.0010599479,0.0016941185,0.0016395727,0.0009840815,0.000277086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038416297,0.00009910363,0.00057431305,0.000084839645,0.000038074504,0.00008505457,0.00017667148,0.94449097,0.0028024276,0.029599948,0.0011779701,0.020486495],"study_design_scores_gemma":[0.000024136216,0.000032206197,0.000057792804,0.0000064318415,0.0000072998273,0.000013182967,0.000024370589,0.98982286,0.00025646196,0.009559068,0.00019236493,0.0000038996773],"about_ca_topic_score_codex":0.0038924299,"about_ca_topic_score_gemma":0.0038752896,"teacher_disagreement_score":0.0038924299,"about_ca_system_score_codex":0.0008763949,"about_ca_system_score_gemma":0.00086133025,"threshold_uncertainty_score":0.007739544},"labels":[],"label_agreement":null},{"id":"W2964657030","doi":"10.1007/978-3-030-26766-7_19","title":"Optimizing Self-organizing Lists-on-Lists Using Pursuit-Oriented Enhanced Object Partitioning","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Probabilistic logic; Learning automata; Object (grammar); Locality; Context (archaeology); Automaton; De facto; Theoretical computer science; Reinforcement learning; Artificial intelligence; Scheme (mathematics); Mathematics","score_opus":0.023128662896949592,"score_gpt":0.26818415449428973,"score_spread":0.24505549159734014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2964657030","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032559227,0.0003358889,0.9622518,0.000104631676,0.000063048916,0.000060612096,0.00007047823,0.0007895306,0.0037648317],"genre_scores_gemma":[0.5304995,0.00024718215,0.46086234,0.00015166115,0.00008742545,0.0002237302,0.00039462093,0.00030066018,0.0072328835],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971014,0.00006653328,0.000015014188,0.00005455759,0.00009491005,0.000058888407],"domain_scores_gemma":[0.9993481,0.0003575727,0.00004641092,0.000072336035,0.0001227944,0.000052671076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049489253,0.0008501313,0.0013905128,0.000610247,0.00063722825,0.0011093932,0.0018247657,0.0012006933,0.0043331226],"category_scores_gemma":[0.0014255104,0.0005930374,0.00057791267,0.0010239205,0.00042844444,0.0013606669,0.0016027328,0.0006894772,0.0008696582],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033511317,0.00020151684,0.00042838705,0.00014582032,0.000059899292,0.00005926059,0.00008048931,0.8039068,0.009589359,0.008900506,0.004712368,0.17158054],"study_design_scores_gemma":[0.000009555036,0.00003893233,0.000039902585,0.0000026127223,0.0000049284604,0.000010444513,0.000009356198,0.9979746,0.00062128925,0.0010371903,0.00024799636,0.0000032107992],"about_ca_topic_score_codex":0.0027123517,"about_ca_topic_score_gemma":0.0035750226,"teacher_disagreement_score":0.0043331226,"about_ca_system_score_codex":0.0006115422,"about_ca_system_score_gemma":0.00074888027,"threshold_uncertainty_score":0.014495671},"labels":[],"label_agreement":null},{"id":"W2965199817","doi":"","title":"Pure entropic regularization for metrical task systems","year":2019,"lang":"en","type":"article","venue":"Oxford University Research Archive (ORA) (University of Oxford)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Competitive analysis; Randomized algorithm; Online algorithm; Binary logarithm; Metric space; Computer science; Deterministic algorithm; Mathematics; Conditional entropy; Entropy (arrow of time); Embedding; Regularization (linguistics); Exploit; Algorithm; Mathematical optimization; Combinatorics; Discrete mathematics; Upper and lower bounds; Artificial intelligence; Principle of maximum entropy","score_opus":0.024890200048123992,"score_gpt":0.24760775900450654,"score_spread":0.22271755895638257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2965199817","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04428729,0.0002933952,0.944242,0.0010945601,0.00007487062,0.00009274085,0.00024219084,0.00080965133,0.00886327],"genre_scores_gemma":[0.71955717,0.00025584895,0.26033014,0.0005545528,0.00016132882,0.00036162505,0.00062649505,0.00053517707,0.017617691],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989612,0.00030311613,0.000050962655,0.0002682399,0.0002520522,0.00016434323],"domain_scores_gemma":[0.9969457,0.0016137953,0.00025261563,0.00053067086,0.00031900793,0.0003382186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015465572,0.0013676019,0.0012559545,0.0005571638,0.00067665556,0.0012203348,0.0017643841,0.0017353179,0.006276159],"category_scores_gemma":[0.009871733,0.00045342272,0.0006340182,0.00057526707,0.0014833396,0.002409008,0.0032179249,0.0026067025,0.0011921836],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029268715,0.00014264895,0.00082070334,0.00023042898,0.000049875318,0.00013736259,0.00013712111,0.6536037,0.0065659177,0.2545885,0.0095065525,0.07392456],"study_design_scores_gemma":[0.000009942774,0.000028820132,0.00008211062,0.000004351878,0.0000028753846,0.000014394855,0.000005562252,0.9574965,0.0004486974,0.04129538,0.0006058521,0.0000055063806],"about_ca_topic_score_codex":0.0037250018,"about_ca_topic_score_gemma":0.0046338798,"teacher_disagreement_score":0.006276159,"about_ca_system_score_codex":0.0018497619,"about_ca_system_score_gemma":0.0020401662,"threshold_uncertainty_score":0.020995855},"labels":[],"label_agreement":null},{"id":"W2966140795","doi":"","title":"Exploration et couverture par stigmergie d’un environnement inconnu avec une flotte de robots autonomes réactifs","year":2019,"lang":"fr","type":"preprint","venue":"INRIA a CCSD electronic archive server","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Humanities; Art; Brick; Political science; Geography; Archaeology","score_opus":0.019628999083163724,"score_gpt":0.25386548897567646,"score_spread":0.23423648989251272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966140795","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7850046,0.0005259232,0.20023842,0.0012204106,0.00013588442,0.00007371284,0.00009206402,0.00037288739,0.012336034],"genre_scores_gemma":[0.9553688,0.00024883437,0.028402528,0.00008265677,0.00006463219,0.00010239009,0.00009890041,0.00006500054,0.01556621],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993999,0.0002071067,0.000017086386,0.0001375571,0.00014134216,0.00009707913],"domain_scores_gemma":[0.9982066,0.0012463053,0.00010244249,0.00010577342,0.0001193872,0.00021951883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009693917,0.0013965772,0.0012276629,0.0014272614,0.0021804548,0.0024107988,0.00088284607,0.0032354696,0.0028774915],"category_scores_gemma":[0.0032818408,0.0009647623,0.0014512403,0.0008768423,0.002921353,0.0015917608,0.002229393,0.0019999307,0.00040083056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000580264,0.00013128083,0.0018848374,0.00009860368,0.00010700716,0.0012695708,0.0006507524,0.95232993,0.012983442,0.017705243,0.00061205507,0.011646921],"study_design_scores_gemma":[0.00014003072,0.0002168987,0.002601938,0.000014917476,0.000018448225,0.00018969785,0.0001665874,0.98814887,0.0035402242,0.0036242004,0.0013061849,0.000032138087],"about_ca_topic_score_codex":0.028958397,"about_ca_topic_score_gemma":0.019115653,"teacher_disagreement_score":0.028958397,"about_ca_system_score_codex":0.0022386836,"about_ca_system_score_gemma":0.0008870977,"threshold_uncertainty_score":0.057579696},"labels":[],"label_agreement":null},{"id":"W2968601138","doi":"10.1109/icra.2019.8794252","title":"The Robust Canadian Traveler Problem Applied to Robot Routing","year":2019,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Tree traversal; Robot; Computer science; Mathematical optimization; Routing (electronic design automation); Vehicle routing problem; Selection (genetic algorithm); Variation (astronomy); Operations research; Artificial intelligence; Algorithm; Mathematics; Computer network","score_opus":0.015660010591459952,"score_gpt":0.21308443356914258,"score_spread":0.19742442297768265,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2968601138","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017977374,0.0006358143,0.97172683,0.000729696,0.00011306398,0.00011980903,0.00037876097,0.00025906286,0.008059517],"genre_scores_gemma":[0.69990325,0.0011556263,0.28745344,0.0002676906,0.00016108637,0.00030507456,0.0007479662,0.00029949204,0.009706296],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986803,0.0004770597,0.000042901767,0.0002797136,0.00030614363,0.00021387642],"domain_scores_gemma":[0.9981365,0.0011933193,0.00017364579,0.00008310048,0.00028308496,0.00013041886],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020025775,0.0014751245,0.0016279775,0.001340787,0.0011398687,0.0016871312,0.0019735994,0.0021871522,0.003866209],"category_scores_gemma":[0.006413127,0.0006962731,0.0012240116,0.002216531,0.0018306116,0.0013415905,0.0016024414,0.00209,0.00022222748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023379198,0.0000070224196,0.00013465209,0.000029805506,0.000016386548,0.000026667181,0.000013994868,0.9723727,0.00013838348,0.021590967,0.00082447845,0.0048215254],"study_design_scores_gemma":[0.00000632494,0.000010889223,0.000084645006,0.000004219877,0.0000049750192,0.000010713656,0.000008747534,0.9879909,0.00009402763,0.011063653,0.00071206124,0.000008900052],"about_ca_topic_score_codex":0.21810669,"about_ca_topic_score_gemma":0.12421608,"teacher_disagreement_score":0.21810669,"about_ca_system_score_codex":0.0051524104,"about_ca_system_score_gemma":0.007779097,"threshold_uncertainty_score":0.43367434},"labels":[],"label_agreement":null},{"id":"W2969848726","doi":"10.1007/978-3-030-34405-4_1","title":"Evacuation of Equilateral Triangles by Mobile Agents of Limited Communication Range","year":2019,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Equilateral triangle; Perimeter; Combinatorics; Range (aeronautics); Centroid; Mathematics; Point (geometry); Computer science; Mobile agent; Mathematical optimization; Geometry; Distributed computing; Engineering","score_opus":0.0343644728755405,"score_gpt":0.30826128946266623,"score_spread":0.2738968165871257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2969848726","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5283907,0.00060070015,0.4475681,0.0013894074,0.00029619315,0.00024623197,0.0005953024,0.00044062565,0.02047273],"genre_scores_gemma":[0.95141155,0.0003364048,0.034945004,0.00017165006,0.000053158838,0.00018169689,0.00045549826,0.00011312607,0.012331844],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996817,0.00008218609,0.000016415348,0.000065524895,0.00004588107,0.00010827261],"domain_scores_gemma":[0.99824524,0.00088441843,0.00027775505,0.00013606215,0.00011905685,0.00033754547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004145504,0.0006587382,0.0013663482,0.0008055285,0.0014415468,0.0013981349,0.0019003483,0.0022605944,0.0052256356],"category_scores_gemma":[0.004285883,0.00067018217,0.0010059605,0.0008255253,0.0012428784,0.0015864922,0.004007656,0.001159992,0.00075892743],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006774643,0.00009095757,0.0014064406,0.00016902294,0.000052624087,0.00085380184,0.0004453327,0.95708144,0.0045055873,0.023593511,0.0019355492,0.009188203],"study_design_scores_gemma":[0.000059479542,0.000079652564,0.00015134802,0.000018138835,0.000011810618,0.00007638963,0.00026044366,0.9811198,0.0011229798,0.015684245,0.0014025538,0.000013031775],"about_ca_topic_score_codex":0.0047511957,"about_ca_topic_score_gemma":0.0026859562,"teacher_disagreement_score":0.0052256356,"about_ca_system_score_codex":0.0007790201,"about_ca_system_score_gemma":0.0006394924,"threshold_uncertainty_score":0.017481446},"labels":[],"label_agreement":null},{"id":"W2970627438","doi":"10.1016/j.tcs.2019.08.031","title":"Searching for a non-adversarial, uncooperative agent on a cycle","year":2019,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Perimeter; Position (finance); RADIUS; Computer science; Upper and lower bounds; Constant (computer programming); Turning radius; Mobile robot; Mathematics; Algorithm; Artificial intelligence; Engineering; Geometry; Computer network","score_opus":0.01357223503755122,"score_gpt":0.28620262882830155,"score_spread":0.2726303937907503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970627438","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36771703,0.00027291852,0.60488427,0.0035434999,0.00015802891,0.00033663245,0.00023785543,0.0006041425,0.022245584],"genre_scores_gemma":[0.8899217,0.0001336606,0.09615696,0.0002767199,0.000043849595,0.00015529347,0.00013583926,0.000096481024,0.013079485],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995209,0.00013202861,0.000016540771,0.00014287274,0.00006930321,0.00011829304],"domain_scores_gemma":[0.997974,0.0012092994,0.00015057677,0.00018984034,0.00015652296,0.00031972642],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008348985,0.00072017446,0.0012044695,0.00067107857,0.0013199251,0.0014334884,0.0023069135,0.0028989634,0.0072995117],"category_scores_gemma":[0.0049817734,0.00048686133,0.00066696823,0.0005194769,0.0013981296,0.0026106343,0.002456531,0.0015527309,0.0006870757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011539472,0.0003786109,0.0028761667,0.00026419494,0.00019876119,0.00070786965,0.00034232138,0.78600913,0.006609943,0.14584854,0.0056832246,0.049927264],"study_design_scores_gemma":[0.000051015588,0.0001390544,0.000113953305,0.000016393595,0.000018158362,0.00005918578,0.00006627936,0.9577328,0.0009371787,0.039926343,0.0009278954,0.00001177798],"about_ca_topic_score_codex":0.002515271,"about_ca_topic_score_gemma":0.0029321916,"teacher_disagreement_score":0.0072995117,"about_ca_system_score_codex":0.0008735841,"about_ca_system_score_gemma":0.002200978,"threshold_uncertainty_score":0.024419308},"labels":[],"label_agreement":null},{"id":"W2970866601","doi":"10.1137/20m1362899","title":"Want to Gather? No Need to Chatter!","year":2020,"lang":"en","type":"preprint","venue":"SIAM Journal on Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Node (physics); A priori and a posteriori; Computer science; Task (project management); Product (mathematics); Time complexity; Polynomial; Upper and lower bounds; Theoretical computer science; Mathematics; Algorithm; Engineering","score_opus":0.04709621463748689,"score_gpt":0.31005201720830283,"score_spread":0.26295580257081597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2970866601","genre_codex":"commentary","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09047997,0.008439689,0.141959,0.45514327,0.0057389396,0.00015252637,0.0010557191,0.0012556304,0.29577532],"genre_scores_gemma":[0.6848326,0.005316182,0.05620365,0.032085378,0.0023305186,0.00026685643,0.0010031601,0.0006141231,0.21734756],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998771,0.00055041973,0.000040279512,0.00029584643,0.0001632419,0.00017920378],"domain_scores_gemma":[0.99530655,0.00264403,0.00036363452,0.00052072,0.00043043,0.00073453184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017663722,0.00048288563,0.0006906652,0.00040199826,0.002363406,0.0025998955,0.0009938986,0.003842301,0.029545657],"category_scores_gemma":[0.010975679,0.0005603312,0.00046145098,0.0005254774,0.0033793703,0.010588867,0.002658278,0.0037128543,0.011013228],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006963936,0.00027275557,0.0059805876,0.0011302247,0.000101296886,0.001120459,0.007717462,0.0018865924,0.005264759,0.5554923,0.26655236,0.15378481],"study_design_scores_gemma":[0.00007748051,0.0001564597,0.0031228561,0.000332109,0.000054882257,0.0017675642,0.01180027,0.0070296475,0.0017845704,0.66934586,0.30440712,0.00012117824],"about_ca_topic_score_codex":0.0011849344,"about_ca_topic_score_gemma":0.0017024955,"teacher_disagreement_score":0.029545657,"about_ca_system_score_codex":0.0005869527,"about_ca_system_score_gemma":0.00053647987,"threshold_uncertainty_score":0.09884012},"labels":[],"label_agreement":null},{"id":"W2972852770","doi":"10.1007/s00446-019-00362-2","title":"Meeting in a polygon by anonymous oblivious robots","year":2019,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Polygon (computer graphics); Computer science; Combinatorics; Asynchronous communication; Algebraic number; Visibility polygon; Upper and lower bounds; Asymptotically optimal algorithm; Theoretical computer science; Algorithm; Discrete mathematics; Mathematics; Simple polygon; Regular polygon; Geometry","score_opus":0.006297182411765845,"score_gpt":0.22727481758885,"score_spread":0.22097763517708413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2972852770","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27824807,0.0002816735,0.6892009,0.0011400474,0.0001554421,0.00020800928,0.0002363814,0.0006087186,0.029920736],"genre_scores_gemma":[0.8946161,0.00024686396,0.09062397,0.00006717011,0.000052864052,0.00018125279,0.00017095853,0.00010676561,0.013933974],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990288,0.00032224873,0.000048042926,0.00020088552,0.00019753471,0.00020248367],"domain_scores_gemma":[0.9980319,0.00089762144,0.0003961181,0.00033039885,0.00009190879,0.0002520157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006730622,0.00057364395,0.0009931003,0.0005241455,0.0020111478,0.0017947757,0.0018073035,0.0012969305,0.0053638634],"category_scores_gemma":[0.0042420547,0.00060561695,0.00087557867,0.0011610516,0.0014746042,0.0028611557,0.0041913413,0.00095183385,0.000987774],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001823785,0.00024473446,0.0026546419,0.00032379845,0.00017493422,0.001283204,0.0014438819,0.7876036,0.0116922995,0.12848035,0.004809448,0.059465338],"study_design_scores_gemma":[0.000098829594,0.0002304966,0.00041132903,0.000019351233,0.00004278014,0.0001752449,0.00076372107,0.923247,0.0035162864,0.06412762,0.007341059,0.00002633231],"about_ca_topic_score_codex":0.0024280434,"about_ca_topic_score_gemma":0.00202663,"teacher_disagreement_score":0.0053638634,"about_ca_system_score_codex":0.0007061212,"about_ca_system_score_gemma":0.0006621573,"threshold_uncertainty_score":0.01794386},"labels":[],"label_agreement":null},{"id":"W2975694009","doi":"10.1016/j.tcs.2019.09.026","title":"Priority evacuation from a disk: The case of n = 1,2,3","year":2019,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; Carleton University; Toronto Metropolitan University; Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Robot; Servant; Queen (butterfly); Computer science; Position (finance); Simulation; Mathematics; Artificial intelligence; Business; Programming language","score_opus":0.010608038022033667,"score_gpt":0.2689961043936256,"score_spread":0.25838806637159195,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2975694009","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.88528496,0.0011384629,0.04899035,0.005767156,0.00063658674,0.00015319108,0.00077027513,0.00032926467,0.056929786],"genre_scores_gemma":[0.9874391,0.00016084553,0.006719235,0.00013011615,0.000055111566,0.00001885894,0.00008856175,0.00004089494,0.005347465],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999171,0.00017828561,0.000025951254,0.00009863893,0.00009637942,0.00042972306],"domain_scores_gemma":[0.9941555,0.0033911252,0.0004203908,0.00041451058,0.00068756595,0.0009308446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016761484,0.0003803763,0.0009470495,0.00070662104,0.0024553475,0.0020852864,0.0017541784,0.0022519105,0.007708245],"category_scores_gemma":[0.01197753,0.00030879257,0.00050345314,0.000856659,0.0012429056,0.002121316,0.0013776158,0.0009661125,0.00057554076],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.008374516,0.0009537897,0.01807249,0.0011005565,0.0001460004,0.014658483,0.0016899451,0.6033843,0.0073336605,0.24560769,0.056115195,0.04256345],"study_design_scores_gemma":[0.00034340797,0.00030838218,0.00227042,0.00004814643,0.00007088834,0.0015742595,0.0020106062,0.8800585,0.0024095154,0.10547747,0.0053545497,0.000073875904],"about_ca_topic_score_codex":0.009414132,"about_ca_topic_score_gemma":0.008676839,"teacher_disagreement_score":0.009414132,"about_ca_system_score_codex":0.0011377914,"about_ca_system_score_gemma":0.001467277,"threshold_uncertainty_score":0.025786698},"labels":[],"label_agreement":null},{"id":"W2975703404","doi":"10.1109/infcomw.2019.8845156","title":"Task Dispatch through Online Training for Profit Maximization at the Cloud","year":2019,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cloud computing; Profit maximization; Profit (economics); Scheduling (production processes); Task analysis; Upper and lower bounds; Distributed computing; Real-time computing; Operations research; Mathematical optimization; Task (project management); Operating system","score_opus":0.05643131051759774,"score_gpt":0.3007617829015977,"score_spread":0.24433047238399996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2975703404","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3257903,0.0007559472,0.66275424,0.0011916504,0.00012365238,0.00018443522,0.00017369963,0.0007993373,0.008226674],"genre_scores_gemma":[0.9593624,0.00011905844,0.03914503,0.00008574591,0.000031258412,0.000047067,0.000060808226,0.00005429735,0.0010944011],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99931705,0.0002168703,0.000022514336,0.00011077718,0.00010127351,0.00023157851],"domain_scores_gemma":[0.99808097,0.0012524009,0.00021659503,0.00013667709,0.00015559448,0.00015777728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013615795,0.00088278466,0.0011489305,0.00035570897,0.00059424766,0.00086184085,0.0012181352,0.0007921095,0.0020458545],"category_scores_gemma":[0.0050139176,0.00032780392,0.00033974898,0.0006980714,0.0008924323,0.001547284,0.00076994643,0.0010454829,0.00027516708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020383873,0.00010448055,0.0006497093,0.000032337066,0.0000098088485,0.00004747207,0.000023944556,0.9739319,0.0013011777,0.002500993,0.0008945883,0.020299697],"study_design_scores_gemma":[0.000008102304,0.000019674195,0.00008467622,0.0000014978211,0.000001616571,0.0000069344264,0.0000064575397,0.9981059,0.00033665178,0.0013373796,0.000089461,0.0000016275944],"about_ca_topic_score_codex":0.008505221,"about_ca_topic_score_gemma":0.005136613,"teacher_disagreement_score":0.008505221,"about_ca_system_score_codex":0.0012991286,"about_ca_system_score_gemma":0.0020835884,"threshold_uncertainty_score":0.016911447},"labels":[],"label_agreement":null},{"id":"W2977712778","doi":"10.1007/s00453-020-00752-0","title":"Building a Nest by an Automaton","year":2020,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Narodowe Centrum Nauki; Narodowym Centrum Nauki; Université du Québec en Outaouais","keywords":"Algorithm; Computer science; Tree (set theory); Robot; Geometry; Artificial intelligence; Mathematics; Combinatorics","score_opus":0.019838259336137455,"score_gpt":0.26788215972330226,"score_spread":0.2480439003871648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977712778","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13800961,0.0003604377,0.8336099,0.0005210946,0.00009762741,0.00009741861,0.00032283066,0.003460042,0.023520973],"genre_scores_gemma":[0.7709808,0.0002651869,0.21482463,0.00013311673,0.000034182867,0.00018338987,0.0005903181,0.00033405118,0.012654293],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993988,0.00014884252,0.000054842596,0.00017438234,0.00013438135,0.00008875443],"domain_scores_gemma":[0.9991271,0.00040871542,0.000069676236,0.00021004074,0.00009640874,0.000088092114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037245938,0.00048685202,0.00050029176,0.00047128444,0.0009008269,0.0014670758,0.0009885903,0.0009793587,0.006891916],"category_scores_gemma":[0.0015048368,0.0005390964,0.0015438116,0.00034265438,0.0017024842,0.0016656956,0.0022981425,0.0009749686,0.0011972494],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031896617,0.00015461221,0.003254012,0.00034193567,0.000093971496,0.0009144916,0.0010305844,0.45852643,0.021311507,0.46511775,0.0032731702,0.045662485],"study_design_scores_gemma":[0.00006187707,0.00011784375,0.000306667,0.00005780265,0.000043772096,0.00014921316,0.0001100062,0.7259487,0.0056098,0.2548103,0.01275424,0.00002973343],"about_ca_topic_score_codex":0.003234567,"about_ca_topic_score_gemma":0.0028299638,"teacher_disagreement_score":0.006891916,"about_ca_system_score_codex":0.0007115781,"about_ca_system_score_gemma":0.00063520944,"threshold_uncertainty_score":0.023055732},"labels":[],"label_agreement":null},{"id":"W2978693269","doi":"10.22215/etd/2019-13628","title":"Experimental Analysis of Programmable Particles","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Homogeneous; Distributed computing; Simple (philosophy); Physics","score_opus":0.022296432534118976,"score_gpt":0.3174123726107749,"score_spread":0.29511594007665587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2978693269","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94943625,0.00090555265,0.024209455,0.00029193892,0.00030478244,0.00018106839,0.0012805731,0.00036490415,0.023025589],"genre_scores_gemma":[0.9827198,0.00040615955,0.008265536,0.00010107922,0.000041756542,0.0002307182,0.0014055821,0.00013318505,0.006696253],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994591,0.000058256344,0.000028692491,0.00016042215,0.0001845541,0.00010901014],"domain_scores_gemma":[0.9988776,0.00037510882,0.00012270652,0.00026695014,0.0002461867,0.000111585105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006626002,0.00034041703,0.00030031442,0.00041928142,0.00067493564,0.0006828835,0.00076870044,0.0007090603,0.008252929],"category_scores_gemma":[0.0015831225,0.00017655379,0.00019918976,0.0004668394,0.0008497981,0.0005421891,0.0006443448,0.0007366416,0.0012076072],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013578684,0.0011102973,0.004136885,0.00044645878,0.00007261837,0.0005249242,0.00035991115,0.011796819,0.9355525,0.021512158,0.0036814995,0.019448163],"study_design_scores_gemma":[0.0003131058,0.0023608853,0.008404584,0.00007041881,0.00006916502,0.00037592193,0.00030590463,0.042122908,0.9217884,0.0058883177,0.01822016,0.00008033848],"about_ca_topic_score_codex":0.0006787954,"about_ca_topic_score_gemma":0.00032927791,"teacher_disagreement_score":0.008252929,"about_ca_system_score_codex":0.0005414864,"about_ca_system_score_gemma":0.00026953156,"threshold_uncertainty_score":0.027608752},"labels":[],"label_agreement":null},{"id":"W2980007075","doi":"10.1007/s10107-021-01723-1","title":"The aggregation closure is polyhedral for packing and covering integer programs","year":2021,"lang":"en","type":"preprint","venue":"Mathematical Programming","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Closure (psychology); Intersection (aeronautics); Generalization; Combinatorics; Polyhedron; Integer (computer science); Mathematics; Computer science; Political science; Geography; Mathematical analysis; Law","score_opus":0.039457364235447955,"score_gpt":0.2967326560548221,"score_spread":0.25727529181937414,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980007075","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04498462,0.0009112023,0.9168776,0.0014535574,0.00039785032,0.00013883016,0.0004816219,0.00017730436,0.034577373],"genre_scores_gemma":[0.5865932,0.0024556788,0.38217908,0.0009182215,0.0011080466,0.00068665575,0.0015744276,0.00075017277,0.0237345],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99740726,0.0007704318,0.00017739444,0.0005950754,0.0007066247,0.00034315785],"domain_scores_gemma":[0.99411124,0.0037096504,0.00053749233,0.00069872383,0.00050919235,0.00043360074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002763824,0.0013658148,0.0024124691,0.0016715546,0.0017304949,0.0059389663,0.0013857539,0.0016788249,0.008324662],"category_scores_gemma":[0.013368332,0.0012615199,0.0023832256,0.002729057,0.0031523157,0.009510228,0.003190846,0.0072720875,0.00096420257],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008120881,0.00008847829,0.00026170467,0.00012230061,0.00001484143,0.000060086768,0.00019189918,0.01820814,0.00062042894,0.9510723,0.0037222311,0.02555644],"study_design_scores_gemma":[0.000013693402,0.000032020693,0.000096867836,0.000036860867,0.0000080616755,0.00007514935,0.000067875786,0.053198628,0.00041889708,0.9420118,0.0040291967,0.000011036188],"about_ca_topic_score_codex":0.0013000427,"about_ca_topic_score_gemma":0.0010340046,"teacher_disagreement_score":0.008324662,"about_ca_system_score_codex":0.0017166766,"about_ca_system_score_gemma":0.0013253638,"threshold_uncertainty_score":0.02784872},"labels":[],"label_agreement":null},{"id":"W2981655024","doi":"10.1007/s00224-019-09952-w","title":"Guest Editorial: Special Issue on Approximation and Online Algorithms","year":2019,"lang":"en","type":"editorial","venue":"Theory of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Algorithm","score_opus":0.013594254467402532,"score_gpt":0.2748879037506026,"score_spread":0.2612936492832001,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2981655024","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000024532099,0.003833609,0.00023606997,0.018909713,0.9751364,0.000014195368,0.00004907068,0.00004419886,0.001752122],"genre_scores_gemma":[0.0003182731,0.0021230048,0.00015259498,0.004869439,0.9841033,0.00001463964,0.000033668588,0.000052492553,0.008332452],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9927797,0.0011961207,0.0007313929,0.0009615235,0.0037960345,0.0005352598],"domain_scores_gemma":[0.9692359,0.0121743195,0.0020596937,0.0010451949,0.011472387,0.004012471],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0072601,0.004619987,0.0060087997,0.006251337,0.0032060272,0.011884874,0.0038070143,0.0136271985,0.039811846],"category_scores_gemma":[0.031769432,0.0014824487,0.0032692715,0.002531864,0.0023674155,0.0051374733,0.0020713618,0.015551019,0.021267522],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042855278,0.000013645244,0.000015839405,0.00014404466,0.000022683447,0.000055103203,0.000002993968,0.000048418824,0.000041776788,0.0003916774,0.99428517,0.0049358197],"study_design_scores_gemma":[0.00015728507,0.000043921387,0.00024900987,0.0003992,0.00009185835,0.0002446871,0.000018853007,0.00073569175,0.00018295899,0.0040208474,0.9938293,0.000026372603],"about_ca_topic_score_codex":0.0009598759,"about_ca_topic_score_gemma":0.0031420353,"teacher_disagreement_score":0.039811846,"about_ca_system_score_codex":0.0041375975,"about_ca_system_score_gemma":0.0029006714,"threshold_uncertainty_score":0.1331839},"labels":[],"label_agreement":null},{"id":"W2985558354","doi":"10.1109/mrs.2019.8901079","title":"On Minimum Time Multi-Robot Planning with Guarantees on the Total Collected Reward","year":2019,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Robot; Computer science; Mobile robot; Motion planning; Value (mathematics); Approximation algorithm; Mathematical optimization; Algorithm; Artificial intelligence; Mathematics; Machine learning","score_opus":0.020792738848567072,"score_gpt":0.2439213876007203,"score_spread":0.2231286487521532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985558354","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023619674,0.0010275587,0.96609205,0.000770585,0.000082849794,0.00014139077,0.0002912216,0.0005081597,0.0074665505],"genre_scores_gemma":[0.51133466,0.0015145367,0.4763912,0.0004200113,0.00017182148,0.0007103028,0.0007950743,0.00067902944,0.007983414],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976816,0.00078994525,0.00009311908,0.00041680157,0.0005602907,0.00045819744],"domain_scores_gemma":[0.9902547,0.0073644933,0.0008145305,0.0005350713,0.0005831099,0.00044801828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034746279,0.0027831462,0.0020430612,0.0009858242,0.001148301,0.0018901062,0.002051538,0.001859192,0.005317597],"category_scores_gemma":[0.013320309,0.0008143667,0.0012549219,0.002249636,0.001901566,0.0032577037,0.0021023455,0.002882465,0.0010408841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022887373,0.0000609749,0.00031965264,0.00018615625,0.000041481417,0.000059130747,0.000089382316,0.9523506,0.0009194594,0.030293116,0.0017979183,0.013653283],"study_design_scores_gemma":[0.000034036686,0.00009019043,0.0000993208,0.000024574903,0.000009965947,0.0000268543,0.000025807876,0.9698842,0.00032689972,0.028732873,0.00073729677,0.000008016361],"about_ca_topic_score_codex":0.0063105747,"about_ca_topic_score_gemma":0.0056233923,"teacher_disagreement_score":0.0063105747,"about_ca_system_score_codex":0.003019548,"about_ca_system_score_gemma":0.0030942042,"threshold_uncertainty_score":0.021908402},"labels":[],"label_agreement":null},{"id":"W2986240933","doi":"10.1109/mrs.2019.8901059","title":"Collision-aware Task Assignment for Multi-Robot Systems","year":2019,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Robot; Collision avoidance; Bidding; Task (project management); Collision; Function (biology); Binary number; Mathematical optimization; Distributed computing; Artificial intelligence; Engineering; Mathematics; Computer security","score_opus":0.05146401897043256,"score_gpt":0.303555263479558,"score_spread":0.25209124450912546,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2986240933","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0189111,0.00027301343,0.9788189,0.00013057333,0.000043862234,0.000055799763,0.000023333076,0.000179043,0.0015644754],"genre_scores_gemma":[0.8022476,0.00022587927,0.19474244,0.000069730646,0.000051339135,0.00018216982,0.00006787554,0.00007694211,0.0023361251],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991078,0.0002841536,0.00003628916,0.00016112103,0.00024043166,0.00017007375],"domain_scores_gemma":[0.99909663,0.00038151327,0.00015763102,0.00011296946,0.00014507268,0.00010614797],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00097248366,0.00081364135,0.0011148757,0.00046479175,0.0010295303,0.0008693107,0.0016700593,0.0007463433,0.0019752383],"category_scores_gemma":[0.0021619794,0.00055523537,0.0005691295,0.00076872937,0.00073301553,0.0012395745,0.0017456432,0.0011359638,0.00030175172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048673344,0.00004888333,0.00023369868,0.000052346768,0.00001685261,0.00005904885,0.0000535842,0.9680111,0.0019618848,0.008138086,0.00062520255,0.02075069],"study_design_scores_gemma":[0.000012629323,0.000031505166,0.00007067319,0.0000024742426,0.0000033473887,0.000019464229,0.000015003499,0.9936027,0.0003575148,0.0053211567,0.0005590224,0.000004548933],"about_ca_topic_score_codex":0.0030539453,"about_ca_topic_score_gemma":0.002765082,"teacher_disagreement_score":0.0030539453,"about_ca_system_score_codex":0.0008676974,"about_ca_system_score_gemma":0.0015996546,"threshold_uncertainty_score":0.0066078305},"labels":[],"label_agreement":null},{"id":"W2991443058","doi":"10.1007/978-3-030-34500-6_13","title":"Deep Reinforcement Learning for Multi-satellite Collection Scheduling","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada; Royal Military College of Canada; Queen's University","funders":"","keywords":"Computer science; Reinforcement learning; Scheduling (production processes); Schedule; Artificial intelligence; Heuristic; Baseline (sea); Task (project management); Critical path method; Machine learning; Mathematical optimization","score_opus":0.03757488183802357,"score_gpt":0.2835196784441623,"score_spread":0.24594479660613874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2991443058","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03939728,0.0011829498,0.95068425,0.0006329646,0.00017422004,0.00004914749,0.00022895027,0.00092646154,0.006723735],"genre_scores_gemma":[0.89348173,0.00051336305,0.093715794,0.00020284131,0.00011689951,0.0001125473,0.00028779238,0.00013604232,0.011432976],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978775,0.000049941133,0.000008867612,0.000052939096,0.000036820627,0.000063704974],"domain_scores_gemma":[0.9993243,0.00041378057,0.000060989896,0.00004810951,0.00009711439,0.000055782464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000687745,0.0006276506,0.0011083125,0.00030348162,0.00031546186,0.0005927718,0.0012656365,0.0010662646,0.0051330277],"category_scores_gemma":[0.0018912876,0.0004291015,0.00038065977,0.0005276466,0.00049434684,0.0007634799,0.00079318095,0.0016960092,0.0005398425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000048593978,0.00004006242,0.00019195808,0.000035027042,0.000014940296,0.0000132501855,0.000012320415,0.9513878,0.0004944122,0.0040065097,0.0020994213,0.04165572],"study_design_scores_gemma":[0.000002645964,0.0000070488286,0.000028627011,0.000002056305,0.0000018336852,0.0000018397651,0.0000015703753,0.998004,0.00007590609,0.0017400209,0.00013329649,0.0000011239053],"about_ca_topic_score_codex":0.01108646,"about_ca_topic_score_gemma":0.014183556,"teacher_disagreement_score":0.01108646,"about_ca_system_score_codex":0.0012666036,"about_ca_system_score_gemma":0.0012960111,"threshold_uncertainty_score":0.022043884},"labels":[],"label_agreement":null},{"id":"W2992503655","doi":"10.1145/3374888.3374893","title":"Optimal Posted Prices for Online Resource Allocation with Supply Costs","year":2019,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Valuation (finance); Competitive analysis; Payment; Business; Bundle; Resource (disambiguation); Microeconomics; Environmental economics; Resource allocation; Total cost; Computer science; Industrial organization; Operations research; Economics; Finance","score_opus":0.052646092793336006,"score_gpt":0.3368921266299996,"score_spread":0.28424603383666364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2992503655","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08314441,0.0013720024,0.89440733,0.002150665,0.00044363458,0.00036908514,0.00038329547,0.0005783785,0.01715116],"genre_scores_gemma":[0.85866725,0.0010285915,0.12439639,0.0003847855,0.0004386272,0.00043670135,0.00027042913,0.00025726733,0.014120049],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99667895,0.0017054734,0.00013762916,0.0003897207,0.0005855511,0.000502835],"domain_scores_gemma":[0.9845508,0.012162088,0.001000908,0.0006323888,0.00086212385,0.00079168036],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005384248,0.0017049796,0.003209543,0.0012769811,0.0012076821,0.0040264498,0.0036801624,0.004017274,0.008566957],"category_scores_gemma":[0.018165344,0.0016006534,0.0013138321,0.001854049,0.0024994118,0.0065755933,0.0019513745,0.0030571802,0.00099491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039518165,0.00040878836,0.00049106515,0.0003222576,0.00011921793,0.00021831965,0.00011500865,0.7886366,0.0014545174,0.17930327,0.0047221063,0.023813637],"study_design_scores_gemma":[0.000061971885,0.0000723995,0.000090285845,0.000016377422,0.000022882261,0.000037183112,0.000021009,0.9339157,0.00028290105,0.0644722,0.0009882017,0.00001891397],"about_ca_topic_score_codex":0.002981067,"about_ca_topic_score_gemma":0.0027130842,"teacher_disagreement_score":0.008566957,"about_ca_system_score_codex":0.0041730115,"about_ca_system_score_gemma":0.0037098655,"threshold_uncertainty_score":0.030277431},"labels":[],"label_agreement":null},{"id":"W3000635646","doi":"10.1137/16m1107899","title":"The matroid secretary problem for minor-closed classes and random matroids","year":2020,"lang":"en","type":"article","venue":"IRIS Research product catalog (Sapienza University of Rome)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Seventh Framework Programme","keywords":"Matroid; Combinatorics; Minor (academic); Mathematics; Matroid partitioning; Graphic matroid; Conjecture; Weighted matroid; Oriented matroid; Discrete mathematics; Law","score_opus":0.0464255519365953,"score_gpt":0.2876908832998089,"score_spread":0.2412653313632136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3000635646","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36867237,0.00053365744,0.60720074,0.0024096484,0.00008951466,0.0002875487,0.00078963686,0.00097090873,0.019046046],"genre_scores_gemma":[0.7984821,0.00045850404,0.18800876,0.0003836749,0.000213357,0.00033136233,0.0013483105,0.00030819033,0.010465748],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99741864,0.00085410516,0.00011218245,0.0006702408,0.0004884504,0.0004564653],"domain_scores_gemma":[0.9890314,0.0070039975,0.00078815187,0.0016620428,0.00050631893,0.0010081001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022906284,0.00066848285,0.0015200886,0.00088940095,0.0014392047,0.0040311622,0.002330087,0.0013209356,0.005943193],"category_scores_gemma":[0.012730221,0.00068056275,0.0013639962,0.0015166786,0.00160979,0.005387186,0.0018881012,0.0026919446,0.000875275],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013858648,0.0010391752,0.0063959938,0.00048518908,0.00018652026,0.00025935008,0.0009899504,0.13332075,0.014815556,0.670485,0.022889288,0.14774732],"study_design_scores_gemma":[0.0001819713,0.00021690958,0.0011854167,0.000030913845,0.00005451549,0.0005361411,0.00025553894,0.64456546,0.0072229453,0.3336668,0.012044185,0.000039229915],"about_ca_topic_score_codex":0.002325312,"about_ca_topic_score_gemma":0.002266439,"teacher_disagreement_score":0.005943193,"about_ca_system_score_codex":0.0017386947,"about_ca_system_score_gemma":0.0015325994,"threshold_uncertainty_score":0.019881904},"labels":[],"label_agreement":null},{"id":"W3004144975","doi":"10.1007/s00453-023-01201-4","title":"Approximations for Throughput Maximization","year":2024,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Las vegas; Combinatorics; Schedule; Approximation algorithm; Mathematics; Computer science; Discrete mathematics; Algorithm","score_opus":0.018538962459733195,"score_gpt":0.28992695283353953,"score_spread":0.27138799037380634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3004144975","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005526538,0.0023882636,0.9579864,0.0017993404,0.00035428375,0.000101685175,0.0003004216,0.0005282121,0.031014886],"genre_scores_gemma":[0.50778705,0.006604339,0.41373393,0.0016405068,0.001715962,0.0011138335,0.0011926078,0.0017109109,0.06450081],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962787,0.0016039468,0.000104316125,0.0004644107,0.0009897946,0.0005588349],"domain_scores_gemma":[0.9854813,0.011190814,0.00052922696,0.0013358856,0.0010133885,0.00044936693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005738887,0.00286791,0.003007311,0.002737106,0.0016775237,0.005015148,0.0046354127,0.003501099,0.017564133],"category_scores_gemma":[0.03637027,0.0016281636,0.0023827562,0.0043900935,0.00328396,0.006576914,0.0037021856,0.006700359,0.003786553],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016189144,0.00010873325,0.00030037118,0.00024796347,0.000056401674,0.000080255646,0.0001854097,0.37239847,0.00053992175,0.5744055,0.01761232,0.033902843],"study_design_scores_gemma":[0.000013146583,0.000014188896,0.00007643856,0.00004888192,0.000020319614,0.00003495373,0.000025991192,0.72561264,0.0002196939,0.2705038,0.0034204682,0.00000953318],"about_ca_topic_score_codex":0.0064581824,"about_ca_topic_score_gemma":0.005042696,"teacher_disagreement_score":0.017564133,"about_ca_system_score_codex":0.006925167,"about_ca_system_score_gemma":0.00386436,"threshold_uncertainty_score":0.0587579},"labels":[],"label_agreement":null},{"id":"W3005850668","doi":"10.1007/s12530-020-09327-4","title":"On utilizing an enhanced object partitioning scheme to optimize self-organizing lists-on-lists","year":2020,"lang":"en","type":"article","venue":"Evolving Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Process (computing); Field (mathematics); Scrambling; Data structure; Object (grammar); Scheme (mathematics); Locality; Theoretical computer science; Data mining; Algorithm; Artificial intelligence; Programming language","score_opus":0.036181035902850156,"score_gpt":0.278014047605634,"score_spread":0.24183301170278382,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3005850668","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040574837,0.00029212266,0.95502007,0.00014512031,0.00005837864,0.00008395307,0.000029556595,0.00026066386,0.003535202],"genre_scores_gemma":[0.44345748,0.0003367824,0.55025595,0.00019955801,0.00006271738,0.00022749492,0.00014158874,0.00015530102,0.0051631676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998462,0.00004865412,0.000008550321,0.00002182427,0.00005591906,0.000018814375],"domain_scores_gemma":[0.9996171,0.00017499259,0.000027877766,0.000054278506,0.00010294006,0.000022722053],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006391981,0.00045068792,0.00066494395,0.0005742862,0.0006128028,0.00064398226,0.0011118259,0.00089635875,0.0018561188],"category_scores_gemma":[0.0015158902,0.0002759113,0.00035403902,0.00082869845,0.00043455904,0.0010526653,0.0007775356,0.00050598657,0.00033530698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007381582,0.00008137927,0.00043006628,0.00007554195,0.000030501835,0.000025971734,0.00007864055,0.8648615,0.008136774,0.016736824,0.0013468281,0.108122185],"study_design_scores_gemma":[0.000005613325,0.000029644576,0.00006260991,0.0000027690148,0.000004685017,0.000008184431,0.000006074953,0.99715173,0.00071988284,0.0015743795,0.00043038858,0.00000400293],"about_ca_topic_score_codex":0.0037033642,"about_ca_topic_score_gemma":0.0057989657,"teacher_disagreement_score":0.0037033642,"about_ca_system_score_codex":0.00056689215,"about_ca_system_score_gemma":0.0006044276,"threshold_uncertainty_score":0.0073636174},"labels":[],"label_agreement":null},{"id":"W3006243781","doi":"","title":"Algorithmes pour voyager sur un graphe contenant des blocages","year":2019,"lang":"fr","type":"dissertation","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Humanities; Philosophy; Physics","score_opus":0.01995597148899109,"score_gpt":0.23585396109927192,"score_spread":0.21589798961028084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006243781","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15203868,0.0005642596,0.83246094,0.0015162088,0.000080709106,0.0005138559,0.00062502775,0.0049785315,0.007221793],"genre_scores_gemma":[0.26924258,0.00018629173,0.7236758,0.00026608337,0.000051998988,0.00037802407,0.0013248688,0.00045743247,0.004416998],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99843353,0.00027382615,0.00007578444,0.000575721,0.00033677495,0.00030423084],"domain_scores_gemma":[0.99618983,0.002520814,0.0003662834,0.00036964257,0.00032763008,0.00022581426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014281757,0.0015632295,0.0017810287,0.0015683076,0.0014000969,0.0025642614,0.0034540815,0.0033125156,0.0057697743],"category_scores_gemma":[0.0071050655,0.0008728614,0.0014322809,0.0018954708,0.0017468517,0.003602764,0.001438506,0.0024342258,0.0010492157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00075032935,0.00059962814,0.0039408575,0.00043647364,0.00017692031,0.00020595505,0.0005905395,0.62539834,0.010033567,0.08010371,0.011063243,0.26670042],"study_design_scores_gemma":[0.00010849238,0.00011425556,0.00036109536,0.000017826394,0.00002091328,0.00008784171,0.000095565934,0.9656105,0.0021573994,0.029293826,0.0021157684,0.000016508571],"about_ca_topic_score_codex":0.015233055,"about_ca_topic_score_gemma":0.017935662,"teacher_disagreement_score":0.015233055,"about_ca_system_score_codex":0.0032751597,"about_ca_system_score_gemma":0.0028931913,"threshold_uncertainty_score":0.030288756},"labels":[],"label_agreement":null},{"id":"W3013877464","doi":"10.4230/lipics.opodis.2019.24","title":"Oblivious Permutations on the Plane","year":2020,"lang":"en","type":"preprint","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Robot; Permutation (music); Class (philosophy); Computer science; Plane (geometry); Euclidean geometry; Mobile robot; Algorithm; Theoretical computer science; Mathematics; Artificial intelligence; Geometry","score_opus":0.05331678362262645,"score_gpt":0.2853190603340678,"score_spread":0.23200227671144133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3013877464","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15713973,0.00018877583,0.83042413,0.00043402333,0.00004434718,0.00010910909,0.00017593661,0.00030368607,0.011180349],"genre_scores_gemma":[0.8104978,0.00044275838,0.18003896,0.00009610341,0.00004599366,0.00025037426,0.00026041904,0.0000747904,0.00829268],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99916244,0.00030556085,0.00005308824,0.00016416187,0.00015955836,0.00015507001],"domain_scores_gemma":[0.9988354,0.00057810714,0.00020509744,0.00022029738,0.00007748963,0.00008363404],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004983955,0.0005577756,0.00066133717,0.00029537923,0.0005885221,0.001305575,0.0007900437,0.0007296942,0.002449798],"category_scores_gemma":[0.0021222027,0.00026097675,0.0006200646,0.0006110272,0.0014729805,0.0021916179,0.00107651,0.0010971068,0.0004957053],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024987344,0.00005194826,0.0005318857,0.00006569775,0.00002811599,0.00027706067,0.00022154023,0.5898035,0.0045414357,0.38538754,0.0007588375,0.018082492],"study_design_scores_gemma":[0.000113336544,0.00010115568,0.00023821616,0.000010008169,0.000015640106,0.00009409523,0.0001327715,0.6880375,0.003172182,0.30226567,0.0057995445,0.000019876798],"about_ca_topic_score_codex":0.0019736127,"about_ca_topic_score_gemma":0.0013419177,"teacher_disagreement_score":0.002449798,"about_ca_system_score_codex":0.0007449864,"about_ca_system_score_gemma":0.00072715944,"threshold_uncertainty_score":0.00819546},"labels":[],"label_agreement":null},{"id":"W3018254556","doi":"10.1007/s00453-024-01286-5","title":"Symmetry Breaking in the Plane","year":2024,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais","funders":"","keywords":"Symmetry breaking; Theory of computation; Combinatorics; Mathematics; Computer science; Symmetry (geometry); Discrete mathematics; Physics; Theoretical physics; Geometry; Algorithm; Quantum mechanics","score_opus":0.014734001092750504,"score_gpt":0.26918003697773385,"score_spread":0.2544460358849833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3018254556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33733374,0.0032110054,0.37458047,0.006863011,0.0010089187,0.0002001346,0.00074585306,0.00052371627,0.27553326],"genre_scores_gemma":[0.9317668,0.0013252322,0.038797915,0.00076546456,0.0004388175,0.0001435982,0.0005862637,0.00027239442,0.025903527],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99903095,0.0003265733,0.000036668334,0.00015001518,0.00026227592,0.0001935165],"domain_scores_gemma":[0.9984811,0.000655363,0.00019401133,0.0003898496,0.00014640596,0.00013334356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009723058,0.0005658185,0.0010297298,0.0009933729,0.0014728949,0.003330774,0.0011175643,0.0013429737,0.01178236],"category_scores_gemma":[0.0052276268,0.00038549557,0.0014013721,0.0009351983,0.0027533665,0.0044147884,0.0019243264,0.0035212343,0.0015480673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000058617665,0.00002099867,0.00015813795,0.000034608704,0.000014132637,0.00004355584,0.00006055931,0.004861865,0.00040739318,0.9822204,0.0034424942,0.008677253],"study_design_scores_gemma":[0.00001572113,0.000009055841,0.00006516923,0.0000061365176,0.0000031610869,0.00002611264,0.000026956219,0.009350431,0.00014233931,0.9889796,0.001371812,0.0000034797101],"about_ca_topic_score_codex":0.0014060296,"about_ca_topic_score_gemma":0.00068071525,"teacher_disagreement_score":0.01178236,"about_ca_system_score_codex":0.001003337,"about_ca_system_score_gemma":0.00097610534,"threshold_uncertainty_score":0.039415896},"labels":[],"label_agreement":null},{"id":"W3021544669","doi":"10.1016/j.dam.2020.04.031","title":"Preface: CALDAM 2016","year":2020,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Mathematics; Metric (unit); Approximation algorithm; Combinatorics; Applied mathematics","score_opus":0.027686436379464836,"score_gpt":0.2527815976058852,"score_spread":0.22509516122642037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021544669","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00091969,0.0379089,0.0025668675,0.053076,0.693748,0.00016527051,0.006012485,0.0004767482,0.20512608],"genre_scores_gemma":[0.012966128,0.012523778,0.0010341951,0.00517507,0.1344714,0.00012095301,0.0029028582,0.0006476421,0.830158],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988167,0.00019357227,0.000078741636,0.00026172624,0.00054942514,0.00009986488],"domain_scores_gemma":[0.99529415,0.0005833712,0.00023826137,0.00032325546,0.0025943597,0.00096661464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016602885,0.0014764203,0.0010332691,0.0031642353,0.0022854568,0.005222533,0.0012165995,0.0019323013,0.24549292],"category_scores_gemma":[0.010689188,0.00036554193,0.000652819,0.0020207998,0.00084606773,0.0021734494,0.0022342082,0.0027254103,0.13161574],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000348434,0.000008859897,0.00004605816,0.00007747756,0.000002808888,0.000025027039,0.000017016853,0.000112692534,0.000044251603,0.002546005,0.9851414,0.01194365],"study_design_scores_gemma":[0.000011402902,0.000016609156,0.0003706329,0.00022334541,0.000003681444,0.000035828794,0.000029162768,0.0001397296,0.00010605825,0.0025890588,0.9964669,0.0000075851112],"about_ca_topic_score_codex":0.005776296,"about_ca_topic_score_gemma":0.010701444,"teacher_disagreement_score":0.24549292,"about_ca_system_score_codex":0.005209865,"about_ca_system_score_gemma":0.002319378,"threshold_uncertainty_score":0.8212556},"labels":[],"label_agreement":null},{"id":"W3021723940","doi":"10.1007/978-0-387-34735-6_8","title":"Distributed Algorithms for Autonomous Mobile Robots","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mobile robot; Robot; Computer science; Robotics; Artificial intelligence; Variety (cybernetics); Computability; Set (abstract data type); Focus (optics); Task (project management); Distributed computing; Distributed algorithm; Human–computer interaction; Algorithm; Engineering; Systems engineering","score_opus":0.019566349700235516,"score_gpt":0.2733669439739512,"score_spread":0.2538005942737157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3021723940","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003757274,0.0080980575,0.9714807,0.0022156197,0.00038635108,0.00007553123,0.00006181598,0.0002939313,0.013630674],"genre_scores_gemma":[0.4427142,0.012417316,0.5120073,0.001051045,0.0014330191,0.0012393801,0.00047919585,0.0003035694,0.028354919],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988883,0.00044699013,0.00005818328,0.0001758958,0.00034627927,0.00008429742],"domain_scores_gemma":[0.99841535,0.0010648157,0.00010067267,0.00016646228,0.00019335208,0.000059289236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013378789,0.0009993493,0.00095948036,0.00073717843,0.00060138694,0.0015814871,0.0014685421,0.001701606,0.004151165],"category_scores_gemma":[0.0068813562,0.00036347343,0.00048318997,0.0012533726,0.0016366434,0.0018326794,0.0021177873,0.002518339,0.0011904592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047659494,0.00004079099,0.00031758408,0.00023562885,0.000054255554,0.00007357007,0.00016418919,0.23085321,0.000600771,0.68014216,0.009508784,0.077961475],"study_design_scores_gemma":[0.00005489884,0.000026003278,0.00008242825,0.00003081423,0.0000093248345,0.00003577368,0.000030462525,0.471025,0.00016922342,0.51022583,0.01830181,0.000008321147],"about_ca_topic_score_codex":0.0020714398,"about_ca_topic_score_gemma":0.0012753408,"teacher_disagreement_score":0.004151165,"about_ca_system_score_codex":0.0016607582,"about_ca_system_score_gemma":0.0011221552,"threshold_uncertainty_score":0.013887048},"labels":[],"label_agreement":null},{"id":"W3022187609","doi":"10.1016/j.ipl.2020.105973","title":"Randomized distributed online algorithms against adaptive offline adversaries","year":2020,"lang":"en","type":"article","venue":"Information Processing Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Danmarks Frie Forskningsfond","keywords":"Adversary; Competitive analysis; Adversary model; Online algorithm; Computer science; Randomized algorithm; Randomization; Algorithm; Deterministic algorithm; Theoretical computer science; Mathematics; Upper and lower bounds; Computer security; Randomized controlled trial","score_opus":0.025858568714240946,"score_gpt":0.24563019098400907,"score_spread":0.21977162226976812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022187609","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06052782,0.00081020826,0.922963,0.0028667864,0.0004974395,0.00028090627,0.00028429608,0.0015888778,0.010180675],"genre_scores_gemma":[0.8796347,0.0003392511,0.10938215,0.00079389615,0.00038423788,0.0005244802,0.0002509196,0.0003430194,0.008347459],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9916642,0.00365449,0.0003435314,0.0017116738,0.0015455309,0.0010805536],"domain_scores_gemma":[0.9509995,0.036821924,0.002193287,0.007032354,0.0017410248,0.0012118641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008544007,0.0025995765,0.0033646517,0.001293684,0.0015594125,0.003034162,0.0048035597,0.0044764797,0.0051418254],"category_scores_gemma":[0.035215706,0.0013404998,0.0011526413,0.0017869881,0.0042564115,0.0061794636,0.007237494,0.0055238185,0.0013192659],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029147516,0.0004942759,0.0010779328,0.00027613016,0.0001796904,0.00016128155,0.0001218388,0.8456045,0.0039354456,0.08725231,0.0076129474,0.050368864],"study_design_scores_gemma":[0.00016709008,0.00011280399,0.00009080009,0.000015681615,0.000019461517,0.00004582387,0.000017580256,0.958276,0.001233003,0.039569303,0.00043940078,0.000013020617],"about_ca_topic_score_codex":0.00092480046,"about_ca_topic_score_gemma":0.0011462622,"teacher_disagreement_score":0.008544007,"about_ca_system_score_codex":0.0027508643,"about_ca_system_score_gemma":0.003488828,"threshold_uncertainty_score":0.045185626},"labels":[],"label_agreement":null},{"id":"W3022352819","doi":"10.1007/s00453-023-01122-2","title":"Almost Universal Anonymous Rendezvous in the Plane","year":2023,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche","keywords":"Rendezvous; Theory of computation; Set (abstract data type); Computer science; Algorithm; Plane (geometry); Mathematics; Combinatorics; Geometry; Physics","score_opus":0.02015590187175076,"score_gpt":0.25314379735999765,"score_spread":0.2329878954882469,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3022352819","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4879509,0.0014122874,0.4220073,0.0019054555,0.00012738848,0.0000947256,0.00089838874,0.0011876727,0.084415875],"genre_scores_gemma":[0.96908474,0.0005646023,0.018667681,0.00016292087,0.00006814448,0.00005490591,0.0002726138,0.0001687794,0.010955591],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9981833,0.00043342187,0.000066588844,0.00039884925,0.00040383296,0.00051387167],"domain_scores_gemma":[0.993719,0.0039040882,0.0006683386,0.0009846573,0.00033926519,0.00038468867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012017087,0.0007657252,0.0015406968,0.0012473618,0.0021500231,0.0035611736,0.0015613649,0.0016048828,0.007535802],"category_scores_gemma":[0.008784006,0.0005831651,0.0008332784,0.0019698227,0.0030664604,0.007102996,0.004455106,0.0025123237,0.0010080107],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037432899,0.000051300114,0.0005244062,0.000105670566,0.00005884258,0.00015880408,0.0003715888,0.05156649,0.0012421771,0.9263704,0.0033888833,0.01578703],"study_design_scores_gemma":[0.000052390245,0.000021427548,0.00016975832,0.00002136741,0.000025646053,0.0001316425,0.00016520395,0.078871906,0.0011856761,0.91667587,0.0026597704,0.000019264013],"about_ca_topic_score_codex":0.002450037,"about_ca_topic_score_gemma":0.001669115,"teacher_disagreement_score":0.007535802,"about_ca_system_score_codex":0.0014310776,"about_ca_system_score_gemma":0.00093936326,"threshold_uncertainty_score":0.025209785},"labels":[],"label_agreement":null},{"id":"W3023308714","doi":"10.1007/s00453-020-00724-4","title":"Deterministic Treasure Hunt in the Plane with Angular Hints","year":2020,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Agence Nationale de la Recherche","keywords":"Treasure; Combinatorics; Vertex (graph theory); Plane (geometry); Position (finance); Mathematics; Euclidean geometry; Algorithm; Computer science; Topology (electrical circuits); Geometry; Finance","score_opus":0.02181661713673369,"score_gpt":0.22067070731841365,"score_spread":0.19885409018167996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023308714","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14405377,0.0015435183,0.82271814,0.0012056184,0.00021336952,0.000093705625,0.0004463737,0.0007222226,0.0290033],"genre_scores_gemma":[0.85417783,0.0006895856,0.13064553,0.00035455736,0.000092292496,0.00017492923,0.00042652918,0.00019959758,0.013239197],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999052,0.00037093126,0.00004127047,0.00015843449,0.00016570352,0.00021160598],"domain_scores_gemma":[0.99614704,0.0029457617,0.00020646173,0.00034906555,0.00016430233,0.00018727373],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013443878,0.0009033383,0.0017667977,0.00076545053,0.0008637757,0.0026025453,0.0017554882,0.0023332536,0.005728704],"category_scores_gemma":[0.00897454,0.00080671406,0.00089896016,0.0013437861,0.0022011937,0.0040995106,0.0032559359,0.0028652125,0.00090154336],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010592311,0.00011484171,0.0007794221,0.00019627537,0.00009656973,0.00012340967,0.00014224942,0.5343051,0.0015296113,0.42942536,0.005240326,0.026987545],"study_design_scores_gemma":[0.00011080888,0.000079670746,0.00012953773,0.000028784527,0.000018138719,0.00003705221,0.00003441658,0.6949027,0.00048659666,0.30310518,0.0010406732,0.000026430518],"about_ca_topic_score_codex":0.0016748968,"about_ca_topic_score_gemma":0.0017406879,"teacher_disagreement_score":0.005728704,"about_ca_system_score_codex":0.0009047148,"about_ca_system_score_gemma":0.0010500482,"threshold_uncertainty_score":0.019164383},"labels":[],"label_agreement":null},{"id":"W3023452807","doi":"10.1016/j.tcs.2010.01.007","title":"Remembering without memory: Tree exploration by asynchronous oblivious robots","year":2010,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":91,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais; University of Ottawa","funders":"Agence Nationale de la Recherche","keywords":"Robot; Computer science; Asynchronous communication; Task (project management); Theoretical computer science; Node (physics); Tree (set theory); Swarm robotics; Graph; Mobile robot; Constructive; Self-reconfiguring modular robot; Computation; Distributed computing; Algorithm; Artificial intelligence; Mathematics; Robot control; Combinatorics","score_opus":0.013010429633134717,"score_gpt":0.25849732909190537,"score_spread":0.24548689945877064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3023452807","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44692576,0.0010743415,0.537434,0.0009363476,0.00012230265,0.00007304041,0.00011850508,0.0010552024,0.012260476],"genre_scores_gemma":[0.9624926,0.00019724932,0.034217514,0.00006570617,0.000025320658,0.00004585792,0.000050990362,0.00008103383,0.0028237607],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99963903,0.00012912955,0.000019482393,0.00007169514,0.00005866987,0.00008208584],"domain_scores_gemma":[0.99665904,0.0021291426,0.00020895757,0.0005956344,0.00017579235,0.00023141276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076142413,0.00039844547,0.0009033448,0.00037274213,0.00083512766,0.0011526698,0.0016785869,0.0010270845,0.0032988458],"category_scores_gemma":[0.006282762,0.00037205112,0.0004161393,0.0005574174,0.0010874217,0.003714463,0.0016714671,0.0011159749,0.0003135689],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024613913,0.000266484,0.00243703,0.0004196312,0.00014660157,0.0004795704,0.0013101001,0.6440491,0.012436334,0.18594751,0.0056365994,0.14440973],"study_design_scores_gemma":[0.00007943734,0.0000994724,0.00016938958,0.000012399112,0.000030680752,0.00006259315,0.00009088526,0.83950436,0.0017748219,0.15721622,0.0009449671,0.00001477726],"about_ca_topic_score_codex":0.0012230602,"about_ca_topic_score_gemma":0.0012626859,"teacher_disagreement_score":0.0032988458,"about_ca_system_score_codex":0.00038918384,"about_ca_system_score_gemma":0.0006465344,"threshold_uncertainty_score":0.01103574},"labels":[],"label_agreement":null},{"id":"W3026866611","doi":"10.1007/s00453-021-00920-w","title":"Online Coloring and a New Type of Adversary for Online Graph Problems","year":2022,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Combinatorics; Parameterized complexity; Adversary; Bipartite graph; Competitive analysis; Bounded function; Discrete mathematics; Treewidth; Upper and lower bounds; Graph; Computer science; Line graph; Pathwidth","score_opus":0.0654509948533736,"score_gpt":0.2981127694963594,"score_spread":0.2326617746429858,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3026866611","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021847976,0.00040702242,0.9588748,0.0027075375,0.00047309112,0.00014558701,0.00024940053,0.00038762196,0.014906945],"genre_scores_gemma":[0.6234045,0.0012622272,0.33206433,0.0021208073,0.0021095735,0.00064877514,0.0005701364,0.00061482994,0.03720483],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99103206,0.004208416,0.0002909648,0.0015970574,0.0017665587,0.0011048808],"domain_scores_gemma":[0.9635691,0.023717051,0.0015713818,0.00751514,0.0015286976,0.0020986602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007023316,0.0020612206,0.0024071157,0.0016667568,0.0024888357,0.004793638,0.0074670757,0.005973766,0.0071485196],"category_scores_gemma":[0.024255617,0.0013878623,0.0035311782,0.0028151067,0.006526103,0.01294186,0.0074741687,0.011615265,0.0010627639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00050037605,0.00031561303,0.0010964546,0.00022051249,0.0001198653,0.0002240137,0.00025357897,0.11819286,0.0028738072,0.8416513,0.0108036045,0.023748009],"study_design_scores_gemma":[0.00007543166,0.00011125974,0.00017952637,0.000028069793,0.000053708343,0.00019187052,0.000048806956,0.4844315,0.0009915059,0.50813204,0.0057184095,0.000037740636],"about_ca_topic_score_codex":0.0011694623,"about_ca_topic_score_gemma":0.0019982478,"teacher_disagreement_score":0.0074670757,"about_ca_system_score_codex":0.0034012515,"about_ca_system_score_gemma":0.0027178624,"threshold_uncertainty_score":0.03714329},"labels":[],"label_agreement":null},{"id":"W3031249145","doi":"","title":"Combinatorial batch codes.","year":2008,"lang":"en","type":"preprint","venue":"IACR Cryptology ePrint Archive","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Lakehead University; University of Waterloo","funders":"","keywords":"Server; Computer science; Code (set theory); Probabilistic logic; Theoretical computer science; Discrete mathematics; Operating system; Mathematics; Programming language; Artificial intelligence; Set (abstract data type)","score_opus":0.022903451522838063,"score_gpt":0.2719641128123258,"score_spread":0.24906066128948773,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3031249145","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047787905,0.0037136488,0.8757813,0.0015118936,0.000743942,0.00026699287,0.0012345554,0.00050425704,0.06845549],"genre_scores_gemma":[0.64100134,0.0042482237,0.29225785,0.0014980009,0.0012099766,0.0007849544,0.0022217776,0.00046924318,0.056308623],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984434,0.00051323575,0.00006290344,0.0002720983,0.00044965438,0.00025878093],"domain_scores_gemma":[0.99515593,0.0026661393,0.0005756793,0.0008013573,0.0005536856,0.00024726082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013842876,0.001038453,0.000946948,0.0011463446,0.0009838683,0.0019264807,0.0016228341,0.0015930549,0.010161434],"category_scores_gemma":[0.0071120188,0.0005591801,0.00089599413,0.0018331716,0.0019875017,0.0031470084,0.0015901006,0.0022892177,0.0019545048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015725181,0.00006665647,0.00059042673,0.00019692312,0.000035827296,0.000105787636,0.00006652742,0.059471916,0.0015960339,0.89933014,0.010416752,0.027965732],"study_design_scores_gemma":[0.000083860534,0.00016457801,0.0003708821,0.0000712314,0.00003761834,0.00048249846,0.00006338443,0.335972,0.002884642,0.63096404,0.028846508,0.00005875725],"about_ca_topic_score_codex":0.0016169493,"about_ca_topic_score_gemma":0.0016121654,"teacher_disagreement_score":0.010161434,"about_ca_system_score_codex":0.0018746129,"about_ca_system_score_gemma":0.0015373973,"threshold_uncertainty_score":0.033993363},"labels":[],"label_agreement":null},{"id":"W3031729887","doi":"10.1007/978-3-030-49161-1_20","title":"Optimizing Self-organizing Lists-on-Lists Using Transitivity and Pursuit-Enhanced Object Partitioning","year":2020,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Theoretical computer science; Context (archaeology); Probabilistic logic; Filter (signal processing); Object (grammar); Transitive relation; Artificial intelligence; Mathematics; Computer vision; Combinatorics","score_opus":0.015370842572621935,"score_gpt":0.259489397901025,"score_spread":0.24411855532840304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3031729887","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027030895,0.00030983344,0.96802014,0.000110616944,0.00004815419,0.00004607587,0.000067772235,0.00058560463,0.0037809424],"genre_scores_gemma":[0.53800666,0.00032188508,0.45143732,0.00014541256,0.00008670817,0.00022062116,0.00038754634,0.00032818175,0.0090656625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972385,0.0000710139,0.000015208279,0.000054567343,0.00007810174,0.00005724441],"domain_scores_gemma":[0.99930835,0.00041602078,0.000053570075,0.00007158303,0.00010236853,0.000048078236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058808277,0.0008905979,0.001385478,0.00062976877,0.00066466205,0.0012837517,0.0019343826,0.001329686,0.0038908806],"category_scores_gemma":[0.0016292467,0.0006996765,0.00059207587,0.0012438601,0.00060515385,0.0017783917,0.00169839,0.0007916259,0.0007198698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016657289,0.00010574516,0.00024832383,0.00010810179,0.00004364501,0.000035466972,0.000058795787,0.8906981,0.0051619573,0.015064712,0.0034913183,0.084817275],"study_design_scores_gemma":[0.000006544992,0.000027289532,0.000023944947,0.0000023098441,0.0000035455982,0.0000070751503,0.0000073849415,0.99729735,0.00043288217,0.0020000888,0.00018889761,0.0000027794365],"about_ca_topic_score_codex":0.0030576147,"about_ca_topic_score_gemma":0.003803488,"teacher_disagreement_score":0.0038908806,"about_ca_system_score_codex":0.00084453775,"about_ca_system_score_gemma":0.00087838504,"threshold_uncertainty_score":0.0130162835},"labels":[],"label_agreement":null},{"id":"W3033345754","doi":"","title":"Synchronization by Asynchronous Mobile Robots with Limited Visibility","year":2020,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Asynchronous communication; Robot; Mobile robot; Synchronizing; Visibility; Computer science; Real-time computing; Synchronization (alternating current); Schedule; Computation; Distributed computing; Algorithm; Artificial intelligence; Computer network; Channel (broadcasting)","score_opus":0.03706273716227314,"score_gpt":0.17172622267036483,"score_spread":0.1346634855080917,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3033345754","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21045938,0.00015937864,0.7848376,0.00026215572,0.00004488455,0.00011603051,0.000059287628,0.0006081936,0.0034531103],"genre_scores_gemma":[0.95278436,0.00007766407,0.044966515,0.000063413325,0.000029347915,0.00016878931,0.000050194216,0.000041104257,0.0018186286],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99775237,0.0005780853,0.00016958988,0.0006028051,0.000547845,0.00034931712],"domain_scores_gemma":[0.9936854,0.0032865643,0.0012762025,0.00098888,0.000380069,0.00038278478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013966004,0.00061951415,0.0008798087,0.0005555321,0.00075562845,0.0011941184,0.0016011655,0.0009002352,0.0012924032],"category_scores_gemma":[0.0078181075,0.0005163013,0.0006743981,0.00043002734,0.0019430842,0.0017923121,0.002843518,0.0011888552,0.00023166477],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014823931,0.00014953288,0.0034391594,0.00021993769,0.000101058846,0.0006799195,0.0010019612,0.68795466,0.052397665,0.2249821,0.00090950535,0.026682138],"study_design_scores_gemma":[0.00014750421,0.0001961857,0.0003035661,0.000016355054,0.000025602194,0.000067999084,0.00006639456,0.9584509,0.008000481,0.03129025,0.0014159892,0.000018859302],"about_ca_topic_score_codex":0.001994481,"about_ca_topic_score_gemma":0.0015328957,"teacher_disagreement_score":0.001994481,"about_ca_system_score_codex":0.0010454571,"about_ca_system_score_gemma":0.0012013253,"threshold_uncertainty_score":0.007585287},"labels":[],"label_agreement":null},{"id":"W3035592717","doi":"10.24963/ijcai.2020/562","title":"Multi-Directional Heuristic Search","year":2020,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Israel Science Foundation; National Science Foundation","keywords":"Heuristics; Mathematical optimization; Heuristic; Computer science; Task (project management); Path (computing); Bidirectional search; Consistent heuristic; Algorithm; Search algorithm; Best-first search; Incremental heuristic search; Beam search; Mathematics; Engineering","score_opus":0.08922955930922948,"score_gpt":0.298222700249762,"score_spread":0.2089931409405325,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3035592717","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.030113056,0.0010655926,0.9515548,0.00028369026,0.000100451296,0.00021477998,0.00014526173,0.00075201795,0.01577031],"genre_scores_gemma":[0.47665522,0.00052822515,0.51601547,0.00033539883,0.000040253173,0.0005232876,0.00036570022,0.0001628622,0.0053735846],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988954,0.0005159936,0.000065248714,0.00014929798,0.0002479006,0.00012605201],"domain_scores_gemma":[0.9987245,0.00068350474,0.00013923238,0.0001911561,0.0001777258,0.00008387434],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015830178,0.0010944038,0.001068179,0.001275334,0.0007994704,0.0013899886,0.0014926234,0.0017400682,0.0046000453],"category_scores_gemma":[0.00432856,0.00052584615,0.0009459295,0.001370576,0.00065542985,0.0014235929,0.001609777,0.00088969845,0.0009761931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004533274,0.00026007972,0.0013105191,0.00036733336,0.00013802116,0.00013880644,0.00020353221,0.6966979,0.0035280066,0.059646007,0.005692079,0.23156433],"study_design_scores_gemma":[0.00007236729,0.00013875499,0.0001221957,0.000039232407,0.00003308537,0.000078585195,0.00008378413,0.978243,0.0012278805,0.01456932,0.005374272,0.000017524882],"about_ca_topic_score_codex":0.0024905992,"about_ca_topic_score_gemma":0.0038240203,"teacher_disagreement_score":0.0046000453,"about_ca_system_score_codex":0.0007393175,"about_ca_system_score_gemma":0.0015081406,"threshold_uncertainty_score":0.015388668},"labels":[],"label_agreement":null},{"id":"W3037022759","doi":"10.1609/socs.v11i1.18525","title":"Moving Agents in Formation in Congested Environments","year":2020,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Swarm behaviour; Computer science; Focus (optics); Path (computing); Phase (matter); Swarm robotics; Field (mathematics); Algorithm; Mathematical optimization; Artificial intelligence; Mathematics; Physics","score_opus":0.03289317222300333,"score_gpt":0.26769560564883993,"score_spread":0.2348024334258366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037022759","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20545739,0.0009009752,0.78651613,0.00065738155,0.00010974189,0.000117429285,0.000074169504,0.00029166762,0.005875161],"genre_scores_gemma":[0.91932267,0.00045753267,0.07753182,0.000086431726,0.000042175354,0.00009907868,0.00006951518,0.0000361882,0.0023546172],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993166,0.00027515725,0.000028164146,0.00013982097,0.000111104375,0.00012925173],"domain_scores_gemma":[0.9983015,0.0008210538,0.0003924692,0.00015121227,0.00013741838,0.00019624911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012481016,0.00063324766,0.00057994854,0.00045711632,0.0010423166,0.0010988719,0.001217912,0.0009908114,0.0013512636],"category_scores_gemma":[0.0043046945,0.00048220856,0.00042930178,0.00049220043,0.0017873991,0.0022845306,0.0022144523,0.0007770316,0.00019885009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000067975314,0.000031881336,0.001550325,0.000062090156,0.000025098037,0.00040244346,0.00027656395,0.95649636,0.0015365521,0.03018725,0.00050928426,0.008854237],"study_design_scores_gemma":[0.000028689408,0.00009170137,0.000589045,0.000012685593,0.000018425966,0.0001442588,0.00023036535,0.9729033,0.0010407118,0.021846833,0.0030808686,0.000013036792],"about_ca_topic_score_codex":0.0030717638,"about_ca_topic_score_gemma":0.0020452442,"teacher_disagreement_score":0.0030717638,"about_ca_system_score_codex":0.00065958884,"about_ca_system_score_gemma":0.0006803734,"threshold_uncertainty_score":0.006600678},"labels":[],"label_agreement":null},{"id":"W3042234904","doi":"10.22215/etd/2016-11649","title":"Coordinated Multi-Agents Patrolling Algorithms","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Patrolling; Robot; Mobile robot; Visibility; Computer science; Algorithm; Domain (mathematical analysis); Visibility graph; Artificial intelligence; Mathematics; Geography; Geometry","score_opus":0.03568156763571621,"score_gpt":0.31694906139694323,"score_spread":0.281267493761227,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042234904","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029650804,0.00069833035,0.96112007,0.00032386702,0.00007383357,0.00010045388,0.00009882606,0.0006391613,0.0072945417],"genre_scores_gemma":[0.661967,0.0006100718,0.3283162,0.00017251441,0.00006895541,0.00030685525,0.00030200745,0.0001821153,0.008074366],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922085,0.00018776902,0.000039728213,0.00025912622,0.00015607374,0.0001363763],"domain_scores_gemma":[0.9989391,0.00045354792,0.0001746887,0.00020846992,0.00012406152,0.00010009329],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006419442,0.0009597913,0.001073453,0.0004962523,0.00069354824,0.001332183,0.002125309,0.0010694391,0.002767959],"category_scores_gemma":[0.0022045108,0.00044203282,0.0005700285,0.0009109752,0.0008223468,0.0011803078,0.0015259229,0.00096807093,0.0005945587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007794683,0.000078900026,0.0006316323,0.00008396518,0.00005337472,0.00006013502,0.00009315493,0.9313842,0.001421906,0.02256777,0.0023493872,0.04119759],"study_design_scores_gemma":[0.00003442925,0.000041409767,0.00010492915,0.000006868941,0.000010391544,0.000023337132,0.00002363178,0.988191,0.00056776794,0.009100672,0.0018905397,0.000005060875],"about_ca_topic_score_codex":0.0032285168,"about_ca_topic_score_gemma":0.002591911,"teacher_disagreement_score":0.0032285168,"about_ca_system_score_codex":0.00090111746,"about_ca_system_score_gemma":0.00089261984,"threshold_uncertainty_score":0.009259701},"labels":[],"label_agreement":null},{"id":"W3046340469","doi":"10.4230/lipics.disc.2025.49","title":"A Characterization of Semi-Synchrony for Asynchronous Robots with Limited Visibility, and its Application to Luminous Synchronizer Design","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Asynchronous communication; Robot; Visibility; Computer science; Synchronizing; Mobile robot; Synchronizer; Real-time computing; Synchronization (alternating current); Schedule; Computation; Distributed computing; Algorithm; Artificial intelligence; Channel (broadcasting); Computer network","score_opus":0.07280824242103562,"score_gpt":0.20746736120348225,"score_spread":0.13465911878244663,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3046340469","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03807075,0.00011012537,0.95745325,0.00021445409,0.00002835759,0.0001148178,0.00007204045,0.00032161057,0.0036146326],"genre_scores_gemma":[0.8519559,0.0002461837,0.14381827,0.00017517043,0.000072676616,0.000485051,0.00013472732,0.00013663902,0.002975412],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9965551,0.0007988685,0.00032143854,0.0009413033,0.0009907938,0.0003924887],"domain_scores_gemma":[0.98515004,0.008187222,0.0027979314,0.0018847145,0.0010527924,0.0009271504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028304025,0.00075363606,0.00080387254,0.00073772937,0.0008921781,0.0019540016,0.0018356687,0.0011063631,0.0032918295],"category_scores_gemma":[0.016180668,0.0006731696,0.0009091686,0.00066765957,0.003462642,0.0031767224,0.0030233616,0.002073722,0.00043940058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00064390356,0.00016190592,0.0022201163,0.0003222896,0.000076824705,0.00053206214,0.0010998388,0.28647226,0.04742795,0.6336181,0.0012792741,0.026145414],"study_design_scores_gemma":[0.00012952332,0.00035183653,0.00045299856,0.000048541704,0.000039338956,0.00023312288,0.000117113144,0.8248637,0.0152405,0.15467504,0.0038043545,0.000043983742],"about_ca_topic_score_codex":0.0010612998,"about_ca_topic_score_gemma":0.0009456222,"teacher_disagreement_score":0.0032918295,"about_ca_system_score_codex":0.0014366105,"about_ca_system_score_gemma":0.002029421,"threshold_uncertainty_score":0.014968753},"labels":[],"label_agreement":null},{"id":"W306704402","doi":"10.1007/978-3-642-25835-0_4","title":"Search and Rescue Operations","year":2012,"lang":"en","type":"book-chapter","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"International Civil Aviation Organization","funders":"","keywords":"Search and rescue; Computer science; Artificial intelligence","score_opus":0.05730721572742271,"score_gpt":0.28444444085348686,"score_spread":0.22713722512606416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W306704402","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020021168,0.018980818,0.08411282,0.0020656195,0.0014510092,0.000050789156,0.00025855243,0.00028522938,0.890793],"genre_scores_gemma":[0.044482704,0.021385878,0.028798167,0.00066562067,0.000984603,0.0001108247,0.00047140193,0.00030116425,0.9027996],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998234,0.000029220422,0.000006936985,0.00003300732,0.00008765739,0.000019901263],"domain_scores_gemma":[0.9999435,0.00001603641,0.0000043429213,0.000014263582,0.000015096165,0.000006783952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015717183,0.0012094025,0.000755403,0.0008087711,0.00077895354,0.002079184,0.0007884323,0.0011257902,0.042299744],"category_scores_gemma":[0.00037418387,0.00031870065,0.00046337635,0.0010571928,0.001450088,0.002510797,0.0011170534,0.0019043521,0.01263842],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033198237,0.000039867224,0.00005645218,0.00030710976,0.000011388487,0.000056681452,0.00017821786,0.009309105,0.0018517365,0.5038114,0.14318311,0.3411617],"study_design_scores_gemma":[0.0000061949445,0.000033807242,0.0001945736,0.0001704707,0.000007238529,0.0001582115,0.000121971054,0.006977001,0.0010071541,0.1973262,0.7939807,0.000016331891],"about_ca_topic_score_codex":0.0017909127,"about_ca_topic_score_gemma":0.002719843,"teacher_disagreement_score":0.042299744,"about_ca_system_score_codex":0.0008592919,"about_ca_system_score_gemma":0.0008175694,"threshold_uncertainty_score":0.14150673},"labels":[],"label_agreement":null},{"id":"W3080419432","doi":"10.3233/faia200470","title":"Entropy-based adaptive exploit-explore coefficient for Monte-Carlo path planning","year":2020,"lang":"en","type":"preprint","venue":"Open Archive Toulouse Archive Ouverte (University of Toulouse)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Motion planning; Mathematical optimization; Monte Carlo method; Convergence (economics); Context (archaeology); Entropy (arrow of time); Artificial intelligence; Mathematics; Robot","score_opus":0.08950398227348327,"score_gpt":0.27367719963964565,"score_spread":0.18417321736616238,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3080419432","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.032922696,0.00054731616,0.9619185,0.00018299285,0.00005197332,0.000080604004,0.000052176634,0.0004211204,0.0038226484],"genre_scores_gemma":[0.85392743,0.00030038352,0.14391652,0.00010372941,0.000037766524,0.00021109039,0.00012026936,0.00012303719,0.0012598174],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992918,0.00021071642,0.000035559347,0.000096962416,0.00025725056,0.00010761193],"domain_scores_gemma":[0.99670345,0.002379306,0.0002451159,0.00017020851,0.00038866038,0.00011330397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014216028,0.0007588989,0.00082428806,0.00072529976,0.00043741864,0.0007915259,0.0015588469,0.0010179781,0.0018113693],"category_scores_gemma":[0.008578669,0.00039825976,0.00051664887,0.00044332453,0.0008646902,0.0010595259,0.0012250469,0.0015282414,0.00026241766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006485757,0.0000326163,0.0007468256,0.000046019475,0.000018394287,0.00003613402,0.000040767452,0.9658778,0.0015999915,0.0056723943,0.00036095927,0.025503164],"study_design_scores_gemma":[0.0000053266945,0.000019421313,0.00009782768,0.0000074387717,0.0000043908267,0.000011338652,0.0000039398965,0.9979791,0.00058094854,0.0010833195,0.00020210625,0.0000047566205],"about_ca_topic_score_codex":0.003989973,"about_ca_topic_score_gemma":0.0040813405,"teacher_disagreement_score":0.003989973,"about_ca_system_score_codex":0.00090730767,"about_ca_system_score_gemma":0.0017340239,"threshold_uncertainty_score":0.007933497},"labels":[],"label_agreement":null},{"id":"W3081729211","doi":"10.22215/etd/2015-11117","title":"Searching with Two-Speed Autonomous Mobile Robots","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Patrolling; Robot; Mobile robot; Schedule; Interval (graph theory); Computer science; Domain (mathematical analysis); Rendezvous; Real-time computing; Simulation; Artificial intelligence; Engineering; Mathematics; Geography","score_opus":0.022674069218936405,"score_gpt":0.3183425371563703,"score_spread":0.2956684679374339,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3081729211","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13901284,0.0024428652,0.836051,0.0011406887,0.00023894793,0.00009670411,0.00008034642,0.00014567448,0.02079098],"genre_scores_gemma":[0.7997133,0.002649639,0.18126616,0.00019701227,0.00017759764,0.0002112597,0.00013291025,0.000039536,0.015612559],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99977344,0.00005838197,0.000009122762,0.000055141994,0.00006877326,0.000035138073],"domain_scores_gemma":[0.9996629,0.00014908203,0.00006413193,0.000035878227,0.000040343093,0.00004761323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028737335,0.0007584275,0.00050838105,0.0003925642,0.00035512412,0.0010437628,0.00094780006,0.0012178087,0.0014562377],"category_scores_gemma":[0.0010570079,0.0003377171,0.0006457111,0.0004889151,0.0008687178,0.0016120571,0.0011302884,0.00080444146,0.00028094553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010063141,0.000106927044,0.0012687634,0.00022558354,0.000057327277,0.000265112,0.00019963097,0.7947895,0.009090762,0.16740258,0.0016115358,0.024881575],"study_design_scores_gemma":[0.00004366677,0.00012119321,0.00025196638,0.0000124708695,0.000007824937,0.00010134167,0.000046329023,0.9673136,0.0010603488,0.026524004,0.004500616,0.000016659451],"about_ca_topic_score_codex":0.0012830158,"about_ca_topic_score_gemma":0.0006134836,"teacher_disagreement_score":0.0014562377,"about_ca_system_score_codex":0.00045663616,"about_ca_system_score_gemma":0.00038265032,"threshold_uncertainty_score":0.004871607},"labels":[],"label_agreement":null},{"id":"W3082880435","doi":"10.1007/978-3-030-62401-9_10","title":"Fast Byzantine Gathering with Visibility in Graphs","year":2020,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Robot; Computer science; Node (physics); Task (project management); Graph; Time complexity; Visibility; Identifier; Mobile robot; Theoretical computer science; Algorithm; Combinatorics; Artificial intelligence; Mathematics; Computer network; Engineering; Geography","score_opus":0.02180060328076514,"score_gpt":0.2709419330904639,"score_spread":0.24914132980969875,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082880435","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09663917,0.0004708079,0.88627666,0.0007726994,0.00013757075,0.00028347975,0.00057988806,0.004808326,0.010031271],"genre_scores_gemma":[0.47839415,0.00030039533,0.5112825,0.00015029001,0.00008562361,0.00020839978,0.00087832223,0.0010210837,0.0076793074],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981021,0.0005124388,0.00008907238,0.0004153831,0.00043924738,0.00044165127],"domain_scores_gemma":[0.9933816,0.003211337,0.0004642329,0.002168559,0.00043522727,0.00033913998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014139916,0.0017086806,0.0022154788,0.0017345696,0.002076788,0.0024011359,0.0019494384,0.0016466924,0.007252443],"category_scores_gemma":[0.008415794,0.0010554745,0.0016837296,0.0019236167,0.0016242741,0.0059311707,0.0068239355,0.002156726,0.0016687528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0029528837,0.0005137965,0.0033773761,0.0015967364,0.00029972914,0.000733105,0.001980342,0.19624756,0.047522344,0.17771387,0.030528875,0.5365333],"study_design_scores_gemma":[0.00026121794,0.0003802406,0.000690148,0.000105473584,0.00011185506,0.00028603847,0.00043579986,0.63539267,0.02603793,0.32437536,0.011859822,0.000063443884],"about_ca_topic_score_codex":0.003151102,"about_ca_topic_score_gemma":0.005380478,"teacher_disagreement_score":0.007252443,"about_ca_system_score_codex":0.00088945095,"about_ca_system_score_gemma":0.0015681022,"threshold_uncertainty_score":0.024261892},"labels":[],"label_agreement":null},{"id":"W3090961338","doi":"10.20382/jocg.v11i1a16","title":"Faster algorithms for some optimization problems on collinear points","year":2020,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Waterloo","funders":"","keywords":"Disjoint sets; Interval (graph theory); Dimension (graph theory); Mathematics; Algorithm; Point (geometry); Running time; Combinatorics; Set (abstract data type); Range (aeronautics); Server; Computer science; Geometry","score_opus":0.33922023217704805,"score_gpt":0.5231738900159135,"score_spread":0.18395365783886547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3090961338","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007124652,0.0011309496,0.9780291,0.0008150482,0.00026563075,0.00027949165,0.00034473516,0.0034419445,0.008568445],"genre_scores_gemma":[0.05674362,0.00053035346,0.93410003,0.0005794001,0.0002871909,0.00078438444,0.0013633842,0.0010321323,0.004579476],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99605715,0.0008489357,0.00025478928,0.0012371104,0.0009921732,0.0006097906],"domain_scores_gemma":[0.99294394,0.004117893,0.00046298603,0.0012892104,0.0009951625,0.00019091838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030220698,0.0044847257,0.0028574008,0.0024231097,0.0015719801,0.0029394273,0.0044309855,0.002962064,0.027716069],"category_scores_gemma":[0.01189776,0.0015494765,0.0037797021,0.0041517112,0.0013461385,0.007470639,0.004090338,0.0063712425,0.0081346715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00079137005,0.00087232003,0.001930448,0.0016766825,0.0003964584,0.00036625937,0.00055976654,0.33223,0.006492047,0.114206985,0.049541533,0.49093613],"study_design_scores_gemma":[0.00040446737,0.00013664158,0.0004695718,0.000096846554,0.00008322882,0.00021407478,0.00014332634,0.8236116,0.0021037823,0.15597732,0.016710417,0.000048698526],"about_ca_topic_score_codex":0.004992135,"about_ca_topic_score_gemma":0.0077504492,"teacher_disagreement_score":0.027716069,"about_ca_system_score_codex":0.0025434096,"about_ca_system_score_gemma":0.0027290261,"threshold_uncertainty_score":0.092719495},"labels":[],"label_agreement":null},{"id":"W3091080409","doi":"10.1109/ijcnn48605.2020.9207659","title":"A Novel way of Training a Neural Network with Reinforcement learning and without Back Propagation","year":2020,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Royal Military College of Canada","funders":"","keywords":"Reinforcement learning; Computer science; Artificial neural network; Worry; Gradient descent; Backpropagation; Artificial intelligence; Learning automata; Core (optical fiber); Action (physics); Automaton","score_opus":0.04778871109854664,"score_gpt":0.2548645749179814,"score_spread":0.20707586381943477,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3091080409","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003972796,0.000089096065,0.9935122,0.00012012694,0.000089372305,0.00003376356,0.000013357229,0.0004945349,0.0016747091],"genre_scores_gemma":[0.28915828,0.00018214004,0.7024363,0.00030221906,0.00011634462,0.00025304768,0.00008135497,0.00024369337,0.0072265654],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993901,0.00015194007,0.00004010682,0.00013952008,0.00022156413,0.000056611276],"domain_scores_gemma":[0.99922013,0.00034809462,0.00007271233,0.00011747824,0.00018575325,0.000055926852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001094936,0.001072837,0.0008146375,0.00052123144,0.00050811144,0.000989206,0.0017652056,0.0015762751,0.0032016323],"category_scores_gemma":[0.0034242657,0.0005896217,0.0007170676,0.00037732863,0.0009632757,0.0018119989,0.0011212362,0.002334797,0.0007438429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017065469,0.00023887289,0.001122979,0.00015602197,0.00018592409,0.00018385056,0.00013727498,0.72868115,0.012422868,0.03905029,0.0029710683,0.21467899],"study_design_scores_gemma":[0.000015658394,0.000046776226,0.000055408887,0.00000784289,0.000012227831,0.00003032811,0.0000035216688,0.9927521,0.0019234731,0.0038576298,0.0012876112,0.000007408411],"about_ca_topic_score_codex":0.0045521706,"about_ca_topic_score_gemma":0.0047890404,"teacher_disagreement_score":0.0045521706,"about_ca_system_score_codex":0.0007178854,"about_ca_system_score_gemma":0.00095537683,"threshold_uncertainty_score":0.010710537},"labels":[],"label_agreement":null},{"id":"W3094630273","doi":"10.1145/3340531.3412730","title":"Multi-Channel Sellers Traffic Allocation in Large-scale E-commerce Promotion","year":2020,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Heuristics; Channel (broadcasting); Promotion (chess); Entertainment; Rendering (computer graphics); Telecommunications; Artificial intelligence","score_opus":0.04964900520495525,"score_gpt":0.27411455121353867,"score_spread":0.22446554600858343,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094630273","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22796233,0.0010690892,0.76251,0.00052671117,0.00013123274,0.00013517156,0.00012340207,0.00058870186,0.0069533503],"genre_scores_gemma":[0.9700561,0.00020757537,0.0277015,0.00008312813,0.0000390746,0.000048204973,0.00008854016,0.000055057895,0.0017207472],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993056,0.00025741363,0.00001948132,0.00014367836,0.000107858046,0.00016598712],"domain_scores_gemma":[0.99911326,0.0004559993,0.0000891752,0.00005404449,0.00016392728,0.000123536],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012591034,0.00092463306,0.0008223974,0.00050550164,0.0005021962,0.0013138653,0.0011459548,0.0010905198,0.0015980212],"category_scores_gemma":[0.0021423611,0.0004967575,0.00058148033,0.0005977115,0.00067142525,0.0013798336,0.0008794902,0.0010471008,0.00029732988],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000118127486,0.00012794655,0.0015411137,0.00005348832,0.000021546162,0.00009207836,0.000049891984,0.9712253,0.0020028644,0.0028430643,0.0011463944,0.02077813],"study_design_scores_gemma":[0.000004913061,0.000019906782,0.00018771851,0.0000017758379,0.000004363275,0.00001155286,0.000023300658,0.99853384,0.00019915983,0.0008197652,0.00019017143,0.0000036041968],"about_ca_topic_score_codex":0.005978482,"about_ca_topic_score_gemma":0.0045151627,"teacher_disagreement_score":0.005978482,"about_ca_system_score_codex":0.0009941856,"about_ca_system_score_gemma":0.000983098,"threshold_uncertainty_score":0.011887372},"labels":[],"label_agreement":null},{"id":"W3094751736","doi":"10.1007/978-3-030-62401-9_9","title":"Weighted Group Search on a Line","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Group (periodic table); Line (geometry); Mathematics; Geometry","score_opus":0.03669237838102849,"score_gpt":0.27552589137066497,"score_spread":0.23883351298963648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3094751736","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019755384,0.00048975553,0.9137488,0.00061228964,0.0002853204,0.00010855111,0.00016907495,0.0008288823,0.064001985],"genre_scores_gemma":[0.2381638,0.0005712229,0.6239385,0.0004796421,0.00021328314,0.00040175644,0.0005415409,0.00063449907,0.13505574],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996333,0.00014755793,0.00001072619,0.00006506697,0.00009026231,0.000053164997],"domain_scores_gemma":[0.9996159,0.00016427836,0.00002609559,0.000087950575,0.000061833,0.000043885317],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004900101,0.0007129503,0.0010188378,0.00059156655,0.00061604875,0.0010799319,0.0013671076,0.001173872,0.024428964],"category_scores_gemma":[0.0015162671,0.00033496,0.00060630334,0.0012935201,0.0006125327,0.0017492074,0.0014167859,0.0015139385,0.0048680315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042776734,0.00021956333,0.00032599995,0.00019529875,0.00007164482,0.00014329424,0.00016467604,0.20065652,0.0045601698,0.34080946,0.055304114,0.39712146],"study_design_scores_gemma":[0.000099926874,0.00020488045,0.00014198302,0.000040554165,0.00002244527,0.000088141685,0.00006192907,0.66648114,0.0015292012,0.2953843,0.03592872,0.000016845719],"about_ca_topic_score_codex":0.0009529782,"about_ca_topic_score_gemma":0.0011338822,"teacher_disagreement_score":0.024428964,"about_ca_system_score_codex":0.00054697826,"about_ca_system_score_gemma":0.00048733447,"threshold_uncertainty_score":0.081723034},"labels":[],"label_agreement":null},{"id":"W3096267547","doi":"10.3390/info11110506","title":"A Multi-Objective Optimization Problem on Evacuating 2 Robots from the Disk in the Face-to-Face Model; Trade-Offs between Worst-Case and Average-Case Analysis","year":2020,"lang":"en","type":"article","venue":"Information","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Face (sociological concept); Parameterized complexity; Robot; Mathematical optimization; Trajectory; Algorithm; Artificial intelligence; Mathematics","score_opus":0.04580419657583967,"score_gpt":0.2778586777553245,"score_spread":0.23205448117948485,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3096267547","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024484716,0.00074054085,0.96856725,0.000929074,0.0000936097,0.00015368196,0.00026898252,0.00017973447,0.0045823855],"genre_scores_gemma":[0.5522602,0.0009758025,0.43591622,0.0006129313,0.00024863298,0.00075387856,0.0007149132,0.0003590513,0.008158273],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99722075,0.0012011713,0.000102911916,0.0007116874,0.000386347,0.0003770388],"domain_scores_gemma":[0.99323845,0.0051891822,0.00055398117,0.0003535782,0.00028266027,0.0003821579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0047143204,0.0029019848,0.0034489103,0.00095426425,0.0010409585,0.002492237,0.0035290783,0.0042395657,0.005820895],"category_scores_gemma":[0.011645,0.0010255133,0.0025896342,0.0011234226,0.0018941901,0.0032490827,0.002738037,0.0037136055,0.0006955959],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013415201,0.0000745461,0.00027578892,0.00017986876,0.00006501009,0.00010253668,0.00004845014,0.9753879,0.0004612285,0.013503332,0.0014431402,0.008324149],"study_design_scores_gemma":[0.000017114111,0.00006854732,0.00010671205,0.00002059104,0.00001243584,0.00003655414,0.000027116588,0.98742616,0.00020041528,0.011664518,0.0004076315,0.000012122605],"about_ca_topic_score_codex":0.0044777356,"about_ca_topic_score_gemma":0.0030115184,"teacher_disagreement_score":0.005820895,"about_ca_system_score_codex":0.0020033256,"about_ca_system_score_gemma":0.0017532044,"threshold_uncertainty_score":0.024932027},"labels":[],"label_agreement":null},{"id":"W3104447038","doi":"10.1137/1.9781611975994.131","title":"Instance-Optimality in the Noisy Value-and Comparison-Model","year":2019,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Agence Nationale de la Recherche","keywords":"Pairwise comparison; Computer science; Value (mathematics); Computational complexity theory; Crowdsourcing; Computation; Task (project management); Algorithm; Theoretical computer science; Mathematics; Artificial intelligence; Machine learning","score_opus":0.10814892731091824,"score_gpt":0.2852486066807999,"score_spread":0.17709967936988164,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3104447038","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048103824,0.003685558,0.90969425,0.011243479,0.00045430165,0.00046321735,0.0034225564,0.0013161524,0.021616612],"genre_scores_gemma":[0.62652487,0.003726684,0.335508,0.0038379459,0.0022117975,0.001493746,0.0041206614,0.0013653254,0.021210982],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98407865,0.0071105734,0.00073822006,0.0035037505,0.0029783284,0.0015905504],"domain_scores_gemma":[0.8786063,0.10473764,0.0034623167,0.0078121303,0.0028411457,0.0025404627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01619152,0.0033792888,0.0074821524,0.0021254476,0.0020565386,0.0070641297,0.008167644,0.006231262,0.012915171],"category_scores_gemma":[0.07551485,0.0020243707,0.0038071391,0.004130089,0.005238633,0.0162095,0.006748348,0.011141544,0.002208453],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009804214,0.0003332177,0.0016594847,0.0009763444,0.00027037572,0.0003152604,0.00045225685,0.3835255,0.0008053402,0.55807066,0.020699399,0.031911794],"study_design_scores_gemma":[0.00012603133,0.000097397264,0.00026624266,0.0000603361,0.00003864719,0.00007359627,0.00003843548,0.42605472,0.0003024857,0.5706176,0.00228999,0.00003444283],"about_ca_topic_score_codex":0.0044179107,"about_ca_topic_score_gemma":0.0037348345,"teacher_disagreement_score":0.01619152,"about_ca_system_score_codex":0.006888177,"about_ca_system_score_gemma":0.004812328,"threshold_uncertainty_score":0.08563},"labels":[],"label_agreement":null},{"id":"W3107537640","doi":"10.1145/3392142","title":"Mechanism Design for Online Resource Allocation","year":2020,"lang":"en","type":"article","venue":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Knapsack problem; Competitive analysis; Computer science; Valuation (finance); Payment; Incentive compatibility; Mechanism design; Resource allocation; Incentive; Function (biology); Resource (disambiguation); Allocative efficiency; Mathematical optimization; Operations research; Microeconomics; Business; Economics; Mathematics","score_opus":0.10921570948108951,"score_gpt":0.2737351367538308,"score_spread":0.16451942727274133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107537640","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032172913,0.0009849321,0.98798776,0.00052469247,0.000117760916,0.0002396723,0.00008540743,0.00021995329,0.006622533],"genre_scores_gemma":[0.48601192,0.0030380778,0.49545106,0.0010475197,0.0005379821,0.002419777,0.0003261855,0.00018323027,0.010984118],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.988536,0.006959621,0.0005561474,0.0014838993,0.0016399567,0.000824442],"domain_scores_gemma":[0.9873668,0.009246275,0.0010735107,0.0011884567,0.0007650314,0.0003599746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0110606225,0.0021642188,0.0029451908,0.0014486208,0.0010945972,0.0044569084,0.0047058635,0.0037666287,0.008476414],"category_scores_gemma":[0.02009818,0.001396804,0.0019235617,0.002651615,0.0027014986,0.0065224404,0.0029903813,0.0040495736,0.0015196444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001651973,0.00022091529,0.00026210598,0.00067649607,0.00017133121,0.00018115435,0.00013090296,0.252552,0.0017248132,0.69286555,0.0043992824,0.046650194],"study_design_scores_gemma":[0.00015766594,0.00015462039,0.000077792145,0.00008087506,0.000057024783,0.00016860184,0.00003925151,0.6014552,0.0008481334,0.3876946,0.00922719,0.000039048326],"about_ca_topic_score_codex":0.0009894331,"about_ca_topic_score_gemma":0.00081604614,"teacher_disagreement_score":0.0110606225,"about_ca_system_score_codex":0.0031405615,"about_ca_system_score_gemma":0.003717586,"threshold_uncertainty_score":0.058494866},"labels":[],"label_agreement":null},{"id":"W3108030130","doi":"10.1016/j.disc.2022.112883","title":"Broadcasting on paths and cycles","year":2022,"lang":"en","type":"article","venue":"Discrete Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Broadcasting (networking); Mathematics; Combinatorics; Graph; Discrete mathematics; Computer science; Computer network","score_opus":0.028254784988091426,"score_gpt":0.2694434600879379,"score_spread":0.24118867509984648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3108030130","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33782664,0.009123698,0.41683054,0.010009304,0.000610999,0.00027136496,0.0014498451,0.00057806284,0.22329949],"genre_scores_gemma":[0.81680286,0.00881412,0.06774765,0.0011069018,0.0007073616,0.00039947528,0.0009144909,0.00044113214,0.10306598],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99927264,0.00026954152,0.000025205207,0.0001362665,0.00014465555,0.00015166425],"domain_scores_gemma":[0.99414897,0.004331981,0.0004220648,0.00036269653,0.00034023385,0.00039406924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077553437,0.0007488785,0.0013339556,0.0019063232,0.0017181655,0.002949002,0.0014991916,0.0018607324,0.014430508],"category_scores_gemma":[0.011145601,0.00074610894,0.00075528864,0.0035952611,0.0026910538,0.005076026,0.0023861092,0.00269963,0.00088947086],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006248061,0.000016418606,0.00013985047,0.00006797047,0.000011036942,0.000042679163,0.00015971942,0.012790697,0.00028181708,0.9714786,0.0037944017,0.011154319],"study_design_scores_gemma":[0.00001802395,0.000010547491,0.00007272343,0.00001971089,0.000008798851,0.000032584318,0.000050675444,0.018991338,0.000117999014,0.97613186,0.004540127,0.0000054483257],"about_ca_topic_score_codex":0.006656863,"about_ca_topic_score_gemma":0.004321726,"teacher_disagreement_score":0.014430508,"about_ca_system_score_codex":0.0027657633,"about_ca_system_score_gemma":0.0014713536,"threshold_uncertainty_score":0.048274815},"labels":[],"label_agreement":null},{"id":"W3109677567","doi":"10.1609/aaai.v35i13.17394","title":"Contract Scheduling With Predictions","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Fondation Mathématique Jacques Hadamard","keywords":"Computer science; Adversarial system; Robustness (evolution); Scheduling (production processes); Binary number; Consistency (knowledge bases); Mathematical optimization; Operations research; Artificial intelligence; Mathematics","score_opus":0.07369333998191974,"score_gpt":0.2945374869621534,"score_spread":0.2208441469802337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3109677567","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047584917,0.00045213272,0.94384253,0.00069704803,0.00020701547,0.00019064339,0.0002605657,0.0011493524,0.0056157773],"genre_scores_gemma":[0.86836576,0.00032018204,0.12616415,0.00021908148,0.00021109547,0.00015829511,0.00031894076,0.0002372591,0.004005199],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9949733,0.0016862721,0.0003089259,0.00086459774,0.0015339674,0.0006328708],"domain_scores_gemma":[0.97852874,0.011947664,0.0020448691,0.0049537914,0.0015966531,0.00092822756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0076667266,0.0010799267,0.0013187539,0.00052653305,0.0010057258,0.0021479474,0.0022092904,0.0011424168,0.0038279973],"category_scores_gemma":[0.031070134,0.00060764083,0.0006533219,0.0008697771,0.0024497092,0.00374985,0.0023440744,0.002515332,0.00076450687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010751386,0.00013979756,0.0022707132,0.00021156264,0.00006794016,0.00030799623,0.00036421558,0.73361427,0.005405271,0.19155475,0.0049216677,0.06006661],"study_design_scores_gemma":[0.000045510802,0.00008886498,0.000158118,0.00001529535,0.00001275981,0.00005477455,0.00002853806,0.9346783,0.0022952373,0.060216025,0.002387785,0.000018696895],"about_ca_topic_score_codex":0.0028545652,"about_ca_topic_score_gemma":0.0018512319,"teacher_disagreement_score":0.0076667266,"about_ca_system_score_codex":0.0017538263,"about_ca_system_score_gemma":0.0035560927,"threshold_uncertainty_score":0.040546},"labels":[],"label_agreement":null},{"id":"W3111473535","doi":"10.1109/blockchain50366.2020.00060","title":"Candidate Set Formation Policy for Mining Pools","year":2020,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"University of Manitoba","keywords":"Computer science; Set (abstract data type); Programming language","score_opus":0.06289138441228816,"score_gpt":0.31615016725465583,"score_spread":0.2532587828423677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3111473535","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.089718096,0.0009991925,0.8725979,0.00375774,0.00026018702,0.0011653187,0.001892919,0.0018752074,0.027733453],"genre_scores_gemma":[0.71930087,0.000634626,0.25562164,0.00043762557,0.00018803446,0.00095224864,0.0021291669,0.00028304275,0.020452755],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99412704,0.002226819,0.00046922767,0.0011574278,0.001304622,0.000714877],"domain_scores_gemma":[0.984018,0.008669376,0.0013633927,0.0027936157,0.0016303721,0.001525133],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0066786516,0.0009395034,0.001744393,0.0019883798,0.0027748724,0.003785168,0.0039056707,0.0022628608,0.017113151],"category_scores_gemma":[0.023837447,0.00068686035,0.0013751012,0.0025540264,0.0016507014,0.006896408,0.003531969,0.0019974979,0.002722703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019157932,0.0005781298,0.004433527,0.0005696128,0.00015298942,0.0008276669,0.000999755,0.23676312,0.0043238024,0.5628103,0.023282433,0.16334292],"study_design_scores_gemma":[0.00019771798,0.0003953221,0.00052337593,0.00010887766,0.00005439522,0.0004851611,0.00028614092,0.7506033,0.0055679483,0.21607701,0.025635539,0.00006522684],"about_ca_topic_score_codex":0.0018397402,"about_ca_topic_score_gemma":0.0020953454,"teacher_disagreement_score":0.017113151,"about_ca_system_score_codex":0.0022721707,"about_ca_system_score_gemma":0.0047769607,"threshold_uncertainty_score":0.05724919},"labels":[],"label_agreement":null},{"id":"W3114470063","doi":"10.1109/latincom50620.2020.9282342","title":"A Low-Complexity Multi-Survivor Dynamic Programming for Constrained Discrete Optimization","year":2020,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"National Instruments Corporation","keywords":"Markov decision process; Dynamic programming; Generalization; Constrained optimization; Optimization problem; Discrete optimization; Markov chain; Stochastic programming; Function (biology)","score_opus":0.0636745229684185,"score_gpt":0.3104675232800502,"score_spread":0.24679300031163168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3114470063","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034121054,0.00013073483,0.993598,0.00019493759,0.000025668589,0.00004180971,0.000047014917,0.00012268136,0.0024271253],"genre_scores_gemma":[0.38537693,0.00044906512,0.60623807,0.00026845402,0.00007935176,0.0005555491,0.0002650843,0.00015032061,0.0066171642],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999509,0.00017292195,0.00001976497,0.000103880935,0.00013978643,0.000054719174],"domain_scores_gemma":[0.99920696,0.0005748135,0.00005678283,0.00004229544,0.00007559186,0.000043546082],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008214031,0.0010399494,0.0010716154,0.00043549231,0.000491392,0.0008273192,0.0009923266,0.001209312,0.0044475244],"category_scores_gemma":[0.002451522,0.00048204223,0.0006343691,0.00076071225,0.0010057143,0.0009932196,0.0015251145,0.002157498,0.0004540406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035129946,0.000036638252,0.00015163093,0.000074280215,0.00001772594,0.000059164617,0.000030478172,0.9316091,0.0009983183,0.04048921,0.0012255898,0.025272675],"study_design_scores_gemma":[0.000006138581,0.0000138455025,0.00001572448,0.000003659573,0.0000014553734,0.000007095762,0.0000031668244,0.99092203,0.00013948434,0.008408,0.0004767451,0.0000026506787],"about_ca_topic_score_codex":0.0038583607,"about_ca_topic_score_gemma":0.004413018,"teacher_disagreement_score":0.0044475244,"about_ca_system_score_codex":0.0010172728,"about_ca_system_score_gemma":0.0016428205,"threshold_uncertainty_score":0.014878452},"labels":[],"label_agreement":null},{"id":"W3116777151","doi":"10.4230/lipics.isaac.2020.10","title":"Approximation Algorithms for Generalized Path Scheduling","year":2020,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Job shop scheduling; Scheduling (production processes); Queue; Path (computing); Algorithm; Computer science; Flow shop scheduling; Longest path problem; Mathematics; Mathematical optimization; Theoretical computer science; Shortest path problem; Graph","score_opus":0.050347934490476275,"score_gpt":0.2875827974597208,"score_spread":0.23723486296924454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3116777151","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015907431,0.0027005067,0.9633543,0.0010436213,0.00034007998,0.00018929783,0.00067780074,0.0015145111,0.014272498],"genre_scores_gemma":[0.33625042,0.0031559241,0.64154786,0.00071306026,0.00040686782,0.0007424167,0.0034636508,0.0007436355,0.012976223],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985936,0.0005403475,0.000051236144,0.00027265903,0.00029931116,0.00024292669],"domain_scores_gemma":[0.9972844,0.0018018625,0.00021210202,0.00034265485,0.00022629643,0.00013278247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018077183,0.0021231761,0.0017964989,0.0014711379,0.0009853528,0.002195462,0.002773858,0.0020471623,0.012997838],"category_scores_gemma":[0.007994058,0.00073271873,0.0013860798,0.0028179341,0.0010611968,0.0036155821,0.0018403683,0.0029359735,0.0018021538],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022571231,0.00011212735,0.0004800267,0.00024782083,0.00009276555,0.000068347035,0.00008374238,0.83110756,0.00041049524,0.07494585,0.015543847,0.07668158],"study_design_scores_gemma":[0.000047883703,0.00003532161,0.000071264694,0.000021995465,0.000012231724,0.000027259175,0.000025528816,0.92834646,0.00008291453,0.06851688,0.0028065462,0.0000057974516],"about_ca_topic_score_codex":0.008295065,"about_ca_topic_score_gemma":0.007903429,"teacher_disagreement_score":0.012997838,"about_ca_system_score_codex":0.0032944775,"about_ca_system_score_gemma":0.0028444051,"threshold_uncertainty_score":0.043482065},"labels":[],"label_agreement":null},{"id":"W3118763906","doi":"10.1007/s00453-020-00792-6","title":"Approximating the Canadian Traveller Problem with Online Randomization","year":2021,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Ministry of Science and Technology, Taiwan","keywords":"Competitive analysis; Theory of computation; Randomized algorithm; Combinatorics; Online algorithm; Deterministic algorithm; Bounded function; Time complexity; Vertex (graph theory); Upper and lower bounds; Approximation algorithm; Mathematics; Computer science; Discrete mathematics; Algorithm; Graph","score_opus":0.012957880170396573,"score_gpt":0.22003555062602606,"score_spread":0.2070776704556295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3118763906","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12031287,0.0024504284,0.81432813,0.0050456226,0.00065536296,0.0005481765,0.0021002474,0.0027834428,0.051775746],"genre_scores_gemma":[0.70508516,0.0009812929,0.262534,0.00084264745,0.00031484762,0.00055335346,0.0024360036,0.0008269673,0.026425742],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99782604,0.00085601147,0.000057023604,0.0004340666,0.0003733903,0.0004535135],"domain_scores_gemma":[0.9925891,0.005174272,0.00032586546,0.0008972756,0.0005249894,0.00048840116],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026661162,0.0017095471,0.0026105584,0.0017111095,0.0019340364,0.0028116785,0.0045682513,0.0035259689,0.01739021],"category_scores_gemma":[0.01887834,0.00091022387,0.0013212828,0.0031671755,0.0025695271,0.005215586,0.0026403556,0.0039633787,0.001632701],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00078115653,0.00035400418,0.0012515411,0.00022365616,0.00007739057,0.00008419956,0.0000945161,0.7531452,0.0005260185,0.15382354,0.036548123,0.05309061],"study_design_scores_gemma":[0.00012055696,0.00004402968,0.00016009799,0.000018031753,0.00001664812,0.000020864441,0.000033236487,0.9289927,0.00020511147,0.0683222,0.002049305,0.000017201226],"about_ca_topic_score_codex":0.08314238,"about_ca_topic_score_gemma":0.09142665,"teacher_disagreement_score":0.9168576,"about_ca_system_score_codex":0.006810421,"about_ca_system_score_gemma":0.011405353,"threshold_uncertainty_score":0.16531688},"labels":[],"label_agreement":null},{"id":"W3119859168","doi":"10.3390/info12010028","title":"Robot Evacuation on a Line Assisted by a Bike","year":2021,"lang":"en","type":"article","venue":"Information","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Sciences and Engineering Research Council of Canada; Carleton University","funders":"","keywords":"Robot; Mobile robot; Computer science; Line (geometry); Simulation; Wireless; Face (sociological concept); Constant (computer programming); Artificial intelligence; Mathematics; Telecommunications","score_opus":0.03134581304665471,"score_gpt":0.2795205945949723,"score_spread":0.2481747815483176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3119859168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41538432,0.00022761455,0.56802046,0.00048778605,0.00012301776,0.000167003,0.00013660906,0.001973276,0.01347997],"genre_scores_gemma":[0.89473647,0.0000856572,0.09470026,0.00006621627,0.0000144804535,0.0001308051,0.00021769863,0.000051915784,0.009996428],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975866,0.000056988105,0.000014917944,0.00005613932,0.000036014684,0.000077353325],"domain_scores_gemma":[0.9995907,0.00013053452,0.00005381536,0.00007096301,0.00005557821,0.00009840304],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00030105404,0.0008358685,0.0008476809,0.00041534172,0.00097650615,0.00063741533,0.001199733,0.0013702511,0.0042729527],"category_scores_gemma":[0.0009475012,0.00030735251,0.00050316023,0.00028661024,0.00059869303,0.0010009963,0.0023171932,0.00091211,0.000903022],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014554892,0.00028464568,0.0026131931,0.000225773,0.00007593096,0.0010028577,0.0006054576,0.8991849,0.020060109,0.01031966,0.002242088,0.061929926],"study_design_scores_gemma":[0.000046254652,0.0002616334,0.00044117664,0.000014357651,0.000013098524,0.00013565172,0.00017431169,0.9905884,0.0038129115,0.0021856425,0.002302183,0.000024332752],"about_ca_topic_score_codex":0.002867929,"about_ca_topic_score_gemma":0.0030419189,"teacher_disagreement_score":0.0042729527,"about_ca_system_score_codex":0.0003711766,"about_ca_system_score_gemma":0.0005351076,"threshold_uncertainty_score":0.014294505},"labels":[],"label_agreement":null},{"id":"W3122384578","doi":"10.1287/opre.1080.0654","title":"Toward Robust Revenue Management: Competitive Analysis of Online Booking","year":2009,"lang":"en","type":"article","venue":"Operations Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":160,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"National Science Foundation","keywords":"Competitive analysis; Revenue; Online algorithm; Revenue management; Computer science; Operations research; Upper and lower bounds; Perspective (graphical); Sequence (biology); Control (management); Mathematical optimization; Business; Microeconomics; Economics; Algorithm; Mathematics; Finance; Artificial intelligence","score_opus":0.12677905652401197,"score_gpt":0.3956695854522347,"score_spread":0.26889052892822274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122384578","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021978209,0.001373644,0.9534076,0.00082255783,0.0000926872,0.00012941644,0.00011241804,0.0001993666,0.021884143],"genre_scores_gemma":[0.8911858,0.0016747629,0.09664911,0.00034724656,0.0004962802,0.00029204023,0.00018188666,0.00032612053,0.008846688],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955101,0.0020358653,0.00010687373,0.0005303594,0.0012042639,0.00061242393],"domain_scores_gemma":[0.98762894,0.008281093,0.0015375782,0.0007400078,0.001256016,0.0005563291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0064266715,0.002140471,0.002312985,0.0018524668,0.001039006,0.004029868,0.003718773,0.001987465,0.007360813],"category_scores_gemma":[0.02453666,0.00089304004,0.0012817426,0.0016506355,0.003125545,0.0070966906,0.0025473877,0.0036719108,0.0008741057],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009857709,0.00014340761,0.000407767,0.00016022965,0.000053041094,0.00008543862,0.00009129864,0.578777,0.0010063488,0.39510286,0.0025277922,0.02154616],"study_design_scores_gemma":[0.000008191227,0.00003382368,0.000086135384,0.000014455939,0.0000072329044,0.000017145714,0.000018169374,0.9229424,0.00024247603,0.0759251,0.00069356227,0.000011306156],"about_ca_topic_score_codex":0.0033306757,"about_ca_topic_score_gemma":0.0013968094,"teacher_disagreement_score":0.007360813,"about_ca_system_score_codex":0.0043640747,"about_ca_system_score_gemma":0.0020469003,"threshold_uncertainty_score":0.03398794},"labels":[],"label_agreement":null},{"id":"W3122751602","doi":"10.22215/etd/2015-10855","title":"Experimental Evaluation of Reordering Buffer Management Algorithms","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Sequence (biology); Buffer (optical fiber); Computer science; Algorithm; Telecommunications","score_opus":0.07176271399182672,"score_gpt":0.3845007939356672,"score_spread":0.3127380799438405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122751602","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.842363,0.009753072,0.08997927,0.0013927448,0.0016762718,0.0014698195,0.0049146684,0.013456812,0.034994327],"genre_scores_gemma":[0.8209973,0.001667937,0.1586978,0.00038976205,0.00020010282,0.00057714555,0.008390146,0.0010199411,0.008059807],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9961033,0.0012049923,0.0004580855,0.0008256276,0.001012262,0.00039574946],"domain_scores_gemma":[0.9790643,0.012926402,0.0009275504,0.003073071,0.003449431,0.00055923645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004432797,0.0018260004,0.0011769762,0.0014496061,0.00096228404,0.001421118,0.003135621,0.0016693479,0.008094523],"category_scores_gemma":[0.024432436,0.0004520398,0.0005285461,0.001982583,0.0007837595,0.0027009181,0.0010397047,0.0013432667,0.002351213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.011870354,0.008777092,0.0060729077,0.003147592,0.0005816663,0.00031304866,0.00033706406,0.39305836,0.03191412,0.007791795,0.042093404,0.49404263],"study_design_scores_gemma":[0.0012337115,0.003724568,0.0033818176,0.00013950597,0.00019176035,0.0001993956,0.0003607348,0.9370993,0.037378393,0.0046503036,0.011569941,0.000070666036],"about_ca_topic_score_codex":0.0066773174,"about_ca_topic_score_gemma":0.0065604323,"teacher_disagreement_score":0.008094523,"about_ca_system_score_codex":0.0018197984,"about_ca_system_score_gemma":0.0016411266,"threshold_uncertainty_score":0.027078867},"labels":[],"label_agreement":null},{"id":"W3122929977","doi":"","title":"A Tree-Structured Markovian Model of the Shipment Consolidation Process","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Markov process; Consolidation (business); Markov chain; Computer science; Mathematical optimization; Markov decision process; Markovian arrival process; Operations research; Heuristic; Economic dispatch; Engineering; Mathematics; Economics; Finance; Statistics","score_opus":0.011763078768868151,"score_gpt":0.2434368522337196,"score_spread":0.23167377346485146,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3122929977","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07568513,0.00063564884,0.9111101,0.0008222229,0.00009477658,0.00009626709,0.0007499452,0.0002763758,0.010529432],"genre_scores_gemma":[0.91719353,0.0013302753,0.0651241,0.00015292614,0.00012028348,0.00023201217,0.0007553875,0.000048365524,0.015043004],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933004,0.00023113473,0.000026140451,0.00014305023,0.00012221203,0.00014747928],"domain_scores_gemma":[0.9983359,0.00104946,0.00023697416,0.00007241309,0.0001803432,0.00012494606],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013256238,0.00073889835,0.0012007401,0.0007972262,0.00061893486,0.0017290324,0.002025076,0.0016796163,0.006027186],"category_scores_gemma":[0.0034620513,0.0005829478,0.00081538846,0.0017895262,0.0012768162,0.002128107,0.00067369465,0.0015705401,0.0008456962],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000055605782,0.000035553538,0.0004299749,0.000038646253,0.000016504044,0.0001487404,0.000048004626,0.9165004,0.00062598457,0.07828503,0.00063386624,0.0031817586],"study_design_scores_gemma":[0.000012964702,0.000014120978,0.000084423256,0.0000035794592,0.0000058156124,0.000016608285,0.0000070933206,0.9865441,0.000063100764,0.012932158,0.00031004474,0.000005995695],"about_ca_topic_score_codex":0.016712192,"about_ca_topic_score_gemma":0.011514893,"teacher_disagreement_score":0.016712192,"about_ca_system_score_codex":0.0017563307,"about_ca_system_score_gemma":0.002106018,"threshold_uncertainty_score":0.033229828},"labels":[],"label_agreement":null},{"id":"W3129885107","doi":"10.1287/moor.2020.1083","title":"Strong algorithms for the ordinal matroid secretary problem","year":2021,"lang":"en","type":"article","venue":"Universidad de Chile","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Matroid; Secretary problem; Mathematics; Combinatorics; Rank (graph theory); Order (exchange); Discrete mathematics; Measure (data warehouse); Probability distribution; Algorithm; Computer science; Mathematical optimization; Data mining; Statistics; Optimal stopping","score_opus":0.02142803827901939,"score_gpt":0.26596309494726605,"score_spread":0.24453505666824665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129885107","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02569226,0.00026076176,0.9632815,0.0008389267,0.00005567744,0.00015464201,0.00014148277,0.0007689956,0.008805721],"genre_scores_gemma":[0.377336,0.00040017112,0.6122216,0.00046362684,0.00020144849,0.0006254209,0.00061805465,0.0004056978,0.007727965],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99510986,0.0018269256,0.0003007333,0.00090004253,0.0012894905,0.00057292084],"domain_scores_gemma":[0.98778963,0.0075698933,0.00086896465,0.002060313,0.001052177,0.0006590484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043675005,0.0010478486,0.0011687591,0.0010713041,0.0013457597,0.0036543438,0.0036409912,0.0018678309,0.006645751],"category_scores_gemma":[0.021568995,0.0008053608,0.0015039931,0.0020928471,0.001831334,0.005924202,0.004756592,0.0037410941,0.0014030902],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004981443,0.00042885958,0.001542984,0.000423309,0.00010138827,0.00009532026,0.0005024591,0.15343787,0.0044898945,0.66283584,0.009943219,0.16570073],"study_design_scores_gemma":[0.00013257786,0.00017497591,0.00026948843,0.000034585133,0.00003508711,0.00013359614,0.00010165057,0.5634748,0.0031360653,0.4254207,0.0070553133,0.000031230316],"about_ca_topic_score_codex":0.0010454501,"about_ca_topic_score_gemma":0.0016447776,"teacher_disagreement_score":0.006645751,"about_ca_system_score_codex":0.0024678549,"about_ca_system_score_gemma":0.0029778655,"threshold_uncertainty_score":0.023097813},"labels":[],"label_agreement":null},{"id":"W3129941803","doi":"","title":"Building a Nest by an Automaton.","year":2019,"lang":"en","type":"article","venue":"European Symposium on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Robot; Grid; Brick; Computer science; Span (engineering); Cellular automaton; Automaton; Carry (investment); Regular grid; Algorithm; Time complexity; Task (project management); Theoretical computer science; Mathematics; Geometry; Engineering; Structural engineering; Artificial intelligence","score_opus":0.011336105694697935,"score_gpt":0.2506736587131816,"score_spread":0.23933755301848367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3129941803","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024938233,0.00022973523,0.9655126,0.00023468453,0.000045083023,0.00010504833,0.00022519467,0.0013439264,0.0073654717],"genre_scores_gemma":[0.31257403,0.00038822132,0.67882586,0.00015968944,0.0000300818,0.00045730436,0.00084060145,0.00023131869,0.006492961],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993253,0.0001701119,0.000058754464,0.0002115656,0.00014616866,0.00008818677],"domain_scores_gemma":[0.99890614,0.0005884043,0.00010251692,0.00025826856,0.00008502348,0.000059620783],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004763624,0.00070590293,0.00055609713,0.00034311987,0.0007403652,0.0010470534,0.0012407629,0.0011234097,0.005188216],"category_scores_gemma":[0.002605695,0.0006134073,0.0018525012,0.00038692117,0.0013558775,0.0016148392,0.0018125509,0.000929656,0.0012369066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029594736,0.00015502253,0.002776807,0.00059841166,0.0001287972,0.00042206416,0.00049336517,0.702731,0.015180098,0.20053996,0.0037985016,0.07288011],"study_design_scores_gemma":[0.00006274139,0.0001461909,0.00023690301,0.00006192988,0.00006594426,0.00018969727,0.00008145048,0.8753477,0.004982502,0.10616121,0.012637949,0.000025820054],"about_ca_topic_score_codex":0.0028805332,"about_ca_topic_score_gemma":0.0042819967,"teacher_disagreement_score":0.005188216,"about_ca_system_score_codex":0.00074012927,"about_ca_system_score_gemma":0.0012127756,"threshold_uncertainty_score":0.017356336},"labels":[],"label_agreement":null},{"id":"W3133770809","doi":"10.1016/j.dam.2021.02.026","title":"Cops and an Insightful Robber","year":2021,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Mathematics; Upper and lower bounds; Graph; Hypercube; Combinatorics; Simple (philosophy); Computer science; Discrete mathematics; Theoretical computer science; Artificial intelligence","score_opus":0.02153216830304185,"score_gpt":0.2727909043294377,"score_spread":0.25125873602639587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3133770809","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023137376,0.0058685686,0.5837284,0.05785041,0.007968795,0.00010750688,0.00072613155,0.0012209023,0.31939194],"genre_scores_gemma":[0.51927036,0.0042275153,0.2287186,0.010787271,0.005584984,0.0003405022,0.00058775546,0.0013202674,0.22916275],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99902534,0.00037093056,0.000039042923,0.0002005135,0.00027322888,0.00009099333],"domain_scores_gemma":[0.9985696,0.0006577444,0.00006742208,0.0003664167,0.00022009178,0.00011875213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010077654,0.0011163906,0.0010480713,0.0011109568,0.002216163,0.0028113227,0.0014011827,0.0023779597,0.023489604],"category_scores_gemma":[0.007840926,0.00053206977,0.00088919466,0.0007249643,0.0044911555,0.007709529,0.003626553,0.00435125,0.003933178],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024856756,0.000010658802,0.00005852912,0.000050567494,0.000009611479,0.0000636123,0.00011008833,0.002563517,0.0001657453,0.9721306,0.016778225,0.008033906],"study_design_scores_gemma":[0.000009486528,0.00001055696,0.000048604084,0.00002945848,0.0000060611496,0.000067392175,0.00005059156,0.012393948,0.00013994846,0.9555871,0.03164592,0.000010866136],"about_ca_topic_score_codex":0.0015016455,"about_ca_topic_score_gemma":0.0012798754,"teacher_disagreement_score":0.023489604,"about_ca_system_score_codex":0.0008267932,"about_ca_system_score_gemma":0.0007981004,"threshold_uncertainty_score":0.0785805},"labels":[],"label_agreement":null},{"id":"W3134754278","doi":"10.23952/asvao.3.2021.3.08","title":"On the approximation error for approximating convex bodies using multiobjective optimization","year":2021,"lang":"en","type":"article","venue":"Applied Set-Valued Analysis and Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Regular polygon; Mathematical optimization; Approximation error; Mathematics; Multi-objective optimization; Convex optimization; Applied mathematics; Computer science; Geometry","score_opus":0.03939735449479389,"score_gpt":0.28807096581468744,"score_spread":0.24867361131989354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3134754278","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008979257,0.000730889,0.9882825,0.00025248827,0.000052809617,0.000029929146,0.000021210619,0.00007822483,0.0015726958],"genre_scores_gemma":[0.3793817,0.0016750528,0.61318946,0.0002717982,0.00012580845,0.00038781713,0.00024204234,0.00042963485,0.004296795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99668473,0.0016198312,0.00014042683,0.00032178953,0.0010606226,0.00017253615],"domain_scores_gemma":[0.9813829,0.015391707,0.0007713716,0.00067860546,0.0014802088,0.00029535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010224026,0.0017920629,0.0021071325,0.0018383197,0.00070712157,0.0023079794,0.001613788,0.002482345,0.0015586102],"category_scores_gemma":[0.031215133,0.0007711675,0.0013253235,0.0012143534,0.0029100426,0.0023412404,0.0031566054,0.0034139631,0.00037078263],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008266214,0.000028329661,0.00050792843,0.00011836459,0.000044824785,0.000039340845,0.000079965765,0.94997406,0.0009586992,0.032717828,0.00040725424,0.015040707],"study_design_scores_gemma":[0.0000023594393,0.0000144967735,0.000051862935,0.000022919352,0.00000342393,0.0000073806455,0.0000065492177,0.99365544,0.0003089554,0.005724871,0.00019774427,0.000004005981],"about_ca_topic_score_codex":0.00423036,"about_ca_topic_score_gemma":0.0023278343,"teacher_disagreement_score":0.010224026,"about_ca_system_score_codex":0.0027381605,"about_ca_system_score_gemma":0.0014121023,"threshold_uncertainty_score":0.054070473},"labels":[],"label_agreement":null},{"id":"W3135232827","doi":"10.48550/arxiv.2006.15379","title":"Cops and an Insightful Robber","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Computer science; Graph; Upper and lower bounds; Hypercube; Combinatorics; Simple (philosophy); Cheating; Mathematics; Discrete mathematics; Artificial intelligence","score_opus":0.13031457915011926,"score_gpt":0.20651221055519775,"score_spread":0.07619763140507849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3135232827","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.338793,0.0019186833,0.49840817,0.008653591,0.00057090994,0.00019605238,0.0005577992,0.0014800363,0.14942184],"genre_scores_gemma":[0.8889736,0.0005264846,0.078658365,0.0007610086,0.00012453645,0.00012989694,0.00034225438,0.0002536336,0.030230349],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991418,0.00030946816,0.000029928404,0.00017049008,0.00018121922,0.00016717178],"domain_scores_gemma":[0.99743783,0.0014232292,0.0002484563,0.00048941496,0.00016474996,0.00023624359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009229049,0.0008353104,0.00071943155,0.00058794016,0.001149173,0.0016361674,0.0010537313,0.0013231289,0.01441395],"category_scores_gemma":[0.0074300007,0.00042025602,0.0006403121,0.00049544836,0.002286317,0.0035884618,0.0024141704,0.0018818777,0.0014757055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036554993,0.00009845946,0.0013383111,0.00021433982,0.000061924795,0.00039366866,0.00049060484,0.049464528,0.0038743159,0.89350146,0.015621166,0.03457565],"study_design_scores_gemma":[0.00007255606,0.00016885033,0.0009387725,0.00006709174,0.000038467886,0.00036912924,0.0003063066,0.21381305,0.0024944078,0.7551009,0.02658986,0.000040524927],"about_ca_topic_score_codex":0.0015035571,"about_ca_topic_score_gemma":0.0012173199,"teacher_disagreement_score":0.01441395,"about_ca_system_score_codex":0.0009381616,"about_ca_system_score_gemma":0.0005663691,"threshold_uncertainty_score":0.048219502},"labels":[],"label_agreement":null},{"id":"W3142890281","doi":"","title":"Taiwan's national memory","year":2009,"lang":"en","type":"article","venue":"IEEE Spectrum","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Upgrade; Dram; Slumping; Government (linguistics); Business; Commerce; Operations management; Finance; Engineering; Computer science; Operating system; Computer hardware; Geography","score_opus":0.017967292752318564,"score_gpt":0.2663864582046756,"score_spread":0.24841916545235704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3142890281","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11321482,0.019868832,0.012845614,0.05327577,0.0023406232,0.00010858041,0.0024935857,0.00097357814,0.79487866],"genre_scores_gemma":[0.56239796,0.007506144,0.006078588,0.004384705,0.00043720606,0.00012006943,0.003092355,0.00010702125,0.4158759],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99986017,0.000014615286,0.0000062392573,0.000026459515,0.00004658258,0.00004588716],"domain_scores_gemma":[0.9997385,0.000023666737,0.000019190818,0.000044587578,0.00010111892,0.00007295633],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003165184,0.00024800087,0.00016210468,0.00045143004,0.0009103795,0.0018856765,0.0004463241,0.0006792422,0.027850568],"category_scores_gemma":[0.0008080093,0.00007279468,0.00013820571,0.0008108489,0.0002630316,0.0013805565,0.0011244987,0.0006163806,0.0041036885],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015499756,0.000044604993,0.004464741,0.0002565915,0.000021207476,0.00065563066,0.00049827475,0.0030938229,0.0030967393,0.09992444,0.430694,0.45709488],"study_design_scores_gemma":[0.000029178706,0.0000794532,0.0057107536,0.00016160434,0.000030984655,0.0005918761,0.0010063044,0.012559981,0.002872162,0.029428462,0.94749874,0.000030568408],"about_ca_topic_score_codex":0.015801512,"about_ca_topic_score_gemma":0.026027497,"teacher_disagreement_score":0.027850568,"about_ca_system_score_codex":0.0015253092,"about_ca_system_score_gemma":0.0041664876,"threshold_uncertainty_score":0.09316945},"labels":[],"label_agreement":null},{"id":"W3144562320","doi":"10.5555/1165139.1165141","title":"A multi-agent architecture for robotic systems in real-time environments","year":2006,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Computer science; Architecture; Distributed computing; Multi-agent system; Agent architecture; Computer architecture; Embedded system; Real-time computing; Artificial intelligence","score_opus":0.015702238508529694,"score_gpt":0.2646063850324099,"score_spread":0.2489041465238802,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3144562320","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031069363,0.0005316581,0.99193877,0.0004900929,0.00008265492,0.00005750851,0.000011085875,0.0003241931,0.0034569914],"genre_scores_gemma":[0.16096133,0.0011379357,0.8297899,0.00022890547,0.00009045261,0.00024695622,0.00006122712,0.00006942409,0.007413946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996381,0.00011521826,0.000024828529,0.00006617317,0.00012577418,0.000030038711],"domain_scores_gemma":[0.9997173,0.000070252136,0.00003987761,0.000050107825,0.00007337022,0.00004904502],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065789913,0.0005405729,0.0003316452,0.00028661787,0.00074951863,0.0013752347,0.0012010044,0.0010932502,0.0025875045],"category_scores_gemma":[0.00094714825,0.00034907353,0.00045857267,0.00033608402,0.0010072178,0.0018252408,0.0010483544,0.0016233703,0.0009146716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001282284,0.00015274828,0.00048879074,0.00048957823,0.000100037105,0.00045280808,0.0005827797,0.34770986,0.02890452,0.45897314,0.0059090075,0.15610853],"study_design_scores_gemma":[0.000049243863,0.00021747168,0.00025670652,0.00008103979,0.000052360865,0.00022902127,0.00010930971,0.8082309,0.0074139284,0.12178908,0.061532255,0.000038696286],"about_ca_topic_score_codex":0.0013658323,"about_ca_topic_score_gemma":0.0023033032,"teacher_disagreement_score":0.0025875045,"about_ca_system_score_codex":0.0005099159,"about_ca_system_score_gemma":0.0008520883,"threshold_uncertainty_score":0.008656025},"labels":[],"label_agreement":null},{"id":"W3148455537","doi":"10.48550/arxiv.2011.02046","title":"Beyond Worst-case Analysis of Multicore Caching Strategies","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Multi-core processor; Cache; Core (optical fiber); Locality; Locality of reference; Flexibility (engineering); Generalization; Cache algorithms; Parallel computing; Online algorithm; Algorithm; Class (philosophy); CPU cache; Artificial intelligence; Mathematics","score_opus":0.10842854413340616,"score_gpt":0.22292266206711156,"score_spread":0.1144941179337054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3148455537","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10405488,0.0024425525,0.8657777,0.002222848,0.00014814002,0.00027185763,0.0003592923,0.00048767496,0.024235055],"genre_scores_gemma":[0.9155956,0.0013231217,0.075644314,0.0009200748,0.00036046596,0.00039534035,0.0003569275,0.00032735805,0.005076813],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9894225,0.0037836074,0.00045726172,0.0016528663,0.0030360997,0.0016475981],"domain_scores_gemma":[0.9237056,0.05812243,0.005267961,0.006743771,0.0045890342,0.0015712975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010374631,0.001482143,0.0017903254,0.0022577408,0.0016604435,0.0059359213,0.0036845412,0.0021674547,0.0045304764],"category_scores_gemma":[0.052154526,0.0008664655,0.001820333,0.0030118765,0.0030770763,0.011153892,0.0027249309,0.0046782037,0.0006019372],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004433135,0.0004512832,0.0051728436,0.0003872836,0.00030833817,0.00020572127,0.00035199575,0.53511727,0.004248048,0.40766916,0.004341368,0.041303437],"study_design_scores_gemma":[0.000013519642,0.00009914628,0.0003927565,0.000031221214,0.00004494427,0.00011411439,0.00010336497,0.8104009,0.001596091,0.18552232,0.0016580316,0.000023550518],"about_ca_topic_score_codex":0.002410747,"about_ca_topic_score_gemma":0.0021988165,"teacher_disagreement_score":0.010374631,"about_ca_system_score_codex":0.0038064031,"about_ca_system_score_gemma":0.003792886,"threshold_uncertainty_score":0.05486697},"labels":[],"label_agreement":null},{"id":"W3150519068","doi":"10.1109/ipdps.2006.1639543","title":"Optimal map construction of an unknown torus","year":2006,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Torus; Security token; Node (physics); Enhanced Data Rates for GSM Evolution; Computer science; Mathematics; Multi-agent system; Algorithm; Combinatorics; Topology (electrical circuits); Discrete mathematics; Artificial intelligence; Geometry; Computer network; Physics","score_opus":0.009185106305420774,"score_gpt":0.23622643331773757,"score_spread":0.2270413270123168,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3150519068","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18552612,0.00024634658,0.8002709,0.00040944744,0.00006268077,0.00011201871,0.00020292345,0.0005639679,0.012605526],"genre_scores_gemma":[0.6761499,0.00026637068,0.31410995,0.000046765897,0.0000330839,0.00014088543,0.0003902985,0.00017826885,0.0086845355],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99956256,0.00013196866,0.000017409227,0.00012169296,0.00007063309,0.00009575677],"domain_scores_gemma":[0.9991053,0.0005123002,0.00010474047,0.0001303126,0.00007833768,0.00006900866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046812548,0.00047044264,0.00072409253,0.00038293004,0.0008064032,0.000936757,0.0010507571,0.0008293746,0.0039218008],"category_scores_gemma":[0.0027145413,0.00043300717,0.00064053363,0.00055118185,0.0011851821,0.002422069,0.0013108748,0.0006967783,0.00052418775],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021902463,0.000060964558,0.00063334225,0.00019902084,0.00003175596,0.00041661874,0.0002356881,0.8678656,0.0035253665,0.08334211,0.0027425133,0.040727925],"study_design_scores_gemma":[0.000032044707,0.00007739907,0.00019369532,0.000011168816,0.000015406704,0.000102660095,0.00018166515,0.92986226,0.0027058015,0.062919974,0.0038817227,0.000016178285],"about_ca_topic_score_codex":0.0032678484,"about_ca_topic_score_gemma":0.002141976,"teacher_disagreement_score":0.0039218008,"about_ca_system_score_codex":0.00095103204,"about_ca_system_score_gemma":0.0010414564,"threshold_uncertainty_score":0.013119757},"labels":[],"label_agreement":null},{"id":"W3154756789","doi":"10.1007/s12530-021-09378-1","title":"On utilizing the transitivity pursuit-enhanced object partitioning to optimize self-organizing lists-on-lists","year":2021,"lang":"en","type":"article","venue":"Evolving Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Transitive relation; Computer science; Context (archaeology); Object (grammar); Filter (signal processing); Theoretical computer science; Artificial intelligence; Mathematics; Computer vision; Combinatorics","score_opus":0.020976038599415048,"score_gpt":0.2616387712903479,"score_spread":0.24066273269093286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154756789","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027238451,0.00040632827,0.96893054,0.00016723998,0.000042712592,0.000054321128,0.000028263441,0.00017751471,0.0029546197],"genre_scores_gemma":[0.62462187,0.0005753679,0.36845258,0.00030981132,0.000092484064,0.0002445318,0.00021503455,0.00015459153,0.005333708],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998062,0.000060210372,0.000010797967,0.00003336441,0.00006158334,0.000027771503],"domain_scores_gemma":[0.99950635,0.00028792105,0.000039394075,0.000039813076,0.000098718534,0.000027651478],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00079071696,0.000691329,0.0009855166,0.0006382272,0.0005741026,0.00084539247,0.0012437186,0.0010737773,0.0017300616],"category_scores_gemma":[0.0019583278,0.00036181658,0.00048036085,0.0009987135,0.0006633204,0.0013606119,0.0012144737,0.00066664227,0.00033085662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007289947,0.00006523863,0.000358014,0.00008125562,0.00003752217,0.000026738691,0.00007014847,0.90966505,0.0037502986,0.015996268,0.0015424321,0.0683342],"study_design_scores_gemma":[0.000003509488,0.00002371616,0.00003480598,0.0000023852149,0.0000034542547,0.000005921185,0.000005446088,0.99774534,0.00027100762,0.0017212146,0.00018046597,0.0000026928817],"about_ca_topic_score_codex":0.0032601322,"about_ca_topic_score_gemma":0.0037866675,"teacher_disagreement_score":0.0032601322,"about_ca_system_score_codex":0.00061127386,"about_ca_system_score_gemma":0.0008390237,"threshold_uncertainty_score":0.006482303},"labels":[],"label_agreement":null},{"id":"W3156953634","doi":"10.1007/978-3-030-86838-3_29","title":"Labeling Schemes for Deterministic Radio Multi-broadcast","year":2021,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Node (physics); Set (abstract data type); Radio broadcasting; Radio networks; Broadcasting (networking); Broadcast engineering; Distributed computing; Theoretical computer science; Telecommunications; Engineering; Wireless network; Wireless","score_opus":0.04539100033866524,"score_gpt":0.32003762845249817,"score_spread":0.27464662811383295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3156953634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022583993,0.000704424,0.95069325,0.0016119912,0.00024237469,0.00023245084,0.00074970163,0.0010601485,0.02212169],"genre_scores_gemma":[0.5934585,0.0012831268,0.37055755,0.0012268443,0.00047401857,0.001089014,0.0011857921,0.0006348873,0.03009027],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99584645,0.0013442367,0.00026697366,0.0007875836,0.00093845575,0.0008163556],"domain_scores_gemma":[0.9838054,0.009579232,0.00083337317,0.004422353,0.00078377244,0.0005758498],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040713227,0.0011736886,0.0020298567,0.001117384,0.0022384196,0.0038001882,0.0044331253,0.0025282176,0.010014497],"category_scores_gemma":[0.014955948,0.0010910799,0.0012804583,0.0025603168,0.0023656872,0.0058230036,0.006048181,0.004094923,0.0017863921],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006755423,0.00013396067,0.00023121045,0.00034741883,0.000046466084,0.00007138269,0.0003192987,0.10039028,0.0028326863,0.81710356,0.011271474,0.066576764],"study_design_scores_gemma":[0.00016338145,0.000082971754,0.00012044845,0.00008278325,0.000049810904,0.0000844003,0.00005923043,0.24424076,0.0017822395,0.7446974,0.008586951,0.000049547292],"about_ca_topic_score_codex":0.0019474382,"about_ca_topic_score_gemma":0.0021723227,"teacher_disagreement_score":0.010014497,"about_ca_system_score_codex":0.0044658906,"about_ca_system_score_gemma":0.0029439714,"threshold_uncertainty_score":0.033501863},"labels":[],"label_agreement":null},{"id":"W3158797200","doi":"10.4230/lipics.mfcs.2021.57","title":"Online Domination: The Value of Getting to Know All Your Neighbors","year":2021,"lang":"en","type":"preprint","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Bipartite graph; Combinatorics; Competitive analysis; Vertex (graph theory); Mathematics; Graph; Planar graph; Node (physics); Set (abstract data type); Computer science; Discrete mathematics; Upper and lower bounds","score_opus":0.030331920693422384,"score_gpt":0.3110980857950028,"score_spread":0.2807661651015804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3158797200","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30369702,0.0021079162,0.6556851,0.0057287198,0.0003219955,0.0002221756,0.0007745333,0.00079833774,0.030664224],"genre_scores_gemma":[0.94319123,0.0007886923,0.04937747,0.0005492282,0.00024748856,0.000114445684,0.0003073273,0.00020938304,0.005214862],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9963642,0.0013258273,0.00010882597,0.0009660651,0.00064484484,0.00059030054],"domain_scores_gemma":[0.96015334,0.030926157,0.0025492264,0.0032173006,0.001268727,0.0018852253],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003683218,0.0012980872,0.0019726353,0.00087153126,0.0015742464,0.0029471673,0.004209971,0.001955828,0.005027364],"category_scores_gemma":[0.025551192,0.00064514397,0.0012701089,0.0016215036,0.0027285304,0.0094184475,0.002739807,0.002858359,0.0008045964],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020943757,0.0007038296,0.009679949,0.0009575373,0.00056720193,0.00084755314,0.0010560455,0.48479453,0.018077895,0.32520625,0.0135813635,0.14243346],"study_design_scores_gemma":[0.000104777864,0.0003870252,0.001168004,0.000057417365,0.00015986105,0.00071104185,0.00020815362,0.7203291,0.0059422106,0.26495102,0.0059239967,0.000057393823],"about_ca_topic_score_codex":0.0019041073,"about_ca_topic_score_gemma":0.0012653628,"teacher_disagreement_score":0.005027364,"about_ca_system_score_codex":0.0024238753,"about_ca_system_score_gemma":0.0015068077,"threshold_uncertainty_score":0.019478977},"labels":[],"label_agreement":null},{"id":"W3160973854","doi":"10.1016/j.jcss.2021.04.003","title":"Exploration of dynamic networks: Tight bounds on the number of agents","year":2021,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada","keywords":"Bounded function; Computer science; Graph; Interval (graph theory); Upper and lower bounds; Mathematics; Discrete mathematics; Topology (electrical circuits); Combinatorics; Theoretical computer science","score_opus":0.044241695295764084,"score_gpt":0.3022377106508853,"score_spread":0.2579960153551212,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160973854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14933406,0.009354356,0.7677382,0.012407946,0.00044478063,0.00037320008,0.0011179843,0.0012317464,0.05799765],"genre_scores_gemma":[0.84084815,0.004950993,0.13394983,0.001474123,0.00051215757,0.00064921903,0.0007753797,0.00095548487,0.015884789],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954457,0.0020071403,0.00018666597,0.000740729,0.00076040364,0.0008593205],"domain_scores_gemma":[0.8639355,0.12093477,0.004423125,0.00462628,0.002145967,0.0039344137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008275158,0.003053961,0.0043862457,0.0028781455,0.0024435355,0.005268781,0.0048909304,0.0045296378,0.01230228],"category_scores_gemma":[0.086032584,0.0026556435,0.002316359,0.0029585203,0.00536636,0.014486095,0.008385102,0.007044614,0.0011072088],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011985278,0.0003558516,0.0027428465,0.00076576544,0.00024379589,0.00020966111,0.00046840942,0.8121205,0.0022946603,0.13447008,0.008688273,0.03644164],"study_design_scores_gemma":[0.000079145255,0.000103910934,0.000344326,0.00012773075,0.00005958084,0.00012479353,0.00009369968,0.8684056,0.000730505,0.12823935,0.0016686842,0.00002268181],"about_ca_topic_score_codex":0.0028113988,"about_ca_topic_score_gemma":0.00532716,"teacher_disagreement_score":0.01230228,"about_ca_system_score_codex":0.0030315684,"about_ca_system_score_gemma":0.0033570041,"threshold_uncertainty_score":0.043763697},"labels":[],"label_agreement":null},{"id":"W3171894515","doi":"10.23952/jano.3.2021.1.07","title":"Learning incentivization strategy for resource rebalancing in shared services with a budget constraint","year":2021,"lang":"en","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Constraint (computer-aided design); Resource (disambiguation); Budget constraint; Resource allocation; Computer science; Resource constraints; Business; Operations research; Mathematical optimization; Chemistry; Economics; Distributed computing; Microeconomics; Engineering; Mathematics; Computer network; Mechanical engineering","score_opus":0.009843123987047843,"score_gpt":0.23540081907985674,"score_spread":0.2255576950928089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3171894515","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10021633,0.00030911766,0.89444256,0.0006310343,0.000060127895,0.00014785235,0.000057488636,0.00032817025,0.0038073813],"genre_scores_gemma":[0.9658393,0.00007584754,0.032304402,0.00009748003,0.000015589872,0.000089007146,0.000028798395,0.000028295084,0.0015212945],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988619,0.0005199236,0.000047208858,0.00023149049,0.00015631093,0.00018315828],"domain_scores_gemma":[0.9961188,0.002703422,0.00043531705,0.0001501032,0.00031640404,0.00027594672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023603712,0.00094848353,0.001397619,0.00038358403,0.00040712245,0.0009794674,0.0012383431,0.0016710972,0.0024237381],"category_scores_gemma":[0.009146365,0.00045746088,0.0003981195,0.00032850972,0.0011779362,0.0015830216,0.0011679722,0.0016699766,0.0002453999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016461266,0.00008655935,0.00078215287,0.000057807854,0.00003266474,0.00009730579,0.00008695442,0.9734238,0.0011991787,0.011324891,0.0005333578,0.012210761],"study_design_scores_gemma":[0.000016847112,0.000023500488,0.000070769136,0.0000048209363,0.0000042650395,0.00000910053,0.000008859832,0.99707174,0.00018888712,0.0024615012,0.00013634734,0.0000034226923],"about_ca_topic_score_codex":0.0052032582,"about_ca_topic_score_gemma":0.003400755,"teacher_disagreement_score":0.0052032582,"about_ca_system_score_codex":0.0013392721,"about_ca_system_score_gemma":0.0020921761,"threshold_uncertainty_score":0.012483001},"labels":[],"label_agreement":null},{"id":"W3174973594","doi":"10.35708/rc1869-126260","title":"Identifying Hazardous Shapes in the Plane","year":2020,"lang":"en","type":"article","venue":"International Journal of Robotic Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Vertex (graph theory); Regular polygon; Line segment; Mobile robot; Hazardous waste; A priori and a posteriori; Enhanced Data Rates for GSM Evolution; Line (geometry); Computer science; Plane (geometry); Set (abstract data type); Artificial intelligence; Combinatorics; Mathematics; Algorithm; Engineering; Geometry; Graph","score_opus":0.05499822655337135,"score_gpt":0.3129449552881545,"score_spread":0.2579467287347832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3174973594","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20904912,0.00044272895,0.78392494,0.00041262314,0.000022576385,0.00014705629,0.00039517035,0.0005287016,0.0050770747],"genre_scores_gemma":[0.6677352,0.00044900016,0.32775348,0.000099747806,0.000027058402,0.00011530366,0.000917216,0.00015268699,0.0027502854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992471,0.00016882525,0.000033924534,0.0002441595,0.00020291515,0.00010320741],"domain_scores_gemma":[0.998063,0.001085064,0.00034810277,0.00022508,0.00017721692,0.00010150376],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064825156,0.0009467843,0.0010597672,0.0009917004,0.0008156656,0.0014756916,0.0013978746,0.0014279608,0.0018585507],"category_scores_gemma":[0.004402225,0.0008385026,0.00092158245,0.001013612,0.0013662734,0.0023876862,0.0024469073,0.0007769375,0.00085070636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046731636,0.00007201428,0.008052604,0.00020431724,0.00005778155,0.00088247465,0.0005683636,0.8630391,0.008865492,0.018927274,0.0016075562,0.09725561],"study_design_scores_gemma":[0.000022445529,0.00007740699,0.0015599919,0.000032085572,0.000014694862,0.00047548805,0.0004958013,0.9679614,0.0048585776,0.021807117,0.0026637574,0.000031222055],"about_ca_topic_score_codex":0.005355795,"about_ca_topic_score_gemma":0.0031333608,"teacher_disagreement_score":0.005355795,"about_ca_system_score_codex":0.00071739743,"about_ca_system_score_gemma":0.0007612696,"threshold_uncertainty_score":0.010649264},"labels":[],"label_agreement":null},{"id":"W3175020564","doi":"10.1145/3448016.3459243","title":"Efficient and Effective Algorithms for Revenue Maximization in Social Advertising","year":2021,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Oracle; Revenue; Computer science; Approximation algorithm; Maximization; Computation; Payment; Quality (philosophy); Social network (sociolinguistics); Social media; Algorithm; Mathematical optimization; Mathematics; World Wide Web; Economics","score_opus":0.01784660297091779,"score_gpt":0.292141372480385,"score_spread":0.27429476950946724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175020564","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019008707,0.0029783817,0.9656085,0.0015392303,0.00015652517,0.0003156695,0.0003648429,0.0013190781,0.00870904],"genre_scores_gemma":[0.29484853,0.0023080406,0.6952022,0.00065979693,0.0004977989,0.0006882595,0.0012438435,0.0003997343,0.004151829],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967416,0.0014101884,0.00015823655,0.00060771767,0.00064807606,0.00043420336],"domain_scores_gemma":[0.99290705,0.00528697,0.00045133763,0.0007295514,0.00040746658,0.0002176758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00378694,0.0027800458,0.0028846627,0.0019878424,0.0010124071,0.0035109145,0.0036226665,0.0030442262,0.0042724456],"category_scores_gemma":[0.015505284,0.0009317203,0.0016742112,0.0040229345,0.0015017593,0.005131396,0.0024944688,0.0036978843,0.0019417402],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035368715,0.0007291381,0.0016554465,0.00053238554,0.00014825958,0.00013037701,0.00028633626,0.6094435,0.0015414346,0.09188229,0.02545831,0.26783884],"study_design_scores_gemma":[0.00008312282,0.000032743526,0.00009979913,0.000023404804,0.000022028797,0.000048112197,0.000039186998,0.9382365,0.0004239055,0.059048872,0.0019338295,0.000008475704],"about_ca_topic_score_codex":0.0037685134,"about_ca_topic_score_gemma":0.0047146287,"teacher_disagreement_score":0.0042724456,"about_ca_system_score_codex":0.0029307713,"about_ca_system_score_gemma":0.0033662992,"threshold_uncertainty_score":0.021264374},"labels":[],"label_agreement":null},{"id":"W3175635045","doi":"10.1609/icaps.v31i1.15967","title":"A Competitive Analysis of Online Multi-Agent Path Finding","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Automated Planning and Scheduling","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Competitive analysis; Online algorithm; Computer science; Controllability; Path (computing); Set (abstract data type); Bounded function; Plan (archaeology); Asymptotically optimal algorithm; Mathematical optimization; Bounded rationality; Algorithm; Mathematics; Upper and lower bounds; Artificial intelligence; Applied mathematics","score_opus":0.07027185868418233,"score_gpt":0.33327608150466753,"score_spread":0.2630042228204852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175635045","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.094758615,0.0012328794,0.87220675,0.0016819094,0.00013330596,0.0002801135,0.00041448502,0.00050601625,0.02878599],"genre_scores_gemma":[0.83818537,0.0008327143,0.15380332,0.00037138985,0.00025480098,0.0003563573,0.00037829595,0.00026218343,0.0055555124],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9958527,0.0012910673,0.00013347958,0.0008221744,0.0011611631,0.0007395182],"domain_scores_gemma":[0.97146565,0.02194344,0.0019511279,0.001844431,0.0016418586,0.0011535597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034584422,0.001688105,0.001836283,0.0013617877,0.001620413,0.0031684283,0.004348559,0.0019979437,0.0072544003],"category_scores_gemma":[0.027364645,0.0007489135,0.0012120942,0.0019374782,0.0023712385,0.006189651,0.002268574,0.0027432917,0.00092222594],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006125075,0.00048672344,0.0028721439,0.00048362685,0.00015897366,0.00025317044,0.0003451309,0.7357164,0.0058977962,0.18306696,0.0054922965,0.06461427],"study_design_scores_gemma":[0.00003399568,0.00009810154,0.00022310876,0.000010364351,0.000020572774,0.00008633125,0.000041341205,0.9593786,0.00077029684,0.038003013,0.0013205148,0.000013764621],"about_ca_topic_score_codex":0.0055920617,"about_ca_topic_score_gemma":0.00311143,"teacher_disagreement_score":0.0072544003,"about_ca_system_score_codex":0.003370658,"about_ca_system_score_gemma":0.002855525,"threshold_uncertainty_score":0.024455965},"labels":[],"label_agreement":null},{"id":"W3177044138","doi":"10.1007/978-3-030-79150-6_11","title":"Object Migration Automata for Non-equal Partitioning Problems with Known Partition Sizes","year":2021,"lang":"en","type":"book-chapter","venue":"IFIP advances in information and communication technology","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Partition (number theory); Computer science; A priori and a posteriori; Cellular automaton; Algorithm; Graph partition; Theoretical computer science; Partition problem; Automaton; Mathematics; Graph; Combinatorics","score_opus":0.012388473284107646,"score_gpt":0.257500720418397,"score_spread":0.24511224713428936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177044138","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050235994,0.00061470486,0.9352554,0.00049049273,0.00017511703,0.000068047564,0.00019251378,0.000685489,0.012282091],"genre_scores_gemma":[0.47948444,0.0008210442,0.49486277,0.00021898467,0.000107157946,0.00032861962,0.00049839565,0.00034528982,0.02333319],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99958044,0.00008023645,0.000045039316,0.00014020484,0.0000995293,0.000054599543],"domain_scores_gemma":[0.99732167,0.001847125,0.0001494586,0.00038484708,0.0002043578,0.000092564616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006037654,0.0005281362,0.0007323223,0.00044709866,0.00081063755,0.0017778897,0.0016745541,0.0011833163,0.005542677],"category_scores_gemma":[0.004023403,0.00045227795,0.0008014953,0.00077393197,0.0011466154,0.00319289,0.0015209602,0.0020171632,0.00073295727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033262148,0.00014926755,0.0008231102,0.00038267177,0.00003696756,0.00021855017,0.0004890464,0.4529435,0.009233635,0.37119266,0.0068176575,0.15738022],"study_design_scores_gemma":[0.000017722563,0.00003413316,0.00017183025,0.000029660496,0.000012591149,0.000070741815,0.00006257529,0.77787596,0.0020610204,0.21648856,0.0031592622,0.000015958258],"about_ca_topic_score_codex":0.0015074492,"about_ca_topic_score_gemma":0.002759935,"teacher_disagreement_score":0.005542677,"about_ca_system_score_codex":0.001208978,"about_ca_system_score_gemma":0.00077721453,"threshold_uncertainty_score":0.018542051},"labels":[],"label_agreement":null},{"id":"W3177770101","doi":"10.1016/j.tcs.2021.06.038","title":"On synchronization and orientation in distributed barrier coverage with relocatable sensors","year":2021,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Concordia University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Orientation (vector space); Asynchronous communication; Visibility; Synchronization (alternating current); Position (finance); Range (aeronautics); Cover (algebra); Computer science; Focus (optics); Algorithm; Mathematics; Geometry; Telecommunications; Physics; Engineering; Aerospace engineering; Channel (broadcasting)","score_opus":0.00543839597750751,"score_gpt":0.23059370979311655,"score_spread":0.22515531381560905,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3177770101","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09000363,0.0012529076,0.8996494,0.0007957922,0.00015067625,0.000080096084,0.00010364136,0.0001404571,0.007823477],"genre_scores_gemma":[0.9457477,0.0014677227,0.045333173,0.00017356778,0.00017818356,0.00015209761,0.00013865877,0.00015283101,0.006656018],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99908364,0.00039351193,0.000035543297,0.00015929142,0.00018203331,0.00014608748],"domain_scores_gemma":[0.9929743,0.005565479,0.00063313235,0.0002456697,0.00031982936,0.00026153174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019150841,0.0008003131,0.0014518235,0.0011289094,0.00073297817,0.0012159415,0.0016727438,0.001160978,0.002792168],"category_scores_gemma":[0.01369036,0.00061991985,0.0007271334,0.0017031286,0.0020453657,0.0023439997,0.0026289534,0.0011857236,0.00019807728],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036062617,0.00005064327,0.0010840826,0.00012570948,0.00004541998,0.00011770388,0.00019235008,0.89630616,0.0021852974,0.08179559,0.0012960455,0.016440354],"study_design_scores_gemma":[0.00003365538,0.000055949044,0.00027506985,0.000010169914,0.000016917887,0.000020588215,0.000058675487,0.9776569,0.0003852279,0.021052472,0.00042376728,0.000010587328],"about_ca_topic_score_codex":0.006503136,"about_ca_topic_score_gemma":0.0032599168,"teacher_disagreement_score":0.006503136,"about_ca_system_score_codex":0.0012268405,"about_ca_system_score_gemma":0.0009391616,"threshold_uncertainty_score":0.012930572},"labels":[],"label_agreement":null},{"id":"W3181822265","doi":"10.1007/978-3-030-93043-1_1","title":"On the Fault-Tolerant Online Bin Packing Problem","year":2021,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Replica; Bin packing problem; Server; Bin; Computer science; Fault tolerance; Competitive analysis; Sequence (biology); Distributed computing; Mathematics; Algorithm; Parallel computing; Computer network; Upper and lower bounds","score_opus":0.030603976821063923,"score_gpt":0.28629887795508696,"score_spread":0.25569490113402304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3181822265","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.16754255,0.0034971142,0.79190516,0.0057265735,0.001035277,0.00020518522,0.0010465196,0.00092110195,0.028120408],"genre_scores_gemma":[0.8413859,0.0026488786,0.13474257,0.0009831995,0.0010909705,0.00022631393,0.0012667929,0.00047375844,0.017181674],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979311,0.00064824946,0.000096122676,0.00032398337,0.0006143318,0.00038614983],"domain_scores_gemma":[0.99141425,0.0063610687,0.0005456955,0.0008791252,0.00045103228,0.00034888356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019102114,0.0011373688,0.0024488322,0.0011309868,0.0012807741,0.0027125543,0.00294194,0.002391591,0.008975473],"category_scores_gemma":[0.0145461485,0.0006412251,0.0009237573,0.003227133,0.0014318773,0.0062282626,0.0024099937,0.0028651555,0.00074759364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016096975,0.00042601232,0.0011342629,0.00052796636,0.00010358825,0.00031839396,0.00019856413,0.7078538,0.002658472,0.13916202,0.022069851,0.12393748],"study_design_scores_gemma":[0.00007420772,0.000099263685,0.0004001044,0.000034170156,0.000027789572,0.00015261602,0.00007509614,0.7912288,0.0008134272,0.20457177,0.0025059073,0.000016978274],"about_ca_topic_score_codex":0.0023053335,"about_ca_topic_score_gemma":0.0016404142,"teacher_disagreement_score":0.008975473,"about_ca_system_score_codex":0.0016861511,"about_ca_system_score_gemma":0.0012458509,"threshold_uncertainty_score":0.030025959},"labels":[],"label_agreement":null},{"id":"W3183614723","doi":"10.1145/3465084.3467910","title":"Separating Bounded and Unbounded Asynchrony for Autonomous Robots","year":2021,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Asynchrony (computer programming); Bounded function; Convergence (economics); Asynchronous communication; Computer science; Range (aeronautics); Euclidean geometry; Plane (geometry); Mathematics; Mathematical analysis; Geometry","score_opus":0.02384694003927283,"score_gpt":0.2868991423199727,"score_spread":0.26305220228069986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3183614723","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09644622,0.0006103252,0.8964509,0.0009125546,0.000052380292,0.00004425969,0.000040162016,0.00013802225,0.005305182],"genre_scores_gemma":[0.941862,0.00048772758,0.055006336,0.00010006007,0.0000907123,0.00012563063,0.00004220099,0.000040740575,0.002244571],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977354,0.00093766506,0.00012896245,0.0005568084,0.00042994824,0.00021127152],"domain_scores_gemma":[0.9874204,0.009586199,0.0013415582,0.000835858,0.0003339931,0.00048206915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024806515,0.0008650491,0.0009599087,0.00053274346,0.00077684503,0.0013070991,0.0014507725,0.0013505721,0.0011245657],"category_scores_gemma":[0.014980667,0.0003956489,0.0007775353,0.0005651957,0.003807034,0.0036000947,0.0032655566,0.0021724096,0.00020209224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028951102,0.000051816405,0.0011411492,0.0001564353,0.00005125406,0.0003748113,0.0004465731,0.5465675,0.0051307273,0.43413886,0.00039538008,0.01125598],"study_design_scores_gemma":[0.000053866825,0.00010798817,0.00021168501,0.000016178104,0.00001452251,0.00004032354,0.000059300088,0.78316754,0.0010033936,0.21442853,0.0008824992,0.000014174981],"about_ca_topic_score_codex":0.0011957154,"about_ca_topic_score_gemma":0.0006864393,"teacher_disagreement_score":0.0024806515,"about_ca_system_score_codex":0.000902386,"about_ca_system_score_gemma":0.0009767021,"threshold_uncertainty_score":0.0131191015},"labels":[],"label_agreement":null},{"id":"W3185337306","doi":"10.22215/etd/2021-14519","title":"Search and Rendezvous by Mobile Robots in Continuous Domains","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Rendezvous; Domain (mathematical analysis); Task (project management); Mobile robot; Function (biology); Robot; Position (finance); Computer science; Combinatorics; Discrete mathematics; Mathematics; Mathematical optimization; Artificial intelligence; Engineering; Mathematical analysis","score_opus":0.010415458597909455,"score_gpt":0.2812024195451884,"score_spread":0.27078696094727894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185337306","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23934077,0.0054301606,0.72419,0.0010853534,0.00012116129,0.000098942735,0.00016956309,0.00022700871,0.029336987],"genre_scores_gemma":[0.89919573,0.0021793223,0.085265554,0.00007263126,0.000071049784,0.0001267519,0.0001892862,0.00005542721,0.012844245],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995111,0.0001705552,0.000019178478,0.000106346655,0.00011453899,0.00007828957],"domain_scores_gemma":[0.998825,0.0008797856,0.00011047224,0.000057681325,0.00004579434,0.000081144586],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006575427,0.0005692195,0.00085880735,0.0005818082,0.0005559924,0.0014150613,0.0007905998,0.0010963101,0.002144653],"category_scores_gemma":[0.00306695,0.00039079104,0.00069828826,0.0008012544,0.001698116,0.0014365402,0.0015184928,0.00089561904,0.00026174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016542454,0.000037443588,0.00055500347,0.00017304844,0.000050250437,0.00015234348,0.000264694,0.85238016,0.0018068728,0.11548195,0.0016312217,0.02730164],"study_design_scores_gemma":[0.00004148332,0.000052184354,0.00027161188,0.00003048866,0.0000093375,0.000046273664,0.000119205695,0.94470155,0.0007121448,0.05050057,0.0035042204,0.000010956058],"about_ca_topic_score_codex":0.0046896683,"about_ca_topic_score_gemma":0.0027314837,"teacher_disagreement_score":0.0046896683,"about_ca_system_score_codex":0.0009627619,"about_ca_system_score_gemma":0.00066290435,"threshold_uncertainty_score":0.009324729},"labels":[],"label_agreement":null},{"id":"W3186619231","doi":"10.1007/978-3-030-80879-2_4","title":"Online Coloring and a New Type of Adversary for Online Graph Problems","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Concordia University; Université de Montréal","funders":"","keywords":"Adversary; Bipartite graph; Parameterized complexity; Combinatorics; Computer science; Bounded function; Mathematics; Discrete mathematics; Graph; Theoretical computer science; Computer security","score_opus":0.0589688178431416,"score_gpt":0.2940742975132717,"score_spread":0.2351054796701301,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3186619231","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010534443,0.00069143344,0.9410013,0.0018055061,0.000773171,0.00013803238,0.00022710688,0.0005343335,0.044294562],"genre_scores_gemma":[0.38622317,0.00251564,0.49238607,0.0023526046,0.003127288,0.0007535309,0.000684426,0.00086711854,0.11109025],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99599165,0.0014398101,0.0001328781,0.00078504207,0.0011461688,0.0005045822],"domain_scores_gemma":[0.98849386,0.0067540267,0.00044630535,0.003036208,0.000595359,0.00067430787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029900784,0.0019049521,0.0017063121,0.0011536201,0.0019341247,0.0040740534,0.00583475,0.0041081733,0.009704471],"category_scores_gemma":[0.00972391,0.0011204717,0.0024508701,0.0025231468,0.004138342,0.009409869,0.0052615735,0.01050499,0.0017900306],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017284934,0.00015547637,0.00030268668,0.00016870105,0.000043672826,0.0001341116,0.00014364521,0.0408106,0.002479453,0.90732706,0.01454976,0.03371204],"study_design_scores_gemma":[0.00004232201,0.00008678159,0.00014014973,0.000034714376,0.00003929702,0.00025400185,0.000038863727,0.22690393,0.0013744521,0.7516643,0.019389173,0.000032073505],"about_ca_topic_score_codex":0.00076642935,"about_ca_topic_score_gemma":0.0013509246,"teacher_disagreement_score":0.009704471,"about_ca_system_score_codex":0.0026958135,"about_ca_system_score_gemma":0.0018107117,"threshold_uncertainty_score":0.032464683},"labels":[],"label_agreement":null},{"id":"W3188945842","doi":"10.1109/tnnls.2021.3099095","title":"Solving Two-Person Zero-Sum Stochastic Games With Incomplete Information Using Learning Automata With Artificial Barriers","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Neural Networks and Learning Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Fundação para a Ciência e a Tecnologia; Natural Sciences and Engineering Research Council of Canada","keywords":"Zero (linguistics); Zero-sum game; Automaton; Learning automata; Artificial intelligence; Computer science; Complete information; Mathematical economics; Mathematics; Game theory","score_opus":0.01986134679584682,"score_gpt":0.23164229711516401,"score_spread":0.2117809503193172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188945842","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041000202,0.00019503995,0.9541856,0.0003196104,0.00003994983,0.00006489738,0.000040285016,0.00022900722,0.0039255205],"genre_scores_gemma":[0.8120931,0.00025191042,0.18335025,0.00019155069,0.000037232872,0.00035216514,0.00009505417,0.00005872683,0.0035699985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991841,0.0002767444,0.000066564884,0.00022842249,0.00013705225,0.00010702374],"domain_scores_gemma":[0.9976446,0.0016556596,0.00021517187,0.00017691706,0.00017364432,0.00013407576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011875621,0.00094817637,0.0011972915,0.00038158934,0.00055354054,0.0016543312,0.0013715064,0.0015904534,0.002123468],"category_scores_gemma":[0.0048557743,0.00057348295,0.0013886548,0.0002765882,0.0012526726,0.0016261627,0.0023174149,0.0019846342,0.00034050448],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008297876,0.000060206312,0.0010595573,0.00012729084,0.000047620706,0.0000970504,0.00021045354,0.9062206,0.0020721667,0.07125213,0.00037182204,0.018398164],"study_design_scores_gemma":[0.0000124145035,0.000027982063,0.00004169069,0.000009035561,0.0000068729087,0.00001122171,0.000012232786,0.9838489,0.00032291107,0.015397654,0.000302486,0.000006438484],"about_ca_topic_score_codex":0.002798741,"about_ca_topic_score_gemma":0.002702253,"teacher_disagreement_score":0.002798741,"about_ca_system_score_codex":0.00088859204,"about_ca_system_score_gemma":0.0015913569,"threshold_uncertainty_score":0.007103741},"labels":[],"label_agreement":null},{"id":"W3191242629","doi":"10.1007/978-3-030-89240-1_6","title":"Evacuating from $$\\ell _p$$ Unit Disks in the Wireless Model","year":2021,"lang":"en","type":"preprint","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Unit disk; Homogeneous space; Metric (unit); Metric space; Combinatorics; Mathematics; Circumference; Upper and lower bounds; Regular polygon; Euclidean space; Type (biology); Unit (ring theory); Chord (peer-to-peer); Unit sphere; Euclidean geometry; Wireless; Space (punctuation); Computer science; Discrete mathematics; Geometry; Mathematical analysis; Engineering; Distributed computing","score_opus":0.05171197795241873,"score_gpt":0.30831687088632176,"score_spread":0.25660489293390304,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3191242629","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38830885,0.0040289136,0.45812595,0.028461624,0.0012929849,0.00024967958,0.0034497392,0.0007301851,0.115352154],"genre_scores_gemma":[0.9115784,0.0024979198,0.010465539,0.000876915,0.00040600126,0.00019326585,0.00059757195,0.00028806578,0.07309632],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99891436,0.00035634966,0.000038783946,0.0002024236,0.00011987153,0.00036816666],"domain_scores_gemma":[0.9958443,0.002135641,0.000519661,0.00033900878,0.00031249752,0.0008489841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014102559,0.0013364593,0.002307952,0.0010724498,0.0021595992,0.004423617,0.0056818514,0.0043469034,0.02239356],"category_scores_gemma":[0.007696831,0.0010837612,0.0011432013,0.0015990281,0.002891013,0.010022191,0.0039155246,0.0029930994,0.0027054688],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039376647,0.00016681847,0.0010035412,0.00020356661,0.00004832388,0.00056020316,0.00038054524,0.2941267,0.00057282386,0.67685604,0.017766068,0.007921591],"study_design_scores_gemma":[0.00011817013,0.00012175218,0.00037017764,0.000071110546,0.0000419249,0.00027111446,0.0006294268,0.7038492,0.0002701193,0.2900447,0.0041519515,0.000060281593],"about_ca_topic_score_codex":0.010491937,"about_ca_topic_score_gemma":0.0060766577,"teacher_disagreement_score":0.02239356,"about_ca_system_score_codex":0.0017528146,"about_ca_system_score_gemma":0.0014805674,"threshold_uncertainty_score":0.07491392},"labels":[],"label_agreement":null},{"id":"W3195783669","doi":"10.1002/net.22075","title":"Impact of knowledge on the cost of treasure hunt in trees","year":2021,"lang":"en","type":"article","venue":"Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Treasure; Node (physics); Tree (set theory); Mathematics; Type (biology); Enhanced Data Rates for GSM Evolution; Computer science; Combinatorics; Artificial intelligence; Algorithm; Geography","score_opus":0.03562918770948417,"score_gpt":0.30564253735452745,"score_spread":0.2700133496450433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3195783669","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.8781921,0.0018245921,0.0968501,0.0032742394,0.00019057486,0.00017285082,0.0008231527,0.00048273714,0.018189665],"genre_scores_gemma":[0.9802962,0.00039121634,0.016860934,0.0001356841,0.000035549878,0.00006040672,0.00025337524,0.00012398392,0.0018426657],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99562943,0.0019376621,0.00020559544,0.0004349391,0.0008002719,0.0009921422],"domain_scores_gemma":[0.89877504,0.09069848,0.0028171055,0.0040303175,0.0020612674,0.0016177694],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005690875,0.00078212103,0.0013181895,0.0008815032,0.0009361195,0.0022068582,0.001978917,0.0018368074,0.005982712],"category_scores_gemma":[0.052494477,0.00050272304,0.00082905934,0.0011252466,0.0019194557,0.0047416426,0.0016046673,0.0023034478,0.00034239775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002070861,0.00027147678,0.0034897008,0.00021452346,0.00008037889,0.00010704882,0.0000672769,0.944364,0.0016393972,0.018771177,0.0017269441,0.027197212],"study_design_scores_gemma":[0.00007124812,0.00035965868,0.0016567732,0.000037122925,0.0000746446,0.00011182317,0.00011779845,0.9721429,0.0017628993,0.022967871,0.0006697627,0.000027500104],"about_ca_topic_score_codex":0.0049305847,"about_ca_topic_score_gemma":0.0043502687,"teacher_disagreement_score":0.005982712,"about_ca_system_score_codex":0.0031665089,"about_ca_system_score_gemma":0.0024808026,"threshold_uncertainty_score":0.03009659},"labels":[],"label_agreement":null},{"id":"W3196918658","doi":"10.1609/socs.v12i1.18577","title":"Extended Abstract: A Competitive Analysis of Online Multi-Agent Path Finding","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Path (computing); Online and offline; Online algorithm; Theoretical computer science; Algorithm; Artificial intelligence; Computer network","score_opus":0.02999098797217792,"score_gpt":0.30331443087961174,"score_spread":0.2733234429074338,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196918658","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046420135,0.0029061309,0.86303216,0.0066627963,0.0012806068,0.000390794,0.0014709419,0.0005528105,0.077283636],"genre_scores_gemma":[0.7726227,0.0025000488,0.17611854,0.0017355343,0.002795453,0.00079493265,0.0017424697,0.00079644274,0.04089391],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99695766,0.0010210539,0.0001030061,0.0006303009,0.00082979427,0.00045814228],"domain_scores_gemma":[0.9752738,0.017409593,0.0017699284,0.0016803371,0.0024255756,0.001440757],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028897254,0.0015829485,0.0017284859,0.0015980996,0.0015892257,0.003981016,0.0040366473,0.0027333302,0.03147687],"category_scores_gemma":[0.026226401,0.000552727,0.0014945384,0.0029117477,0.0019250722,0.0065675713,0.0026207268,0.004162337,0.002926789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006509541,0.0005340468,0.0025564546,0.00088613114,0.00017172997,0.00032733023,0.0002956115,0.32236838,0.0035865323,0.52000725,0.061250295,0.087365314],"study_design_scores_gemma":[0.000045028373,0.00012730248,0.00058371463,0.000045039542,0.000042370408,0.00013484669,0.00006569802,0.8134387,0.00067686004,0.1750044,0.0098014865,0.000034510493],"about_ca_topic_score_codex":0.0042598466,"about_ca_topic_score_gemma":0.0026001574,"teacher_disagreement_score":0.03147687,"about_ca_system_score_codex":0.0034593707,"about_ca_system_score_gemma":0.0022809457,"threshold_uncertainty_score":0.105300665},"labels":[],"label_agreement":null},{"id":"W3199020031","doi":"10.48550/arxiv.2109.10380","title":"Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Bipartite graph; Computer science; Matching (statistics); Reinforcement learning; Submodular set function; Machine learning; Set (abstract data type); Code (set theory); Artificial intelligence; Feature (linguistics); Process (computing); Variety (cybernetics); Greedy algorithm; Data mining; Theoretical computer science; Mathematical optimization; Algorithm; Mathematics","score_opus":0.10368130190836314,"score_gpt":0.2251592190344957,"score_spread":0.12147791712613257,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3199020031","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02454085,0.00032016126,0.97106564,0.00063829985,0.00004781755,0.00009809822,0.00013139842,0.0007663675,0.002391367],"genre_scores_gemma":[0.7846472,0.0003171171,0.20927338,0.0005347788,0.000083885745,0.00036084504,0.00042442404,0.00021829472,0.004140063],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985331,0.00063050806,0.00006721335,0.00036160776,0.000216051,0.00019144599],"domain_scores_gemma":[0.99416757,0.0042148726,0.00042984766,0.000521537,0.00040217227,0.00026406764],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034107394,0.0011051628,0.0017316738,0.0009791781,0.00059497135,0.0011035022,0.00280886,0.0020254431,0.004014047],"category_scores_gemma":[0.013272557,0.00074181834,0.00069416425,0.0011655133,0.0018925635,0.0029434983,0.0019880712,0.0031688395,0.00070784095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000112722155,0.00017149582,0.00091949606,0.00007717047,0.000038859893,0.00004174174,0.000056099092,0.9216793,0.00057035725,0.023865148,0.0021288288,0.050338846],"study_design_scores_gemma":[0.000009910841,0.00001230893,0.00003080543,0.000004835924,0.000002752472,0.0000044905905,0.0000033446267,0.98697996,0.00013059954,0.012651733,0.00016690767,0.0000024311848],"about_ca_topic_score_codex":0.0053717685,"about_ca_topic_score_gemma":0.0062098494,"teacher_disagreement_score":0.0053717685,"about_ca_system_score_codex":0.0020858224,"about_ca_system_score_gemma":0.0023906957,"threshold_uncertainty_score":0.018037915},"labels":[],"label_agreement":null},{"id":"W3202345783","doi":"10.4230/lipics.approx/random.2021.13","title":"Secretary Matching Meets Probing with Commitment","year":2021,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Bipartite graph; Matching (statistics); Competitive analysis; Combinatorics; Knapsack problem; Secretary problem; Online algorithm; Order (exchange); Stochastic block model; Generalization; Set (abstract data type); Time complexity; Mathematics; Context (archaeology); Oracle; Matroid; Discrete mathematics; Computer science; Algorithm; Mathematical optimization; Graph; Upper and lower bounds; Artificial intelligence","score_opus":0.016288179103186976,"score_gpt":0.2455387204149818,"score_spread":0.22925054131179481,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202345783","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.118940994,0.0002937277,0.8591132,0.0030947633,0.0001259144,0.00021176314,0.0008155458,0.0009358955,0.01646821],"genre_scores_gemma":[0.86593604,0.00032598336,0.120011166,0.0006408965,0.0002626289,0.00022049293,0.00088765833,0.00034481572,0.011370356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9937209,0.002212941,0.00025755275,0.0020048372,0.0008135398,0.0009902525],"domain_scores_gemma":[0.984617,0.009317316,0.0016265673,0.00260202,0.0007063435,0.0011307183],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003336985,0.0010951665,0.0019659577,0.00069668994,0.0011996861,0.0035918443,0.0027242235,0.0029527955,0.008887271],"category_scores_gemma":[0.018687254,0.00076281716,0.0018288175,0.0014929333,0.0022616896,0.007996168,0.004058285,0.004366665,0.0011210024],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005726357,0.0003135683,0.0018141957,0.00029166843,0.000115303366,0.0003228651,0.0003888276,0.30391437,0.0034305677,0.6425997,0.0063902694,0.039846055],"study_design_scores_gemma":[0.0000697811,0.00014680332,0.0002934005,0.000016273474,0.000024786954,0.00014311215,0.000113574504,0.6262749,0.0012830822,0.36846796,0.0031373776,0.000028869954],"about_ca_topic_score_codex":0.002460919,"about_ca_topic_score_gemma":0.0015901648,"teacher_disagreement_score":0.008887271,"about_ca_system_score_codex":0.0022135274,"about_ca_system_score_gemma":0.0022971698,"threshold_uncertainty_score":0.029730856},"labels":[],"label_agreement":null},{"id":"W3204335953","doi":"10.1109/icdcs51616.2021.00098","title":"Black Hole Search in Dynamic Rings","year":2021,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science","score_opus":0.021312122018203167,"score_gpt":0.28786546336751945,"score_spread":0.2665533413493163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3204335953","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08568375,0.0006827155,0.9044741,0.0006890768,0.0000700247,0.00008197716,0.00008088992,0.00017403525,0.008063568],"genre_scores_gemma":[0.7938417,0.0008532151,0.19830593,0.00020630033,0.00008140834,0.00014408294,0.00011741541,0.00007487539,0.0063750776],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990607,0.0004173648,0.00003175636,0.00019415504,0.00015152626,0.00014446731],"domain_scores_gemma":[0.9958948,0.0030326094,0.00041973894,0.0003047943,0.0001565176,0.00019159973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014660807,0.00047172554,0.00077129365,0.000488361,0.00072302896,0.0010710648,0.0011721757,0.000977701,0.0031594275],"category_scores_gemma":[0.007314,0.00032165818,0.0005858755,0.0004996746,0.0015061293,0.0032627613,0.0018478761,0.0010677207,0.0003324768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028880045,0.00008133532,0.00081321097,0.00014949072,0.000054777865,0.00018068914,0.00020280255,0.62802905,0.0030951444,0.3415691,0.0017841476,0.02375139],"study_design_scores_gemma":[0.000037681886,0.00008371261,0.00013713316,0.000018416864,0.000013000969,0.000090830545,0.00007795629,0.8687238,0.0012407228,0.12700404,0.002560579,0.000012123069],"about_ca_topic_score_codex":0.00076541404,"about_ca_topic_score_gemma":0.00065544766,"teacher_disagreement_score":0.0031594275,"about_ca_system_score_codex":0.0006602949,"about_ca_system_score_gemma":0.00056224485,"threshold_uncertainty_score":0.010569334},"labels":[],"label_agreement":null},{"id":"W3209464095","doi":"10.1007/978-3-030-81843-2_22","title":"Optimal Stopping in Continuous Time","year":2021,"lang":"en","type":"book-chapter","venue":"Springer finance","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematical proof; Computer science; Stopping time; Optimal stopping; Discrete time and continuous time; Subject (documents); Mathematical economics; Calculus (dental); Mathematics; Mathematical optimization; Statistics; World Wide Web","score_opus":0.016298567963908293,"score_gpt":0.2250894131726481,"score_spread":0.2087908452087398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3209464095","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0067170784,0.04332953,0.29360834,0.007186355,0.0026250929,0.000041828796,0.00031705943,0.00039182912,0.64578277],"genre_scores_gemma":[0.19972132,0.033651873,0.05657864,0.0018174218,0.0032501635,0.00018631422,0.00048500247,0.0009208199,0.70338845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996308,0.00010378922,0.000016673988,0.000056898927,0.0001523746,0.000039374638],"domain_scores_gemma":[0.9994456,0.00033879228,0.000042479383,0.000053473403,0.00006892015,0.00005066392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074092956,0.0010029094,0.0011589277,0.000733402,0.00045868,0.0025987334,0.0007576325,0.0019556996,0.018811643],"category_scores_gemma":[0.0023237173,0.0004885079,0.00048162398,0.0018331035,0.0014987141,0.002145931,0.0007196225,0.0029360794,0.0048119966],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023439698,0.000036557736,0.000060732003,0.00013627872,0.000014577835,0.00003247329,0.00005213831,0.012876948,0.00034190126,0.8635959,0.055422157,0.06740699],"study_design_scores_gemma":[0.000015826488,0.000022736998,0.00019085992,0.00010329934,0.000009380355,0.000044468936,0.000021928063,0.026115645,0.00020994373,0.88730705,0.08594587,0.000013031693],"about_ca_topic_score_codex":0.0011942384,"about_ca_topic_score_gemma":0.0011726108,"teacher_disagreement_score":0.018811643,"about_ca_system_score_codex":0.0016367752,"about_ca_system_score_gemma":0.0011265262,"threshold_uncertainty_score":0.06293124},"labels":[],"label_agreement":null},{"id":"W3211038545","doi":"10.1007/s10878-021-00827-w","title":"Bicriteria streaming algorithms to balance gain and cost with cardinality constraint","year":2021,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"National Natural Science Foundation of China","keywords":"Submodular set function; Cardinality (data modeling); Constraint (computer-aided design); Theory of computation; Monotone polygon; Function (biology); Mathematical optimization; Greedy algorithm; Competitive analysis; Computer science; Extension (predicate logic); Online algorithm; Mathematics; Enumeration; Algorithm; Discrete mathematics; Upper and lower bounds","score_opus":0.015028489032291308,"score_gpt":0.2669975924391859,"score_spread":0.2519691034068946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3211038545","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025671365,0.00087178353,0.96438825,0.0005420202,0.00016860709,0.00017134623,0.00021759034,0.0010161716,0.0069528846],"genre_scores_gemma":[0.36546522,0.00061758107,0.6215017,0.00055103144,0.00031795684,0.00050698104,0.00060294295,0.00052891125,0.0099076135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981635,0.0006948064,0.00010577652,0.0002929035,0.00048099775,0.00026208194],"domain_scores_gemma":[0.99310875,0.0042216494,0.00030387033,0.0012229215,0.0008543086,0.00028842446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030416385,0.0012043582,0.002345174,0.0013826749,0.00094225944,0.0017398256,0.003791162,0.0016262471,0.008028052],"category_scores_gemma":[0.013617153,0.00091623556,0.0006853617,0.003136675,0.0011153346,0.0037477005,0.002777378,0.002431868,0.0017762977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014211683,0.0006086562,0.0009830893,0.00028299086,0.00014278188,0.00010696613,0.00026179737,0.47417215,0.006286452,0.11357186,0.02482317,0.3773389],"study_design_scores_gemma":[0.00011377208,0.00010017378,0.00008084616,0.000020592966,0.000018865729,0.000063364714,0.000029803508,0.947864,0.0010651425,0.04888308,0.0017478815,0.000012502874],"about_ca_topic_score_codex":0.0024632742,"about_ca_topic_score_gemma":0.0057484126,"teacher_disagreement_score":0.008028052,"about_ca_system_score_codex":0.0013262521,"about_ca_system_score_gemma":0.002353253,"threshold_uncertainty_score":0.026856542},"labels":[],"label_agreement":null},{"id":"W3213789197","doi":"10.1142/s1793830922500306","title":"Optimal rendezvous on a line by location-aware robots in the presence of spies*","year":2021,"lang":"en","type":"article","venue":"Discrete Mathematics Algorithms and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Université du Québec en Outaouais; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rendezvous; Robot; Competitive analysis; Computer science; Mobile robot; Set (abstract data type); Bounded function; Task (project management); Line (geometry); Algorithm; Artificial intelligence; Mathematics; Upper and lower bounds; Engineering","score_opus":0.024908221509958816,"score_gpt":0.2950486309745702,"score_spread":0.2701404094646114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3213789197","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22085683,0.00066290173,0.767189,0.0004306034,0.00006954863,0.00021376365,0.00016346946,0.0019638527,0.008450042],"genre_scores_gemma":[0.78940356,0.00021699394,0.20505111,0.0000862507,0.000022435173,0.00013144639,0.00029947935,0.0001807183,0.004607963],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99886835,0.00019885715,0.00005320437,0.00034916698,0.00021017987,0.0003202731],"domain_scores_gemma":[0.9970396,0.0017452389,0.00034672886,0.0003956884,0.00023124827,0.00024145377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010214234,0.0013451544,0.0016639275,0.00080914306,0.0018566162,0.0012569095,0.0026104776,0.0018965969,0.0024147318],"category_scores_gemma":[0.0044223466,0.0005747799,0.0009494826,0.001008223,0.0020510938,0.0020253556,0.0021792557,0.0011225642,0.0005497804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008595042,0.00013379609,0.0012343655,0.00015701489,0.000096655865,0.00035075762,0.000421901,0.90841466,0.012666909,0.021974498,0.002198095,0.051491957],"study_design_scores_gemma":[0.000077737954,0.00014167352,0.00026469107,0.000011742633,0.000021458847,0.00017340698,0.00014065979,0.97882974,0.0063505205,0.012354098,0.0016068771,0.000027483426],"about_ca_topic_score_codex":0.0126946485,"about_ca_topic_score_gemma":0.00911046,"teacher_disagreement_score":0.0126946485,"about_ca_system_score_codex":0.0018673553,"about_ca_system_score_gemma":0.001527973,"threshold_uncertainty_score":0.025241554},"labels":[],"label_agreement":null},{"id":"W384563215","doi":"10.1007/s10878-015-9905-7","title":"The Canadian Tour Operator Problem on paths: tight bounds and resource augmentation","year":2015,"lang":"en","type":"article","venue":"Journal of Combinatorial Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Combinatorics; Travelling salesman problem; Vertex (graph theory); Operator (biology); Competitive analysis; Theory of computation; Mathematics; Graph; Path (computing); Computer science; Lin–Kernighan heuristic; Discrete mathematics; Bottleneck traveling salesman problem; Mathematical optimization; Upper and lower bounds; Algorithm","score_opus":0.018060388072599094,"score_gpt":0.25227332735515046,"score_spread":0.23421293928255135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W384563215","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13902313,0.006972745,0.60142547,0.015838519,0.0011105916,0.0013364556,0.008198463,0.0011555227,0.2249392],"genre_scores_gemma":[0.7044997,0.006831481,0.21858755,0.0017905617,0.0008138451,0.0010045741,0.004500021,0.0010886978,0.060883496],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962501,0.0010090143,0.00008688758,0.0005257145,0.00092101906,0.0012072255],"domain_scores_gemma":[0.98659235,0.009085083,0.0005147997,0.00090227247,0.0013434106,0.0015621562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033230598,0.0030460677,0.0035729462,0.002805399,0.0031995592,0.0063057058,0.006468719,0.0034174563,0.02932077],"category_scores_gemma":[0.02289609,0.0013339613,0.00179802,0.007998151,0.0038584797,0.010505674,0.0047223233,0.007362281,0.0014394438],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00073725934,0.00042445323,0.00093186536,0.0006035287,0.000106138206,0.00020308857,0.0003047328,0.5205485,0.0011866398,0.3782037,0.050652906,0.04609724],"study_design_scores_gemma":[0.00009594771,0.00010649573,0.00045619908,0.00013348935,0.00006889481,0.00011026193,0.00024881377,0.7255249,0.0005254506,0.261945,0.010730075,0.000054575077],"about_ca_topic_score_codex":0.13080469,"about_ca_topic_score_gemma":0.16988872,"teacher_disagreement_score":0.13080469,"about_ca_system_score_codex":0.011698879,"about_ca_system_score_gemma":0.01578891,"threshold_uncertainty_score":0.26008666},"labels":[],"label_agreement":null},{"id":"W4205186260","doi":"10.22215/etd/2020-14107","title":"Bike Assisted Linear Search and Evacuation","year":2020,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Computer science; Face (sociological concept); Search and rescue; Position (finance); Artificial intelligence; Operations research; Simulation; Engineering","score_opus":0.048388354112460216,"score_gpt":0.32639241694791205,"score_spread":0.2780040628354518,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205186260","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08284957,0.003631245,0.8597909,0.0015756565,0.00021670823,0.00009332006,0.00033333097,0.00044005737,0.051069215],"genre_scores_gemma":[0.82459414,0.0027664597,0.1084933,0.0003245911,0.00011825616,0.000235678,0.00038490933,0.000118828415,0.06296371],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996995,0.00010336862,0.000009556236,0.000063983185,0.000057156278,0.000066447916],"domain_scores_gemma":[0.99938405,0.00041239316,0.00006428699,0.000033108397,0.00006699353,0.00003912524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003198369,0.00064187846,0.0007842253,0.00039622924,0.0005253627,0.0007932754,0.00069744827,0.0013849846,0.0058690403],"category_scores_gemma":[0.001904361,0.00026893732,0.00048972754,0.000984572,0.00094719033,0.0013573439,0.0012596587,0.00093831186,0.0007141155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019283792,0.00006723529,0.00030222992,0.00024729755,0.000038302976,0.00007024245,0.00009777501,0.9079689,0.0011927042,0.04483956,0.0040737223,0.040909205],"study_design_scores_gemma":[0.000025903,0.00007161487,0.00021924915,0.000027557406,0.000008690288,0.000036921912,0.00007026515,0.9725126,0.00064196624,0.022901231,0.0034671933,0.000016851964],"about_ca_topic_score_codex":0.0053746887,"about_ca_topic_score_gemma":0.004146222,"teacher_disagreement_score":0.0058690403,"about_ca_system_score_codex":0.00088709296,"about_ca_system_score_gemma":0.00095890823,"threshold_uncertainty_score":0.01963389},"labels":[],"label_agreement":null},{"id":"W4206869873","doi":"","title":"A semidefiinite programming relaxation for Vertex Separator Problem","year":2014,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Separator (oil production); Computer science; Vertex (graph theory); Relaxation (psychology); Mathematical optimization; Mathematics; Theoretical computer science; Physics; Thermodynamics; Graph","score_opus":0.02454861409559402,"score_gpt":0.2585117703922431,"score_spread":0.23396315629664907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206869873","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017859472,0.0010761553,0.9453589,0.0020046968,0.00037814726,0.0001403703,0.0008232848,0.00021432778,0.03214472],"genre_scores_gemma":[0.22457415,0.0014750035,0.73632765,0.0013016713,0.0005886419,0.00077495637,0.0021244409,0.0006330314,0.03220038],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990207,0.00040586898,0.000035126486,0.00019881275,0.00023545967,0.00010402009],"domain_scores_gemma":[0.9972156,0.002004952,0.00015121065,0.00017315567,0.00024803524,0.00020704306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020709676,0.0016605218,0.0013717166,0.00088087015,0.0005824313,0.002111153,0.0023718015,0.0022726462,0.0117677795],"category_scores_gemma":[0.0067817243,0.0008788401,0.0013633247,0.0013913554,0.0013009438,0.0024251102,0.0022217573,0.0063143163,0.0011897106],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004082249,0.00030324812,0.00037917963,0.0009191949,0.00007221373,0.00027228246,0.00026745224,0.62700725,0.0042458656,0.26034674,0.02666504,0.079113305],"study_design_scores_gemma":[0.00006695812,0.000098022916,0.00012720544,0.00010493783,0.000017819732,0.00009223404,0.000058949227,0.85071594,0.0006775127,0.13870502,0.009316961,0.0000183485],"about_ca_topic_score_codex":0.0029597906,"about_ca_topic_score_gemma":0.0025204231,"teacher_disagreement_score":0.0117677795,"about_ca_system_score_codex":0.0014602474,"about_ca_system_score_gemma":0.0013293567,"threshold_uncertainty_score":0.03936714},"labels":[],"label_agreement":null},{"id":"W4211029969","doi":"10.1007/978-3-030-11072-7_18","title":"Dangerous Graphs","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; TRACE (psycholinguistics); Process (computing); Computer security; Node (physics); Computer network","score_opus":0.0199495572327793,"score_gpt":0.24972878476151233,"score_spread":0.22977922752873303,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211029969","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021773709,0.0014170737,0.09372518,0.003168953,0.0013381131,0.00007650154,0.00093238853,0.0008337827,0.8767343],"genre_scores_gemma":[0.36553133,0.0034275649,0.04108549,0.0023805632,0.0009603817,0.00020180488,0.0029958112,0.0014829563,0.58193415],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99967694,0.00006483387,0.000009370111,0.00007748831,0.00012469449,0.000046702004],"domain_scores_gemma":[0.99937445,0.00018432178,0.000047981557,0.00014976197,0.00012994221,0.00011353721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022695962,0.00067451986,0.0004337092,0.0016006121,0.0017608075,0.0019752316,0.00076673686,0.00097505876,0.041959736],"category_scores_gemma":[0.001478378,0.0003579833,0.00049002573,0.0009673633,0.001412573,0.0028886222,0.0017049253,0.002446974,0.008518811],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00000859515,0.0000053164545,0.000043584383,0.000027027854,0.000002713611,0.00004076747,0.00006937559,0.000336455,0.00027437584,0.9734935,0.017368583,0.00832974],"study_design_scores_gemma":[0.0000027643036,0.0000038694984,0.000047469282,0.000015005147,0.0000041942403,0.00011969316,0.000052483912,0.00095266395,0.00026920048,0.93881977,0.059708904,0.000004002943],"about_ca_topic_score_codex":0.0008807334,"about_ca_topic_score_gemma":0.0011829783,"teacher_disagreement_score":0.041959736,"about_ca_system_score_codex":0.00075712305,"about_ca_system_score_gemma":0.0004964936,"threshold_uncertainty_score":0.1403693},"labels":[],"label_agreement":null},{"id":"W4211103781","doi":"10.2200/s00440ed1v01y201208dct010","title":"Distributed Computing by Oblivious Mobile Robots","year":2012,"lang":"en","type":"article","venue":"Synthesis lectures on distributed computing theory","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":99,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dell’Istruzione, dell’Università e della Ricerca","keywords":"Computer science; Mobile robot; Robotics; Robot; Artificial intelligence; Distributed computing; Human–computer interaction","score_opus":0.011187250422149997,"score_gpt":0.2538542189076905,"score_spread":0.2426669684855405,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211103781","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.027795807,0.0020997464,0.94102275,0.0023318813,0.0006051685,0.0000754005,0.00007616891,0.00071106426,0.025282044],"genre_scores_gemma":[0.76963145,0.0026826416,0.17179026,0.00049362134,0.0005843471,0.00039975857,0.00012656563,0.00027677952,0.05401454],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99951196,0.000133951,0.000019244782,0.0001019587,0.00017085,0.00006193197],"domain_scores_gemma":[0.9990976,0.0005169279,0.00005024055,0.00021362427,0.00007296633,0.000048618804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006125467,0.0006789348,0.00080876035,0.00037461738,0.00064708735,0.0012801589,0.000847779,0.0006695147,0.004134455],"category_scores_gemma":[0.002844213,0.00043481783,0.00038317306,0.0007450294,0.001409477,0.001988391,0.0015654073,0.0021284411,0.00079040544],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002486165,0.000052776417,0.00022779581,0.00023469733,0.00005118892,0.000061477214,0.0001941824,0.17440957,0.007812948,0.71736795,0.0110614635,0.08827731],"study_design_scores_gemma":[0.00010599329,0.000079679216,0.00019004647,0.00004155716,0.000031874224,0.0000632396,0.000042834472,0.42090115,0.0051383846,0.5459264,0.027458336,0.000020509287],"about_ca_topic_score_codex":0.0005825362,"about_ca_topic_score_gemma":0.00065158453,"teacher_disagreement_score":0.004134455,"about_ca_system_score_codex":0.0011834538,"about_ca_system_score_gemma":0.0006785732,"threshold_uncertainty_score":0.013831079},"labels":[],"label_agreement":null},{"id":"W4212937252","doi":"10.1080/0952813x.2021.1960630","title":"HLA: a novel hybrid model based on fixed structure and variable structure learning automata","year":2022,"lang":"en","type":"article","venue":"Journal of Experimental & Theoretical Artificial Intelligence","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Learning automata; Variable (mathematics); Dropout (neural networks); Convergence (economics); Automaton; Artificial intelligence; Artificial neural network; Margin (machine learning); Stability (learning theory); Machine learning; Mathematics","score_opus":0.022573203067814802,"score_gpt":0.2877095505486438,"score_spread":0.265136347480829,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4212937252","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037641186,0.00048518126,0.9549971,0.0004644265,0.00013568881,0.0000668177,0.0001834216,0.00087289914,0.005153227],"genre_scores_gemma":[0.93452567,0.00033153803,0.057345312,0.00016237613,0.00004339002,0.00023783038,0.00013513624,0.000048164195,0.0071706492],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996234,0.00007861082,0.000028215518,0.000117619835,0.0000891651,0.00006290239],"domain_scores_gemma":[0.9994411,0.00024166654,0.00008297849,0.00005639366,0.00012714739,0.000050822517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005850164,0.00049511925,0.0008763507,0.0004783344,0.00040118108,0.0011050865,0.0019042143,0.0011503061,0.003256962],"category_scores_gemma":[0.0013973576,0.00034414328,0.0007964916,0.0004029342,0.00094767497,0.0016630238,0.0011087523,0.0011892244,0.0003981121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009798149,0.00004742388,0.001176704,0.000084004605,0.00005562038,0.00013212416,0.000089455454,0.9314929,0.0032697006,0.03163677,0.0009665866,0.030950667],"study_design_scores_gemma":[0.000009465904,0.000036572546,0.00006972791,0.00000413297,0.000008635258,0.000018701014,0.000003859853,0.9952636,0.00023586668,0.0039005417,0.00044414063,0.000004748747],"about_ca_topic_score_codex":0.004781304,"about_ca_topic_score_gemma":0.003500024,"teacher_disagreement_score":0.004781304,"about_ca_system_score_codex":0.0007598179,"about_ca_system_score_gemma":0.0010883036,"threshold_uncertainty_score":0.010895669},"labels":[],"label_agreement":null},{"id":"W4213412735","doi":"10.1182/blood.2021014936","title":"Clearing NETs with T-series resolvins","year":2021,"lang":"en","type":"letter","venue":"Blood","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Clearing; Series (stratigraphy); Computer science; Biology; Business","score_opus":0.020455928698242663,"score_gpt":0.21445348321539798,"score_spread":0.1939975545171553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4213412735","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0078055123,0.0030564496,0.28209013,0.2357498,0.009979579,0.00016508123,0.0005740101,0.0013830048,0.4591965],"genre_scores_gemma":[0.36363217,0.0036971022,0.13374801,0.05318652,0.008683528,0.0005428356,0.0004750565,0.0009382025,0.43509662],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985227,0.00058113335,0.000074148,0.00016409402,0.0005109613,0.0001469642],"domain_scores_gemma":[0.9941705,0.0041700886,0.00016870908,0.0007817145,0.00050300464,0.00020593462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028372353,0.0005442,0.00082488643,0.000792308,0.0022859918,0.0056137433,0.0014868907,0.0067245406,0.028616136],"category_scores_gemma":[0.020884361,0.00047260206,0.00078231975,0.00093677134,0.0036478806,0.0073794913,0.0018877229,0.0072560967,0.005712309],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060358318,0.000013378575,0.0000408077,0.000031184773,0.0000042976762,0.00006794628,0.000033296114,0.002895455,0.00008674333,0.87636375,0.097957656,0.022445222],"study_design_scores_gemma":[0.000038301332,0.000009068726,0.000019770929,0.000028518944,0.0000031005547,0.00005520586,0.000022380378,0.014717871,0.00038941705,0.9034222,0.08128562,0.000008512685],"about_ca_topic_score_codex":0.0031982437,"about_ca_topic_score_gemma":0.0045952573,"teacher_disagreement_score":0.028616136,"about_ca_system_score_codex":0.0028453425,"about_ca_system_score_gemma":0.0025522779,"threshold_uncertainty_score":0.09573048},"labels":[],"label_agreement":null},{"id":"W4214735731","doi":"10.1145/3410048.3410055","title":"Mechanism Design for Online Resource Allocation","year":2020,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Knapsack problem; Competitive analysis; Computer science; Valuation (finance); Payment; Incentive compatibility; Mechanism design; Resource allocation; Incentive; Function (biology); Resource (disambiguation); Mathematical optimization; Online algorithm; Allocative efficiency; Operations research; Microeconomics; Business; Economics; Mathematics","score_opus":0.24251252593777176,"score_gpt":0.37313752467782335,"score_spread":0.1306249987400516,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214735731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032172913,0.0009849321,0.98798776,0.00052469247,0.000117760916,0.0002396723,0.00008540743,0.00021995329,0.006622533],"genre_scores_gemma":[0.48601192,0.0030380778,0.49545106,0.0010475197,0.0005379821,0.002419777,0.0003261855,0.00018323027,0.010984118],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.988536,0.006959621,0.0005561474,0.0014838993,0.0016399567,0.000824442],"domain_scores_gemma":[0.9873668,0.009246275,0.0010735107,0.0011884567,0.0007650314,0.0003599746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0110606225,0.0021642188,0.0029451908,0.0014486208,0.0010945972,0.0044569084,0.0047058635,0.0037666287,0.008476414],"category_scores_gemma":[0.02009818,0.001396804,0.0019235617,0.002651615,0.0027014986,0.0065224404,0.0029903813,0.0040495736,0.0015196444],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001651973,0.00022091529,0.00026210598,0.00067649607,0.00017133121,0.00018115435,0.00013090296,0.252552,0.0017248132,0.69286555,0.0043992824,0.046650194],"study_design_scores_gemma":[0.00015766594,0.00015462039,0.000077792145,0.00008087506,0.000057024783,0.00016860184,0.00003925151,0.6014552,0.0008481334,0.3876946,0.00922719,0.000039048326],"about_ca_topic_score_codex":0.0009894331,"about_ca_topic_score_gemma":0.00081604614,"teacher_disagreement_score":0.0110606225,"about_ca_system_score_codex":0.0031405615,"about_ca_system_score_gemma":0.003717586,"threshold_uncertainty_score":0.058494866},"labels":[],"label_agreement":null},{"id":"W4221140790","doi":"10.4230/lipics.fsttcs.2021.9","title":"Approximation Algorithms for Flexible Graph Connectivity","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University of Virginia; National Science Foundation","keywords":"Approximation algorithm; Combinatorics; Mathematics; Partition (number theory); Graph; Undirected graph; Efficient algorithm; Algorithm; Discrete mathematics","score_opus":0.1280277299512267,"score_gpt":0.22609555582565563,"score_spread":0.09806782587442894,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4221140790","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022400972,0.00181845,0.9601056,0.0016411392,0.00015777646,0.00016430332,0.0007081041,0.0014639951,0.011539629],"genre_scores_gemma":[0.37239993,0.0020088076,0.61331826,0.00083382276,0.00028941012,0.0005764226,0.0029308272,0.00056290923,0.0070796194],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99779934,0.00052781584,0.0001016575,0.0005789533,0.00059638097,0.0003958166],"domain_scores_gemma":[0.99507916,0.0029552495,0.00042919556,0.000985631,0.00036633643,0.00018444107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017352708,0.0019238675,0.0017108172,0.0018187732,0.0010417561,0.0024462452,0.003833414,0.0026311257,0.008223356],"category_scores_gemma":[0.012581868,0.0008378772,0.0021526816,0.0040166634,0.0012401928,0.0058330465,0.0027684316,0.0035540995,0.0014376992],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035206854,0.00022329368,0.0012346669,0.00033731712,0.00014859239,0.00014873217,0.00022922615,0.73377955,0.0011990346,0.11001579,0.01925365,0.13307808],"study_design_scores_gemma":[0.000068208574,0.000045376644,0.00015363228,0.000030788142,0.000030746887,0.00010080814,0.000053396438,0.86442,0.000335989,0.1305428,0.004205943,0.000012311328],"about_ca_topic_score_codex":0.004958863,"about_ca_topic_score_gemma":0.0057902187,"teacher_disagreement_score":0.008223356,"about_ca_system_score_codex":0.0031755585,"about_ca_system_score_gemma":0.0015548348,"threshold_uncertainty_score":0.027509868},"labels":[],"label_agreement":null},{"id":"W4225425583","doi":"10.32473/flairs.v35i.130850","title":"Learning Automata with Artificial Reflecting Barriers in Games with Limited Information","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Nash equilibrium; Computer science; Game theory; Reinforcement learning; Fictitious play; Complete information; Perfect information; Learning automata; Mathematical economics; Point (geometry); Saddle point; Artificial intelligence; Automaton; Mathematics","score_opus":0.09331720338213315,"score_gpt":0.3458034193125344,"score_spread":0.2524862159304012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225425583","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11383645,0.00063873536,0.86892176,0.001058545,0.00012949623,0.00011987767,0.00013012375,0.00048443693,0.014680556],"genre_scores_gemma":[0.9169835,0.00043069173,0.075326554,0.00025309282,0.00006560826,0.00033409032,0.00009657834,0.00005764624,0.0064522666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988172,0.00046128398,0.00009432201,0.00027338671,0.00022710531,0.00012677534],"domain_scores_gemma":[0.9963858,0.002443114,0.0004751935,0.00022302137,0.00022594401,0.000246962],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010663372,0.0006685991,0.0010708016,0.0006229152,0.0008101167,0.0021090684,0.0013156878,0.0017218229,0.0024756053],"category_scores_gemma":[0.006023262,0.00048067558,0.0010286464,0.0003936707,0.0027550284,0.0029382717,0.0028465295,0.0018943758,0.00039156817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009874105,0.00005709088,0.0007975719,0.00011754991,0.000046785775,0.00031730713,0.00036700384,0.5541387,0.0033352324,0.4303939,0.0005445653,0.009785537],"study_design_scores_gemma":[0.000024709345,0.00004416703,0.00007292838,0.000013500805,0.000012524391,0.000038363836,0.000025764319,0.91331744,0.0005245595,0.08488359,0.0010264899,0.000016013288],"about_ca_topic_score_codex":0.0021702875,"about_ca_topic_score_gemma":0.0016221352,"teacher_disagreement_score":0.0024756053,"about_ca_system_score_codex":0.0011387347,"about_ca_system_score_gemma":0.0010456463,"threshold_uncertainty_score":0.008281767},"labels":[],"label_agreement":null},{"id":"W4225983316","doi":"10.1007/978-3-030-99826-4_17","title":"A K-Means Clustering Approach to Segmentation of Maps for Task Allocation in Multi-robot Systems Exploration of Unknown Environments","year":2022,"lang":"en","type":"book-chapter","venue":"Mechanisms and machine science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Cluster analysis; Task (project management); Robot; Computer science; Segmentation; Artificial intelligence; Computer vision; Engineering; Systems engineering","score_opus":0.062276374658030466,"score_gpt":0.2708583085654845,"score_spread":0.20858193390745403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225983316","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00089696614,0.00037033905,0.996309,0.000057814068,0.000068652495,0.000038985738,0.000104722996,0.0006626295,0.0014908632],"genre_scores_gemma":[0.024372183,0.000580068,0.96819276,0.00007519337,0.000062082436,0.00014124907,0.00044029637,0.0005592725,0.005576834],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992182,0.00014115711,0.000050712424,0.00022113258,0.00029165985,0.00007697471],"domain_scores_gemma":[0.99936074,0.00020958275,0.00003306254,0.00010712262,0.0002606119,0.000028803164],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007205032,0.001349582,0.0017694648,0.0019061909,0.0015788368,0.0020343184,0.0033994755,0.0020653857,0.0062344754],"category_scores_gemma":[0.0021325336,0.0010912826,0.0021295373,0.0045956583,0.0010948527,0.0016339009,0.001430502,0.0020055615,0.0032352759],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010586493,0.000082511404,0.0002914643,0.00036849777,0.00015401524,0.00007665178,0.00033764183,0.45415574,0.0107381325,0.03304023,0.019958839,0.4806904],"study_design_scores_gemma":[0.0000065596537,0.000024089277,0.00030156126,0.000030618383,0.000021486545,0.000075495074,0.00006426343,0.9576998,0.0033569545,0.029007932,0.009371343,0.000039990875],"about_ca_topic_score_codex":0.02657001,"about_ca_topic_score_gemma":0.029115394,"teacher_disagreement_score":0.02657001,"about_ca_system_score_codex":0.0017181948,"about_ca_system_score_gemma":0.002063519,"threshold_uncertainty_score":0.052830756},"labels":[],"label_agreement":null},{"id":"W4226066396","doi":"10.1093/sysbio/syac028","title":"A Linear Time Solution to the Labeled Robinson–Foulds Distance Problem","year":2022,"lang":"en","type":"article","venue":"Systematic Biology","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Biology; Mathematics","score_opus":0.016788876269763293,"score_gpt":0.2589924925464515,"score_spread":0.2422036162766882,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226066396","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015836837,0.0010389483,0.9621889,0.0021974628,0.00046649014,0.00043797333,0.0015161387,0.0026924904,0.0136248395],"genre_scores_gemma":[0.08501105,0.00044739456,0.9002318,0.00060050964,0.0002819451,0.0005230747,0.0037617122,0.00062801986,0.008514452],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99737823,0.0005250154,0.00016739072,0.0009926263,0.0005679099,0.00036893436],"domain_scores_gemma":[0.9960963,0.0025370114,0.00021843518,0.00050913735,0.0003941277,0.00024494674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018991153,0.0024448598,0.0029018358,0.0013861503,0.0014832937,0.0029715088,0.004254288,0.0039429283,0.022774098],"category_scores_gemma":[0.00905692,0.0008686301,0.0022306142,0.0025627727,0.0012070197,0.005197722,0.003568969,0.004230434,0.005876997],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084063463,0.0005754562,0.0010624774,0.0014949463,0.00017346401,0.00034729645,0.00043453355,0.26338696,0.007278907,0.1057017,0.092912324,0.5257912],"study_design_scores_gemma":[0.00035775476,0.00020082948,0.00043556924,0.00008126169,0.00004475431,0.00034610854,0.00025763735,0.79167455,0.0019187202,0.18953252,0.015095401,0.00005495474],"about_ca_topic_score_codex":0.0044767046,"about_ca_topic_score_gemma":0.006507715,"teacher_disagreement_score":0.022774098,"about_ca_system_score_codex":0.0020044746,"about_ca_system_score_gemma":0.0037431153,"threshold_uncertainty_score":0.076186955},"labels":[],"label_agreement":null},{"id":"W4226474270","doi":"10.1007/978-3-030-96731-4_18","title":"Machine Learning Advised Ski Rental Problem with a Discount","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Oracle; Online machine learning; Online algorithm; Context (archaeology); Online learning; Renting; Algorithm; Active learning (machine learning)","score_opus":0.011572906254450168,"score_gpt":0.23349785847203353,"score_spread":0.22192495221758335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4226474270","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.162451,0.0016783339,0.7353271,0.009070391,0.0009066798,0.0003511791,0.0026194549,0.0013309402,0.086264856],"genre_scores_gemma":[0.784809,0.0006765988,0.103860274,0.0004809275,0.0005082958,0.00018221719,0.0015758316,0.00043656686,0.10747032],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991467,0.00023162163,0.000049986276,0.0002497429,0.00014530968,0.00017655495],"domain_scores_gemma":[0.9978167,0.0013401669,0.00010920717,0.00033007283,0.00016879772,0.00023512542],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016607945,0.0007659467,0.0023924285,0.0006436694,0.00091496314,0.002306298,0.0026373875,0.0035271219,0.02527562],"category_scores_gemma":[0.0069791954,0.00064604107,0.0010951859,0.001075469,0.0016604933,0.005479483,0.0020328872,0.0035027943,0.0024601303],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096578366,0.00047838583,0.0017308308,0.00041259892,0.00010952757,0.00045311154,0.00020339018,0.3304978,0.001121851,0.46310386,0.06849841,0.13242447],"study_design_scores_gemma":[0.00008399258,0.00006365502,0.00025318467,0.00004379454,0.000023812107,0.000093503215,0.000058835343,0.73658824,0.00049398665,0.2558825,0.00639212,0.000022427463],"about_ca_topic_score_codex":0.0039087,"about_ca_topic_score_gemma":0.0040118992,"teacher_disagreement_score":0.02527562,"about_ca_system_score_codex":0.0016148445,"about_ca_system_score_gemma":0.0018455576,"threshold_uncertainty_score":0.08455539},"labels":[],"label_agreement":null},{"id":"W4229801721","doi":"10.22215/etd/2005-10780","title":"Intruder capture by mobile agents in mesh topologies","year":2005,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Network topology; Computer science; Computer network; Topology (electrical circuits); Electrical engineering; Engineering","score_opus":0.018066465929945815,"score_gpt":0.31253940747510495,"score_spread":0.29447294154515913,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229801721","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46316603,0.0008969236,0.51890886,0.00051430124,0.00013326178,0.00009166978,0.00013750796,0.00036328475,0.015788235],"genre_scores_gemma":[0.9630873,0.00061680004,0.026467957,0.000051760293,0.000040657895,0.000040959745,0.00011803007,0.00003332202,0.009543241],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969685,0.0000738939,0.0000133619205,0.00006266235,0.00008672099,0.000066516586],"domain_scores_gemma":[0.9987691,0.00062292465,0.0002253675,0.00014097532,0.00011915911,0.00012240428],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041577648,0.00042632513,0.0005083108,0.00076311955,0.0004303384,0.0010054872,0.00068485667,0.00077424024,0.0028468245],"category_scores_gemma":[0.0032379758,0.0003489203,0.0004713064,0.00043222625,0.00042663308,0.0016187847,0.0013704716,0.00041960512,0.00059836963],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00091643014,0.00016257571,0.010672272,0.00023843291,0.00017575324,0.0014440084,0.00054062443,0.7582259,0.041743513,0.04000337,0.004015904,0.14186126],"study_design_scores_gemma":[0.000031424188,0.00019538491,0.002050066,0.00002449184,0.000036811165,0.00036753443,0.0003000776,0.97177833,0.00721641,0.015624296,0.0023607453,0.000014409494],"about_ca_topic_score_codex":0.0011535786,"about_ca_topic_score_gemma":0.0011977489,"teacher_disagreement_score":0.0028468245,"about_ca_system_score_codex":0.00033380312,"about_ca_system_score_gemma":0.00018875622,"threshold_uncertainty_score":0.00952363},"labels":[],"label_agreement":null},{"id":"W4230517044","doi":"10.1007/978-3-030-11072-7_4","title":"Gathering","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Robot; Focus (optics); Visibility; Convergence (economics); Point (geometry); Plane (geometry); Theoretical computer science; Artificial intelligence; Algorithm; Mathematics; Geometry; Physics","score_opus":0.021054986344928115,"score_gpt":0.25062823023311026,"score_spread":0.22957324388818215,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230517044","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005579589,0.0006849333,0.057837483,0.0015446269,0.001121017,0.00140858,0.014207606,0.0079189455,0.9096972],"genre_scores_gemma":[0.034724906,0.0012493823,0.040388647,0.0010083552,0.00046155235,0.00087378087,0.028410548,0.0026536945,0.89022917],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913365,0.00012324903,0.000041638483,0.00021537386,0.0003357747,0.00015029826],"domain_scores_gemma":[0.9984945,0.00021634717,0.00006644824,0.0005902902,0.00048008625,0.00015243802],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007842948,0.0014526643,0.00078181224,0.0036763984,0.0023831315,0.0028077385,0.0014192023,0.0008822284,0.38019824],"category_scores_gemma":[0.0031196347,0.00057734974,0.0008881909,0.002999883,0.0005136994,0.0030152146,0.004141698,0.0015525543,0.22391464],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031009136,0.00016126712,0.00056636793,0.0005828192,0.000021453634,0.0002151185,0.00059408846,0.0009223096,0.006476905,0.057627834,0.58476764,0.34775403],"study_design_scores_gemma":[0.000024629511,0.000072895535,0.00056152424,0.00014012083,0.000018845565,0.00019849732,0.00029875257,0.0009873216,0.0035181537,0.01732588,0.9768346,0.000018668206],"about_ca_topic_score_codex":0.0017585058,"about_ca_topic_score_gemma":0.0032360905,"teacher_disagreement_score":0.38019824,"about_ca_system_score_codex":0.0007569805,"about_ca_system_score_gemma":0.0014993673,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4230892244","doi":"10.32920/ryerson.14655639.v1","title":"Scatter Search on a Disk","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Robot; Upper and lower bounds; Carry (investment); Unit disk; Object (grammar); Computer science; Combinatorics; Artificial intelligence; Mathematics","score_opus":0.048902244932385895,"score_gpt":0.30631048598973365,"score_spread":0.2574082410573478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4230892244","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44641173,0.0022490653,0.5259217,0.0012912217,0.00011052934,0.00009621656,0.00052898267,0.00067223585,0.022718374],"genre_scores_gemma":[0.89609194,0.00052503,0.091020584,0.00019147148,0.00004497315,0.000089914174,0.00047171678,0.000110664376,0.011453752],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960166,0.000099643396,0.000020645852,0.00010459441,0.00007574342,0.000097756194],"domain_scores_gemma":[0.99866295,0.00079284405,0.00011773184,0.00017173572,0.0001426845,0.00011204093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004540867,0.00047615173,0.0010973216,0.0007850085,0.0010100208,0.001247403,0.0009258523,0.0013934604,0.005577735],"category_scores_gemma":[0.003334537,0.0004007154,0.00039849884,0.0013153307,0.0006908374,0.0022427528,0.0016252022,0.00059921335,0.0010648095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090682914,0.00013148294,0.0022828467,0.00024805524,0.00006886957,0.0005304167,0.0003228697,0.87778115,0.008310156,0.055066515,0.0077559194,0.046594918],"study_design_scores_gemma":[0.000060240698,0.00006635445,0.00029762398,0.000014843242,0.000007860815,0.0001326004,0.00011506907,0.9729969,0.001351822,0.022633614,0.0023137382,0.000009394902],"about_ca_topic_score_codex":0.0053495597,"about_ca_topic_score_gemma":0.0034083757,"teacher_disagreement_score":0.005577735,"about_ca_system_score_codex":0.00102065,"about_ca_system_score_gemma":0.0007243997,"threshold_uncertainty_score":0.018659413},"labels":[],"label_agreement":null},{"id":"W4232099961","doi":"10.1007/978-1-4939-2864-4_13","title":"Alternative Performance Measures in Online Algorithms","year":2016,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Algorithm","score_opus":0.026556741903097224,"score_gpt":0.26092038490884345,"score_spread":0.23436364300574622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4232099961","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009093663,0.036076326,0.9010896,0.0030265818,0.0014033797,0.00007177229,0.00026228587,0.00042825693,0.04854812],"genre_scores_gemma":[0.5094396,0.031803984,0.41774702,0.0015433182,0.007904947,0.0006331153,0.0008588208,0.0010214743,0.02904773],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.98492485,0.009127934,0.000605144,0.0012495872,0.0034506253,0.0006418866],"domain_scores_gemma":[0.9618272,0.030767547,0.0014030442,0.002887496,0.0025746515,0.00054003054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012232773,0.0029841794,0.0027377869,0.004292773,0.00091223855,0.007097766,0.0036554572,0.0038829397,0.009084582],"category_scores_gemma":[0.04692836,0.0005872068,0.0012098547,0.008543062,0.0050178324,0.012860007,0.0031026055,0.0054156487,0.0023870175],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010606127,0.00008288002,0.00030570198,0.00037766114,0.000051475603,0.000024609015,0.00008287258,0.0278213,0.0002883105,0.8646908,0.0071436623,0.09902464],"study_design_scores_gemma":[0.000017829827,0.00008791512,0.0003197374,0.00020189368,0.00003538453,0.00006202141,0.000057432408,0.12203574,0.00050086173,0.8675527,0.009096852,0.00003173186],"about_ca_topic_score_codex":0.00063624,"about_ca_topic_score_gemma":0.00038227206,"teacher_disagreement_score":0.012232773,"about_ca_system_score_codex":0.0034545083,"about_ca_system_score_gemma":0.0013191748,"threshold_uncertainty_score":0.06469381},"labels":[],"label_agreement":null},{"id":"W4233380038","doi":"10.2139/ssrn.1991202","title":"A Markov Switching Approach to Herding","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; Balsillie School of International Affairs","funders":"","keywords":"Herding; Markov chain; Business; Computer science; Mathematics; Statistics; Geography","score_opus":0.014750449262290721,"score_gpt":0.25488388603816997,"score_spread":0.24013343677587926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233380038","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043025315,0.0013741986,0.9366205,0.0025641036,0.00032154578,0.00007566515,0.00043056355,0.00028026415,0.015307912],"genre_scores_gemma":[0.8445491,0.0031458999,0.10314261,0.0007032232,0.00091955956,0.00035969607,0.00059588597,0.00023493702,0.04634911],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987482,0.0006306331,0.000056985526,0.00021434305,0.0001749412,0.00017487582],"domain_scores_gemma":[0.9917459,0.006608417,0.00050943455,0.00038416768,0.00042251716,0.00032954785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026846973,0.00076895615,0.002570439,0.0021648472,0.0013005617,0.0024857349,0.0042198715,0.0037113326,0.012517253],"category_scores_gemma":[0.011662927,0.001259032,0.0021889992,0.0020543584,0.0026004605,0.004434881,0.0020685703,0.003169481,0.00083834596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005156746,0.0000747213,0.0010522876,0.000090748814,0.00011247159,0.00015620288,0.00015276791,0.30849376,0.00033706857,0.67615,0.003180282,0.010148092],"study_design_scores_gemma":[0.00002036952,0.0000174596,0.00020572997,0.000011993848,0.000024276462,0.000029762614,0.000025508809,0.7880389,0.000031417214,0.21088903,0.0006878954,0.000017694141],"about_ca_topic_score_codex":0.01471196,"about_ca_topic_score_gemma":0.011863222,"teacher_disagreement_score":0.01471196,"about_ca_system_score_codex":0.00246824,"about_ca_system_score_gemma":0.0015627266,"threshold_uncertainty_score":0.04187435},"labels":[],"label_agreement":null},{"id":"W4233810285","doi":"10.1007/978-3-540-69052-8_37","title":"A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Web Polling","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Polling; Computer science; Knapsack problem; Learning automata; Resource allocation; Automaton; Hierarchy; Convergence (economics); Theoretical computer science; Algorithm; Computer network","score_opus":0.02209309194474442,"score_gpt":0.26533987824354915,"score_spread":0.24324678629880472,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233810285","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10632188,0.00061451306,0.86489797,0.00049248186,0.00021288083,0.00019665422,0.00050484994,0.0064614043,0.020297362],"genre_scores_gemma":[0.62985003,0.000252544,0.36197755,0.00025943786,0.00007883973,0.00037525772,0.00052197196,0.00034277164,0.006341628],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987513,0.00028034585,0.00017791372,0.00028726048,0.00025464655,0.0002486094],"domain_scores_gemma":[0.9950723,0.0021735774,0.0002460179,0.0014401847,0.00064755796,0.00042030643],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010012902,0.0006708519,0.0016748218,0.0009502604,0.0016914126,0.003468346,0.0027411256,0.0017997418,0.011286361],"category_scores_gemma":[0.005497238,0.00094455207,0.0009889209,0.0010383575,0.0013388533,0.0027176375,0.0028786615,0.002334323,0.0018011155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010475476,0.0005939713,0.0023612385,0.00070082425,0.00012785142,0.0005581767,0.0007541849,0.16684555,0.047568254,0.5667641,0.009505289,0.20317297],"study_design_scores_gemma":[0.00008573505,0.00009570449,0.0002474083,0.000047977017,0.00006241029,0.00015655569,0.00007603097,0.7853175,0.006227593,0.204151,0.0034819362,0.000050112798],"about_ca_topic_score_codex":0.0021604442,"about_ca_topic_score_gemma":0.0035682197,"teacher_disagreement_score":0.011286361,"about_ca_system_score_codex":0.0012790163,"about_ca_system_score_gemma":0.0018317166,"threshold_uncertainty_score":0.03775662},"labels":[],"label_agreement":null},{"id":"W4233877251","doi":"10.1109/dac.2014.6881419","title":"A cost efficient online algorithm for automotive idling reduction","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Robustness (evolution); Automotive industry; Reduction (mathematics); Competitive analysis; Computer science; Running time; Cost reduction; Algorithm; Mathematics; Engineering; Upper and lower bounds","score_opus":0.038916290497158425,"score_gpt":0.30943502974765885,"score_spread":0.2705187392505004,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233877251","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017278684,0.00033155415,0.9738226,0.0004078946,0.00009512584,0.00021188968,0.00019708107,0.002517923,0.0051371264],"genre_scores_gemma":[0.3808165,0.00021496553,0.61119294,0.0003777614,0.00013134153,0.0005387386,0.00078289554,0.00038202942,0.0055628307],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99836963,0.00032974215,0.000075901546,0.0004874577,0.00042273078,0.00031453118],"domain_scores_gemma":[0.9976528,0.0013172061,0.00020905524,0.00043355525,0.00025739236,0.00013002714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014309408,0.0015086778,0.0021961345,0.0011467083,0.0009489449,0.0012035833,0.0032362584,0.0018947338,0.005415312],"category_scores_gemma":[0.0044508385,0.000620226,0.0012236428,0.001654933,0.0010783395,0.0019233685,0.0023100278,0.0019053282,0.0014750452],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036153797,0.00040283136,0.0009503554,0.00023113364,0.00007788734,0.00010009252,0.0000976723,0.664594,0.0032021804,0.023937535,0.010308221,0.2957366],"study_design_scores_gemma":[0.000076309465,0.000069128946,0.00015276668,0.0000074497448,0.000013832607,0.00004883056,0.000018250981,0.98432505,0.0008589332,0.013159531,0.0012570116,0.000012991235],"about_ca_topic_score_codex":0.006185977,"about_ca_topic_score_gemma":0.0063889017,"teacher_disagreement_score":0.006185977,"about_ca_system_score_codex":0.0017535791,"about_ca_system_score_gemma":0.0044758823,"threshold_uncertainty_score":0.018116057},"labels":[],"label_agreement":null},{"id":"W4234150660","doi":"10.1007/978-3-642-21827-9_53","title":"The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Learning automata; Computer science; Prior probability; Bayesian probability; Estimator; Conjugate prior; Artificial intelligence; Algorithm; Machine learning; Mathematical optimization; Automaton; Mathematics; Statistics","score_opus":0.02299867247613641,"score_gpt":0.253557143766679,"score_spread":0.23055847129054258,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4234150660","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00054802344,0.00025088785,0.99836105,0.00005997044,0.000033673237,0.0000124899225,0.000024595489,0.00018120215,0.0005280583],"genre_scores_gemma":[0.038956128,0.0010548944,0.955866,0.00018969529,0.00018159083,0.0002455729,0.00014440481,0.0003317637,0.0030300447],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99713254,0.001031716,0.00020008835,0.0005773054,0.00095365196,0.000104704864],"domain_scores_gemma":[0.99394953,0.0038137508,0.00029705555,0.0008675381,0.0009136894,0.0001584461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041905134,0.001194494,0.0022891534,0.0016513546,0.0007695631,0.0029471153,0.0037220516,0.002852887,0.003716899],"category_scores_gemma":[0.01801561,0.0011685882,0.0016606704,0.0019822877,0.0019223702,0.005015988,0.003911448,0.004246216,0.0019294516],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016865908,0.000073872296,0.0008516677,0.0002708438,0.00015657926,0.00006897768,0.00017782243,0.20047839,0.0035517185,0.36285093,0.005511748,0.4258388],"study_design_scores_gemma":[0.000018150278,0.00004327833,0.00007630441,0.000034424524,0.000025293644,0.00007318784,0.000008613036,0.85760933,0.0012175903,0.13416347,0.006703802,0.000026456953],"about_ca_topic_score_codex":0.0015802551,"about_ca_topic_score_gemma":0.0015689834,"teacher_disagreement_score":0.0041905134,"about_ca_system_score_codex":0.00090728723,"about_ca_system_score_gemma":0.0013624214,"threshold_uncertainty_score":0.022161841},"labels":[],"label_agreement":null},{"id":"W4236061504","doi":"10.32920/ryerson.14663754","title":"Worst-case &amp; average-case Efficiency trade-offs for search problems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Set (abstract data type); Mathematical optimization; Operations research; Unit (ring theory); Work (physics); Mathematics; Engineering","score_opus":0.07756221973192895,"score_gpt":0.3166777557122791,"score_spread":0.23911553598035012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236061504","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08932567,0.00526557,0.87627167,0.002580229,0.00019612702,0.00013895596,0.00048799373,0.00033917004,0.025394682],"genre_scores_gemma":[0.79063135,0.0029327883,0.19550236,0.0004942949,0.0005255548,0.00045778975,0.0006376758,0.0010002347,0.007818006],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99153745,0.0036845542,0.00039287686,0.001254915,0.0019186205,0.0012115565],"domain_scores_gemma":[0.9430702,0.048293084,0.0026187247,0.0033140313,0.001813263,0.0008907001],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008929962,0.0020194722,0.0020474594,0.0018312382,0.0012635347,0.004083778,0.0026815415,0.0021710806,0.0060248035],"category_scores_gemma":[0.046162568,0.00094357476,0.0017973934,0.0027311991,0.0027228687,0.0070600742,0.0020675312,0.003484699,0.0007691969],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044485825,0.0003032417,0.001800217,0.000439886,0.00019930233,0.00013981087,0.00014109166,0.80609035,0.0023060231,0.15176179,0.0042028017,0.032170694],"study_design_scores_gemma":[0.000042950443,0.00010184395,0.0006748569,0.000050351595,0.000053540953,0.0001232842,0.00006960039,0.8548645,0.0015823168,0.14032751,0.0020849258,0.000024307143],"about_ca_topic_score_codex":0.0011920421,"about_ca_topic_score_gemma":0.001268432,"teacher_disagreement_score":0.008929962,"about_ca_system_score_codex":0.0033149393,"about_ca_system_score_gemma":0.0018390765,"threshold_uncertainty_score":0.047226727},"labels":[],"label_agreement":null},{"id":"W4237149507","doi":"10.1002/9780470072646.index","title":"Index","year":2006,"lang":"en","type":"paratext","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Index (typography); Computer science; Citation; Library science; World Wide Web; Information retrieval","score_opus":0.017499289438198014,"score_gpt":0.27008478481119047,"score_spread":0.25258549537299246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237149507","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012847593,0.0048004035,0.02128111,0.0033912635,0.005398752,0.00043392606,0.013706629,0.002528141,0.9471751],"genre_scores_gemma":[0.0062833834,0.00434885,0.010841332,0.00092419796,0.0019145536,0.0003895487,0.01035972,0.0012330686,0.96370536],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993475,0.00012557692,0.00003227026,0.00010435224,0.00033983687,0.000050359962],"domain_scores_gemma":[0.99846244,0.00049813604,0.0000831468,0.00023520782,0.00046722268,0.0002538662],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000630545,0.0015519173,0.0021001047,0.0031333684,0.0014605075,0.0056226244,0.0020285521,0.0018980425,0.6453796],"category_scores_gemma":[0.004882851,0.00037744394,0.0005192952,0.006393474,0.0008134899,0.0036605473,0.0015348134,0.0016695522,0.52141],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035766796,0.00006854724,0.00009594008,0.0003151321,0.0000065561517,0.000020457954,0.000018565392,0.0007354596,0.00027626724,0.015181338,0.851229,0.13201693],"study_design_scores_gemma":[0.000024663648,0.000029143475,0.00028493043,0.00022644436,0.000010687496,0.00006045964,0.000033401244,0.00248489,0.00029837084,0.023889178,0.9726443,0.000013567821],"about_ca_topic_score_codex":0.0031806082,"about_ca_topic_score_gemma":0.0055430075,"teacher_disagreement_score":0.3546204,"about_ca_system_score_codex":0.0017843387,"about_ca_system_score_gemma":0.0015757325,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4237945925","doi":"10.1007/978-1-4939-7131-2_100995","title":"Resource Exchange Networks","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Resource (disambiguation); Computer science; Computer network","score_opus":0.03127369159726002,"score_gpt":0.23879429922195078,"score_spread":0.20752060762469077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4237945925","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007031199,0.006938617,0.35857013,0.0034250547,0.001367828,0.00015247797,0.00066455937,0.0007909593,0.6210592],"genre_scores_gemma":[0.22112522,0.01708987,0.11213011,0.0010607868,0.0009917372,0.00054160366,0.0016751655,0.0005838822,0.64480156],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997216,0.00006354561,0.000010254078,0.000074215015,0.00008841411,0.00004189759],"domain_scores_gemma":[0.9996767,0.00013069263,0.000020898677,0.00009316019,0.000051084535,0.000027456937],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004753923,0.00072700175,0.0005106041,0.00068545935,0.00079074374,0.0025919469,0.0012642028,0.00089024456,0.039342903],"category_scores_gemma":[0.0016366193,0.00034339313,0.00033805805,0.0014895244,0.0008820662,0.0044164658,0.0015328024,0.0015066154,0.007388168],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000354678,0.000023846633,0.00005349939,0.000108551845,0.000011425776,0.000050082148,0.000053329557,0.014650162,0.000579094,0.83166295,0.04492269,0.10784898],"study_design_scores_gemma":[0.000009081986,0.000020496338,0.00010893526,0.00011184194,0.00001625855,0.00015511051,0.000075623306,0.03697031,0.0011678903,0.6307878,0.33056065,0.00001597679],"about_ca_topic_score_codex":0.0013905552,"about_ca_topic_score_gemma":0.0012178894,"teacher_disagreement_score":0.039342903,"about_ca_system_score_codex":0.0012143442,"about_ca_system_score_gemma":0.00072665786,"threshold_uncertainty_score":0.13161516},"labels":[],"label_agreement":null},{"id":"W4239155994","doi":"10.1002/net.20240","title":"Decontamination of hypercubes by mobile agents","year":2008,"lang":"en","type":"article","venue":"Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":37,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Locality; Hypercube; Visibility; Human decontamination; Binary logarithm; Node (physics); Synchronicity; Copying; Path (computing); Mobile agent; Distributed computing; Theoretical computer science; Computer network; Mathematics; Combinatorics; Parallel computing","score_opus":0.016013971612176426,"score_gpt":0.24127157903904298,"score_spread":0.22525760742686654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239155994","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40755147,0.0010737607,0.57901,0.00058611255,0.00013693856,0.00022393269,0.00011180949,0.00084932795,0.01045663],"genre_scores_gemma":[0.8928194,0.00042975342,0.10093595,0.00012726957,0.00004394436,0.00014233643,0.00022719389,0.00010113089,0.005173074],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99893695,0.0004716342,0.000052672654,0.00015040014,0.00022170074,0.0001666929],"domain_scores_gemma":[0.9982216,0.0006855165,0.00030909554,0.0003788951,0.00024364644,0.0001612953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010348536,0.00067084807,0.00086593936,0.00058119855,0.00086178083,0.0012374823,0.0011867236,0.0008862067,0.002021276],"category_scores_gemma":[0.002699272,0.00036600343,0.000562693,0.00066818536,0.0011123064,0.0016097764,0.0022015865,0.00065251824,0.00041413566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00032656323,0.00009811464,0.0013965265,0.00013095039,0.000052713425,0.00039011065,0.00022578819,0.9335677,0.0128213465,0.01938389,0.0011622808,0.030443983],"study_design_scores_gemma":[0.000036251222,0.00013923866,0.00024033106,0.00001710051,0.000011321735,0.00009195674,0.00016714807,0.9739106,0.008232096,0.013206359,0.0039364984,0.000010945161],"about_ca_topic_score_codex":0.0021701923,"about_ca_topic_score_gemma":0.0012299488,"teacher_disagreement_score":0.0021701923,"about_ca_system_score_codex":0.00067202456,"about_ca_system_score_gemma":0.00045014566,"threshold_uncertainty_score":0.006761849},"labels":[],"label_agreement":null},{"id":"W4241336885","doi":"10.1145/514001.514004","title":"Retargetable binary utilities","year":2002,"lang":"en","type":"article","venue":"Proceedings - ACM IEEE Design Automation Conference","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Binary number; Arithmetic; Mathematics","score_opus":0.1252185535176678,"score_gpt":0.26746779574041174,"score_spread":0.14224924222274393,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241336885","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0433723,0.0006504232,0.8881118,0.00023219147,0.00017722207,0.00026295692,0.0005855894,0.044325043,0.022282466],"genre_scores_gemma":[0.3771878,0.0008136854,0.5642189,0.00048403055,0.000098466175,0.0004418979,0.0022880137,0.0109893745,0.043477803],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99925905,0.00012720571,0.000050292772,0.00016046729,0.00027881912,0.00012410551],"domain_scores_gemma":[0.99841523,0.0006022482,0.00012543597,0.0006175128,0.00020496543,0.00003454915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00055700203,0.000824723,0.0005694019,0.0008931788,0.00040780357,0.0008953251,0.0014109093,0.00073585816,0.010545264],"category_scores_gemma":[0.0037215883,0.00048050444,0.00061807036,0.00062859076,0.0005405868,0.001508542,0.0020136426,0.0011907808,0.0047712103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003964847,0.00017285753,0.001963803,0.00049449835,0.000050097355,0.00093569583,0.00056284165,0.03448661,0.07609803,0.05950396,0.032262016,0.7930732],"study_design_scores_gemma":[0.00024556945,0.00035379743,0.0039015214,0.00027280056,0.00019408672,0.0026082897,0.00028522153,0.35943842,0.19923192,0.12762713,0.30566418,0.00017703888],"about_ca_topic_score_codex":0.00073676795,"about_ca_topic_score_gemma":0.0015172485,"teacher_disagreement_score":0.010545264,"about_ca_system_score_codex":0.00045448396,"about_ca_system_score_gemma":0.00045181168,"threshold_uncertainty_score":0.035277367},"labels":[],"label_agreement":null},{"id":"W4245355198","doi":"10.22215/etd/2016-11362","title":"Network Decontamination from Black Viruses","year":2016,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Node (physics); Network topology; Protocol (science); Computer science; Distributed computing; Hypercube; Human decontamination; Process (computing); A priori and a posteriori; Computer network; Theoretical computer science; Topology (electrical circuits); Mathematics; Combinatorics; Engineering; Parallel computing; Medicine","score_opus":0.023116412474773668,"score_gpt":0.2835354239136898,"score_spread":0.2604190114389161,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245355198","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.097051404,0.0048355996,0.8783046,0.0012231997,0.00027313674,0.00018430174,0.000064271604,0.00020460782,0.017858973],"genre_scores_gemma":[0.80603427,0.0049059573,0.16921146,0.00041532033,0.00016531287,0.00020905955,0.00015839553,0.00013726461,0.018763062],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993006,0.00021806857,0.00002191808,0.00015838098,0.00016940443,0.00013165455],"domain_scores_gemma":[0.99896157,0.0005220654,0.00017017312,0.00012223759,0.00013213721,0.00009171873],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009643734,0.0010945002,0.0010219222,0.0005898192,0.0006693664,0.0014669319,0.0010244894,0.0013616696,0.0019214263],"category_scores_gemma":[0.0031669515,0.00037517113,0.0007141594,0.00040794667,0.001140859,0.0020590827,0.0021986,0.001341503,0.0003779788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028194283,0.00015711693,0.0011937192,0.00064662105,0.000099491626,0.00034513287,0.0003713668,0.7432744,0.013195908,0.122964926,0.0039914367,0.11347799],"study_design_scores_gemma":[0.00004316804,0.00033427944,0.0003114808,0.00014272642,0.0000455172,0.00028649863,0.00031573424,0.881386,0.009579277,0.093675315,0.013855148,0.000024843848],"about_ca_topic_score_codex":0.0011369333,"about_ca_topic_score_gemma":0.0007671955,"teacher_disagreement_score":0.0019214263,"about_ca_system_score_codex":0.0007113727,"about_ca_system_score_gemma":0.00079289114,"threshold_uncertainty_score":0.006427765},"labels":[],"label_agreement":null},{"id":"W4248873997","doi":"10.1109/.2005.1507503","title":"Adaptive distributed fetching and retrieval of goods by a swarm-bot","year":2005,"lang":"en","type":"article","venue":"ICAR '05. Proceedings., 12th International Conference on Advanced Robotics, 2005.","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Office of Science; European Commission","keywords":"Computer science; Swarm behaviour; Distributed computing; Artificial intelligence","score_opus":0.03225028681133361,"score_gpt":0.2956061750044992,"score_spread":0.2633558881931656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248873997","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20197487,0.00015915584,0.79204404,0.00020696082,0.000029818919,0.000097329736,0.000049599457,0.0009046534,0.004533666],"genre_scores_gemma":[0.8860169,0.000117633426,0.10947133,0.000035623332,0.000011230586,0.0001092508,0.00006806204,0.000053510008,0.0041164467],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998467,0.000027352351,0.0000105687495,0.000051424417,0.000035799716,0.000028126382],"domain_scores_gemma":[0.99963725,0.00014019782,0.00006370559,0.00007473923,0.000039322284,0.000044697408],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004267791,0.0005057592,0.0005568476,0.00035406672,0.00052354933,0.00073636335,0.00093894225,0.00071165577,0.0014886857],"category_scores_gemma":[0.0008297948,0.00033320158,0.0004707432,0.00031857248,0.0009658217,0.0009307546,0.0010077874,0.00043546778,0.00026435754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031665427,0.00013020747,0.0022843801,0.000117978016,0.00006141779,0.00034881968,0.00024280068,0.8629252,0.055666205,0.020591829,0.0010194175,0.05629501],"study_design_scores_gemma":[0.000020869316,0.00006018832,0.00027849516,0.0000030420947,0.000012370676,0.000036746023,0.000035865785,0.9901938,0.0038380595,0.00460206,0.00091127265,0.0000072195235],"about_ca_topic_score_codex":0.0028857219,"about_ca_topic_score_gemma":0.0023204286,"teacher_disagreement_score":0.0028857219,"about_ca_system_score_codex":0.00060957327,"about_ca_system_score_gemma":0.0006729076,"threshold_uncertainty_score":0.0057377815},"labels":[],"label_agreement":null},{"id":"W4249919375","doi":"10.32920/ryerson.14663754.v1","title":"Worst-case &amp; average-case Efficiency trade-offs for search problems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mathematical optimization; Computer science; Set (abstract data type); Search theory; Operations research; Unit (ring theory); Work (physics); Mathematics; Engineering; Economics; Microeconomics","score_opus":0.07756221973192895,"score_gpt":0.3166777557122791,"score_spread":0.23911553598035012,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4249919375","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08932567,0.00526556,0.87627167,0.002580224,0.00019612665,0.00013895596,0.0004879933,0.00033917004,0.025394646],"genre_scores_gemma":[0.7906313,0.0029327828,0.1955024,0.0004942944,0.00052555377,0.00045778995,0.0006376749,0.0010002338,0.007817994],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99153745,0.003684556,0.00039287648,0.0012549137,0.0019186205,0.0012115553],"domain_scores_gemma":[0.94307023,0.048293017,0.0026187224,0.0033140252,0.0018132587,0.0008906989],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008929962,0.0020194722,0.0020474594,0.0018312371,0.0012635335,0.0040837736,0.0026815378,0.0021710796,0.0060248007],"category_scores_gemma":[0.04616254,0.0009435743,0.0017973917,0.0027311968,0.0027228713,0.0070600673,0.0020675312,0.003484699,0.00076919544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044485772,0.00030324148,0.0018002156,0.00043988568,0.00019930238,0.00013981079,0.00014109143,0.80609053,0.0023060224,0.15176153,0.004202796,0.032170653],"study_design_scores_gemma":[0.000042950487,0.00010184405,0.0006748569,0.000050351595,0.000053540905,0.00012328397,0.00006960039,0.8548645,0.0015823175,0.14032751,0.0020849227,0.000024307164],"about_ca_topic_score_codex":0.0011920416,"about_ca_topic_score_gemma":0.001268432,"teacher_disagreement_score":0.008929962,"about_ca_system_score_codex":0.003314936,"about_ca_system_score_gemma":0.0018390765,"threshold_uncertainty_score":0.047226727},"labels":[],"label_agreement":null},{"id":"W4250203847","doi":"10.1002/dac.976","title":"An efficient pursuit automata approach for estimating stable all‐pairs shortest paths in stochastic network environments","year":2008,"lang":"en","type":"article","venue":"International Journal of Communication Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Shortest path problem; Computer science; Shortest Path Faster Algorithm; Algorithm; Floyd–Warshall algorithm; Graph; K shortest path routing; Theoretical computer science","score_opus":0.04909891223916364,"score_gpt":0.3075747939105659,"score_spread":0.2584758816714023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250203847","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012467423,0.000078155186,0.9865621,0.0001022938,0.000018360848,0.000026476133,0.000031120348,0.00018946838,0.00052462734],"genre_scores_gemma":[0.6420262,0.000213672,0.35438555,0.00015966735,0.0000639331,0.00030300583,0.00026539213,0.00010425446,0.0024783348],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991054,0.0002863788,0.000064841115,0.00024449185,0.00021082786,0.00008810936],"domain_scores_gemma":[0.9956142,0.003096272,0.00026220726,0.0002774206,0.0005961829,0.00015375993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017216261,0.00077710825,0.0014297339,0.0012581048,0.0005532222,0.0013603838,0.0019367335,0.0013093606,0.0018954219],"category_scores_gemma":[0.008936211,0.0006174036,0.0008902929,0.00095892843,0.0011641347,0.0018920602,0.0020602616,0.0016160004,0.00035462936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006204416,0.000032300417,0.00084455806,0.000045618443,0.000037317543,0.00003235224,0.000058725025,0.9407874,0.00088015205,0.012613177,0.00039301038,0.04421343],"study_design_scores_gemma":[0.0000019298568,0.0000075485505,0.000022430851,0.0000016523494,0.000001309669,0.0000029750345,0.0000032906141,0.9972907,0.00011321752,0.0024919307,0.00006124676,0.0000017892773],"about_ca_topic_score_codex":0.005692359,"about_ca_topic_score_gemma":0.0035157541,"teacher_disagreement_score":0.005692359,"about_ca_system_score_codex":0.0010736969,"about_ca_system_score_gemma":0.0014775151,"threshold_uncertainty_score":0.011318445},"labels":[],"label_agreement":null},{"id":"W4250867380","doi":"10.2139/ssrn.2200485","title":"A Markov Switching Approach to Herding","year":2012,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; Balsillie School of International Affairs","funders":"","keywords":"Herding; Markov chain; Computer science; Business; Economics; Econometrics; Geography; Machine learning","score_opus":0.014750449262290721,"score_gpt":0.25488388603816997,"score_spread":0.24013343677587926,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4250867380","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043025315,0.0013741986,0.9366205,0.0025641036,0.00032154578,0.00007566515,0.00043056355,0.00028026415,0.015307912],"genre_scores_gemma":[0.8445491,0.0031458999,0.10314261,0.0007032232,0.00091955956,0.00035969607,0.00059588597,0.00023493702,0.04634911],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987482,0.0006306331,0.000056985526,0.00021434305,0.0001749412,0.00017487582],"domain_scores_gemma":[0.9917459,0.006608417,0.00050943455,0.00038416768,0.00042251716,0.00032954785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026846973,0.00076895615,0.002570439,0.0021648472,0.0013005617,0.0024857349,0.0042198715,0.0037113326,0.012517253],"category_scores_gemma":[0.011662927,0.001259032,0.0021889992,0.0020543584,0.0026004605,0.004434881,0.0020685703,0.003169481,0.00083834596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005156746,0.0000747213,0.0010522876,0.000090748814,0.00011247159,0.00015620288,0.00015276791,0.30849376,0.00033706857,0.67615,0.003180282,0.010148092],"study_design_scores_gemma":[0.00002036952,0.0000174596,0.00020572997,0.000011993848,0.000024276462,0.000029762614,0.000025508809,0.7880389,0.000031417214,0.21088903,0.0006878954,0.000017694141],"about_ca_topic_score_codex":0.01471196,"about_ca_topic_score_gemma":0.011863222,"teacher_disagreement_score":0.01471196,"about_ca_system_score_codex":0.00246824,"about_ca_system_score_gemma":0.0015627266,"threshold_uncertainty_score":0.04187435},"labels":[],"label_agreement":null},{"id":"W4253180224","doi":"10.1007/978-3-030-11072-7_15","title":"Patrolling","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University; Université du Québec en Outaouais","funders":"","keywords":"Patrolling; Computer science; Robot; Variety (cybernetics); Mobile robot; Graph; Point (geometry); Artificial intelligence; Theoretical computer science; Mathematics; Geometry","score_opus":0.02041638483535308,"score_gpt":0.2504378034000851,"score_spread":0.23002141856473202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253180224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043071296,0.0008680824,0.60121006,0.00052894594,0.0009023005,0.00042182428,0.001638138,0.032953344,0.318406],"genre_scores_gemma":[0.275185,0.00097084197,0.30402678,0.00055961916,0.00023508012,0.00031216844,0.0051846295,0.0036713553,0.40985456],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969494,0.000014044525,0.000011863446,0.00011655191,0.000105951534,0.000056667708],"domain_scores_gemma":[0.9996973,0.000041638697,0.000022160906,0.00015072578,0.00006256267,0.000025626645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001447221,0.00083197956,0.0005093218,0.00070408784,0.00077461515,0.0009263504,0.0011941065,0.0005755109,0.07965349],"category_scores_gemma":[0.000659307,0.00041841457,0.0005219924,0.000777775,0.00042673107,0.0013316212,0.001130731,0.00096590683,0.023841353],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027691232,0.00019139914,0.0005832384,0.00025350103,0.000020405163,0.00018335144,0.00016819304,0.010704044,0.051167537,0.03557588,0.05384226,0.84703314],"study_design_scores_gemma":[0.000084639825,0.00048250493,0.0024085513,0.00015202267,0.00006629658,0.0010569027,0.0002654743,0.15213414,0.121185705,0.06089496,0.66119426,0.00007455902],"about_ca_topic_score_codex":0.0013033168,"about_ca_topic_score_gemma":0.001541545,"teacher_disagreement_score":0.07965349,"about_ca_system_score_codex":0.00029114957,"about_ca_system_score_gemma":0.00046920255,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4255922256","doi":"10.32920/ryerson.14655639","title":"Scatter Search on a Disk","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Robot; Upper and lower bounds; Unit disk; Carry (investment); Object (grammar); Computer science; Combinatorics; Artificial intelligence; Mathematics","score_opus":0.048902244932385895,"score_gpt":0.30631048598973365,"score_spread":0.2574082410573478,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4255922256","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44641173,0.0022490653,0.5259217,0.0012912217,0.00011052934,0.00009621656,0.00052898267,0.00067223585,0.022718374],"genre_scores_gemma":[0.89609194,0.00052503,0.091020584,0.00019147148,0.00004497315,0.000089914174,0.00047171678,0.000110664376,0.011453752],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960166,0.000099643396,0.000020645852,0.00010459441,0.00007574342,0.000097756194],"domain_scores_gemma":[0.99866295,0.00079284405,0.00011773184,0.00017173572,0.0001426845,0.00011204093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004540867,0.00047615173,0.0010973216,0.0007850085,0.0010100208,0.001247403,0.0009258523,0.0013934604,0.005577735],"category_scores_gemma":[0.003334537,0.0004007154,0.00039849884,0.0013153307,0.0006908374,0.0022427528,0.0016252022,0.00059921335,0.0010648095],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00090682914,0.00013148294,0.0022828467,0.00024805524,0.00006886957,0.0005304167,0.0003228697,0.87778115,0.008310156,0.055066515,0.0077559194,0.046594918],"study_design_scores_gemma":[0.000060240698,0.00006635445,0.00029762398,0.000014843242,0.000007860815,0.0001326004,0.00011506907,0.9729969,0.001351822,0.022633614,0.0023137382,0.000009394902],"about_ca_topic_score_codex":0.0053495597,"about_ca_topic_score_gemma":0.0034083757,"teacher_disagreement_score":0.005577735,"about_ca_system_score_codex":0.00102065,"about_ca_system_score_gemma":0.0007243997,"threshold_uncertainty_score":0.018659413},"labels":[],"label_agreement":null},{"id":"W4256116496","doi":"10.2139/ssrn.3724499","title":"Reclamation of a Resource Extraction Site: A Dynamic Game Approach","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Manitoba; Memorial University of Newfoundland","funders":"","keywords":"Land reclamation; Extraction (chemistry); Resource (disambiguation); Computer science; Geography; Archaeology; Chemistry; Chromatography","score_opus":0.01344609984647184,"score_gpt":0.2514250514724357,"score_spread":0.23797895162596389,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256116496","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1540519,0.0004076981,0.7450917,0.003729053,0.0002073124,0.0010422778,0.00041073156,0.00033037562,0.09472895],"genre_scores_gemma":[0.91709626,0.0002548133,0.05969567,0.00022092668,0.000048273723,0.00032455157,0.00009858965,0.000092235874,0.022168629],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979644,0.00087183306,0.00006172137,0.0003278227,0.00024288986,0.00053127133],"domain_scores_gemma":[0.9965061,0.0021798792,0.00025321657,0.00019208666,0.00027573196,0.00059301197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002512258,0.0011275052,0.0021189728,0.00157514,0.0019913078,0.0040749516,0.0052462597,0.0060682343,0.019125352],"category_scores_gemma":[0.006804824,0.001064914,0.0017291213,0.0012268154,0.0024173534,0.005868192,0.003590761,0.0029343045,0.00089185004],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046603382,0.000329159,0.0009708501,0.0002526621,0.00013654624,0.0012671332,0.00041227063,0.77796376,0.0042958194,0.1920168,0.0035612048,0.018327788],"study_design_scores_gemma":[0.00006525087,0.00024696728,0.00030213504,0.00003933628,0.00006508735,0.0001623545,0.0005873962,0.9393761,0.00063506246,0.055075843,0.0033981476,0.00004637502],"about_ca_topic_score_codex":0.009189022,"about_ca_topic_score_gemma":0.009918613,"teacher_disagreement_score":0.019125352,"about_ca_system_score_codex":0.0025513105,"about_ca_system_score_gemma":0.003538229,"threshold_uncertainty_score":0.06398064},"labels":[],"label_agreement":null},{"id":"W4281701211","doi":"10.1145/3543516.3456271","title":"Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging","year":2021,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Division of Electrical, Communications and Cyber Systems; University of Toronto; National Science Foundation","keywords":"Knapsack problem; Competitive analysis; Continuous knapsack problem; Online algorithm; Computer science; Algorithm; Mathematical optimization; Limiting; Identification (biology); Dual (grammatical number); Generalized assignment problem; Change-making problem; Optimization problem; Mathematics; Upper and lower bounds; Engineering","score_opus":0.06932257938094619,"score_gpt":0.3470856595915804,"score_spread":0.27776308021063423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281701211","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0081775645,0.0008611297,0.9801748,0.00046650556,0.0001229874,0.00015026511,0.000062476356,0.00020818005,0.009776042],"genre_scores_gemma":[0.36505115,0.0017258951,0.62465507,0.00045776213,0.00039634152,0.00050598645,0.00025886708,0.00032839822,0.006620592],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99651957,0.001487916,0.00014878968,0.0005550225,0.0008805839,0.0004081161],"domain_scores_gemma":[0.9892671,0.008063804,0.0007964003,0.0006188163,0.000892583,0.0003612442],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046159457,0.0020402137,0.0019710811,0.0012287585,0.0010912872,0.0032821856,0.0035434882,0.0023385144,0.0046319976],"category_scores_gemma":[0.015281565,0.0008471657,0.0012232885,0.0029566586,0.0017909254,0.0034367254,0.002083069,0.0038431848,0.0007736805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015797997,0.00037002767,0.0004761047,0.00029396676,0.00006547335,0.000085839485,0.00012539986,0.7790534,0.0010999873,0.14309214,0.005301762,0.069877855],"study_design_scores_gemma":[0.000025725865,0.000057323035,0.00006732548,0.0000136218305,0.000010160276,0.000039364382,0.000026496084,0.9570644,0.0003673336,0.040450845,0.0018655868,0.000011807176],"about_ca_topic_score_codex":0.0041909353,"about_ca_topic_score_gemma":0.0038962807,"teacher_disagreement_score":0.0046319976,"about_ca_system_score_codex":0.0027912452,"about_ca_system_score_gemma":0.003068865,"threshold_uncertainty_score":0.024411738},"labels":[],"label_agreement":null},{"id":"W4285044551","doi":"10.22215/etd/2022-15057","title":"Strategies for Cooperative Energy Distribution on Multi-Robot Warehouse Systems","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Mobile robot; Power (physics); Battery capacity; Energy (signal processing); Engineering; Feature (linguistics); Battery (electricity); Computer science; Real-time computing; Simulation; Artificial intelligence","score_opus":0.039743587917462804,"score_gpt":0.3162381766939221,"score_spread":0.2764945887764593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285044551","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050786197,0.0005208127,0.9222511,0.0005320358,0.00007095245,0.00012429715,0.000051015435,0.00021037538,0.025453186],"genre_scores_gemma":[0.96062005,0.00033017137,0.026426787,0.00009999083,0.00003942361,0.00022105311,0.000045647044,0.000055713394,0.012161279],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997762,0.000063770676,0.000011505381,0.00004940158,0.000049848433,0.000049273225],"domain_scores_gemma":[0.9996358,0.00017191515,0.000048300048,0.000026334315,0.000078057485,0.000039634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051082484,0.00089653995,0.0007804597,0.0006442944,0.00069757784,0.0012515271,0.0015239154,0.0010242942,0.006368653],"category_scores_gemma":[0.001034247,0.00033675178,0.0005967854,0.0004918142,0.00073987676,0.0013107868,0.0021247913,0.00061853684,0.00073464884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000113150316,0.00007158399,0.00030488186,0.0001350497,0.00005896993,0.00032575984,0.00025764326,0.8948044,0.006831137,0.06470009,0.00203247,0.03036477],"study_design_scores_gemma":[0.000018356142,0.00006540532,0.000077370445,0.000009218919,0.000008860448,0.00003010032,0.000056673915,0.98264664,0.0005285382,0.015504003,0.0010478523,0.000006943784],"about_ca_topic_score_codex":0.0018799452,"about_ca_topic_score_gemma":0.0016476836,"teacher_disagreement_score":0.006368653,"about_ca_system_score_codex":0.0006609969,"about_ca_system_score_gemma":0.00040915186,"threshold_uncertainty_score":0.021305323},"labels":[],"label_agreement":null},{"id":"W4285133257","doi":"10.1090/stml/097/05","title":"The localization game","year":2022,"lang":"en","type":"book-chapter","venue":"Student mathematical library","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science","score_opus":0.017611368599253847,"score_gpt":0.25021456683919335,"score_spread":0.2326031982399395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285133257","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007902047,0.0011844634,0.08061078,0.006085407,0.00021317178,0.000044641616,0.0001595881,0.00019259642,0.9036073],"genre_scores_gemma":[0.4394294,0.0018968901,0.01766236,0.0018224843,0.00025046486,0.0002591456,0.00028287864,0.00022111848,0.5381752],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996685,0.00013159189,0.000008163806,0.000062803985,0.000065998785,0.00006285365],"domain_scores_gemma":[0.9995819,0.00022385777,0.00002497708,0.000054744247,0.0000458953,0.00006858954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00039206122,0.0006534689,0.0005150567,0.00038849862,0.0012018135,0.0032796878,0.0010671655,0.0018389795,0.054079033],"category_scores_gemma":[0.0027496454,0.00028728106,0.0004109398,0.0005276748,0.0021367457,0.0046507353,0.0019633388,0.0026073288,0.007699096],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000014872791,0.000012306224,0.000031527587,0.000018441757,0.000002675034,0.000023291765,0.000062307685,0.0013682805,0.0000953298,0.972475,0.01649253,0.009403498],"study_design_scores_gemma":[0.0000127181665,0.00001306639,0.000053740903,0.000030905543,0.0000030198817,0.000051012004,0.00011478346,0.0069967876,0.00013741529,0.94172823,0.050852325,0.0000060754683],"about_ca_topic_score_codex":0.0019255586,"about_ca_topic_score_gemma":0.0017758362,"teacher_disagreement_score":0.054079033,"about_ca_system_score_codex":0.0017188903,"about_ca_system_score_gemma":0.0010533549,"threshold_uncertainty_score":0.18091238},"labels":[],"label_agreement":null},{"id":"W4285235194","doi":"10.1007/978-3-030-96087-2_2","title":"Robot Models","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in control and information sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Robot; Computer science; Artificial intelligence","score_opus":0.023787812482109226,"score_gpt":0.24295485994413168,"score_spread":0.21916704746202245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285235194","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077828425,0.00437373,0.56238014,0.0017233489,0.001407615,0.00015948305,0.004465563,0.0017609205,0.41594627],"genre_scores_gemma":[0.25393027,0.0064626643,0.07287762,0.0009363126,0.00058629643,0.0006781543,0.007849113,0.00074071565,0.65593874],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998153,0.000027954811,0.000006985044,0.000056166653,0.00007098809,0.000022533319],"domain_scores_gemma":[0.99987316,0.000025212128,0.000015321533,0.000039066854,0.000034843906,0.000012397134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015468517,0.0011926993,0.00090077403,0.00073790486,0.0004583057,0.0013204953,0.0014863478,0.001358709,0.04679816],"category_scores_gemma":[0.00062590715,0.00036587645,0.0007668629,0.00058657076,0.0005814188,0.0012099359,0.0012236836,0.0010576749,0.021250289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042007636,0.000048518163,0.00024015931,0.0002167363,0.000039549548,0.00015223787,0.00006490101,0.13890682,0.0024527549,0.7538817,0.04109151,0.06286305],"study_design_scores_gemma":[0.000031523246,0.00008343781,0.00034637828,0.000068901056,0.00003137712,0.00025271575,0.00006133834,0.34110156,0.0011091972,0.45760503,0.19927473,0.000033782242],"about_ca_topic_score_codex":0.0022038857,"about_ca_topic_score_gemma":0.0017418093,"teacher_disagreement_score":0.04679816,"about_ca_system_score_codex":0.0005038915,"about_ca_system_score_gemma":0.00049770495,"threshold_uncertainty_score":0.15655547},"labels":[],"label_agreement":null},{"id":"W4286580165","doi":"10.1109/lra.2022.3193242","title":"Min-Max Vertex Cycle Covers With Connectivity Constraints for Multi-Robot Patrolling","year":2022,"lang":"en","type":"article","venue":"IEEE Robotics and Automation Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Vector Institute; University of Toronto","funders":"","keywords":"Patrolling; Robot; Vertex (graph theory); Vertex cover; Computer science; Greedy algorithm; Mathematical optimization; Disjoint sets; Time complexity; Mathematics; Algorithm; Theoretical computer science; Combinatorics; Artificial intelligence; Graph","score_opus":0.024789209281276106,"score_gpt":0.25371809794594163,"score_spread":0.22892888866466554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4286580165","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17673726,0.00071853393,0.80900604,0.00059380475,0.00006685017,0.00024914692,0.0006466908,0.00051988167,0.011461726],"genre_scores_gemma":[0.85096484,0.00042213156,0.14418985,0.00012382453,0.000035445217,0.000315794,0.0005654892,0.0001553979,0.0032271666],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994536,0.00018112164,0.000015727726,0.00011431371,0.00010189024,0.00013339668],"domain_scores_gemma":[0.9989304,0.00066425675,0.0001791136,0.00006748208,0.00006134553,0.000097439326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006130356,0.001189796,0.0009825765,0.0006953951,0.0006669349,0.0011007724,0.0011568591,0.0009982004,0.0037657572],"category_scores_gemma":[0.0021820632,0.000604846,0.0008252678,0.0013265357,0.00076943514,0.001275577,0.0008389126,0.0008504843,0.00026095856],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003182841,0.000025683858,0.000226609,0.000041141757,0.0000117620675,0.000054264252,0.000023232016,0.98913133,0.0004677686,0.0042677275,0.0004550541,0.005263617],"study_design_scores_gemma":[0.000010669492,0.000038407514,0.0001346905,0.0000069219786,0.000005613287,0.000025030195,0.000025485273,0.99135345,0.00038798485,0.007340413,0.00066685886,0.0000044687263],"about_ca_topic_score_codex":0.00808838,"about_ca_topic_score_gemma":0.0071102,"teacher_disagreement_score":0.00808838,"about_ca_system_score_codex":0.001371492,"about_ca_system_score_gemma":0.0012361271,"threshold_uncertainty_score":0.016082585},"labels":[],"label_agreement":null},{"id":"W4287445554","doi":"10.17190/amf/1773392","title":"AmeriFlux CA-HPC Havikpak Creek","year":2021,"lang":"en","type":"dataset","venue":"OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Wilfrid Laurier University; Université de Montréal","funders":"","keywords":"Environmental science; Geography","score_opus":0.0161923726681419,"score_gpt":0.250613850919022,"score_spread":0.2344214782508801,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287445554","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00020573453,0.000055345612,0.000057322737,0.00004018653,0.00002085808,0.0000067440315,0.9982888,0.00048116708,0.0008437283],"genre_scores_gemma":[0.00037203712,0.00003062685,0.00018020821,0.000015602614,0.000003929448,0.000021102147,0.99885285,0.00006891462,0.00045477448],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99934286,0.000068880276,0.000043356154,0.00023915622,0.00017998464,0.00012574854],"domain_scores_gemma":[0.9990031,0.00012894592,0.00008782067,0.0002661783,0.00037199815,0.00014191723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006138901,0.0021575708,0.0014868587,0.0024370444,0.0008311805,0.0022089519,0.0031391764,0.0015507657,0.052821085],"category_scores_gemma":[0.0023960914,0.00066892355,0.00100798,0.0060800803,0.0004652829,0.0016137463,0.0013461495,0.0015333849,0.10039233],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000042033727,0.000014938159,0.0005502645,0.00021654091,0.000012783097,0.000013368099,0.000012163739,0.0002800698,0.00007129799,0.00024051302,0.9968823,0.0016639027],"study_design_scores_gemma":[0.00023459455,0.000017263712,0.0050179437,0.00020019813,0.000018568517,0.000058730693,0.00010666262,0.0009006232,0.00035385278,0.0011585214,0.99190193,0.000031113737],"about_ca_topic_score_codex":0.061469488,"about_ca_topic_score_gemma":0.11226123,"teacher_disagreement_score":0.061469488,"about_ca_system_score_codex":0.0017415067,"about_ca_system_score_gemma":0.0018499186,"threshold_uncertainty_score":0.17670411},"labels":[],"label_agreement":null},{"id":"W4287558369","doi":"10.48550/arxiv.2005.00880","title":"Almost Universal Anonymous Rendezvous in the Plane","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Agence Nationale de la Recherche; Université du Québec en Outaouais","keywords":"Rendezvous; Set (abstract data type); Computer science; Plane (geometry); Position (finance); Visibility; Algorithm; Existential quantification; Rotation (mathematics); Orientation (vector space); Mathematics; Combinatorics; Artificial intelligence; Geometry; Physics","score_opus":0.10751423870194961,"score_gpt":0.1941067573270157,"score_spread":0.0865925186250661,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4287558369","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5541843,0.0005113159,0.4165282,0.0010100604,0.000039079434,0.00020709547,0.0018534614,0.002074568,0.02359185],"genre_scores_gemma":[0.9129978,0.00031130886,0.080970176,0.00012461477,0.00003436086,0.00011687566,0.00148228,0.00021263286,0.0037499394],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99647444,0.00060380856,0.00029486595,0.00097142166,0.00076653983,0.00088889984],"domain_scores_gemma":[0.99285924,0.0039976155,0.0010715134,0.0012156112,0.00043939546,0.00041671091],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012557816,0.0008912906,0.0013289764,0.00080613815,0.0016385838,0.0038462947,0.0020027729,0.0014230169,0.004055582],"category_scores_gemma":[0.00856205,0.0008793536,0.0021295089,0.0016625411,0.0018857464,0.0053901915,0.0032647606,0.002083653,0.0008333157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011807726,0.00023702814,0.0041685696,0.0005595259,0.00028160433,0.000995953,0.0017161684,0.32288525,0.013614033,0.6125444,0.004092963,0.0377238],"study_design_scores_gemma":[0.00021179287,0.00015425064,0.0011698025,0.000074263946,0.00011609741,0.00078543235,0.000635508,0.33214837,0.012729545,0.6417431,0.010153206,0.00007868035],"about_ca_topic_score_codex":0.0038741378,"about_ca_topic_score_gemma":0.0031228203,"teacher_disagreement_score":0.004055582,"about_ca_system_score_codex":0.0017007516,"about_ca_system_score_gemma":0.001080676,"threshold_uncertainty_score":0.013567269},"labels":[],"label_agreement":null},{"id":"W4292924664","doi":"10.1007/978-3-319-89441-6","title":"Approximation and Online Algorithms","year":2018,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Algorithm; Online algorithm","score_opus":0.020703148704578293,"score_gpt":0.27208474132042837,"score_spread":0.2513815926158501,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4292924664","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004776416,0.052846923,0.6042455,0.006592868,0.0052957125,0.00014511179,0.0013691289,0.003105205,0.32162312],"genre_scores_gemma":[0.1477591,0.05383626,0.3708916,0.0031756323,0.008798538,0.00064263854,0.0052014943,0.0035367748,0.406158],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99857724,0.00026425096,0.000053726715,0.00030186208,0.00065325917,0.00014972899],"domain_scores_gemma":[0.9984909,0.0006566739,0.00006509416,0.00053690386,0.00017232787,0.000077985635],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095862645,0.002461467,0.0025998177,0.0017101314,0.0008373165,0.003857776,0.0025655425,0.0018777989,0.038150005],"category_scores_gemma":[0.004518784,0.00090114924,0.0013459892,0.0052666324,0.0015221772,0.005366739,0.0023532184,0.006771229,0.01810801],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017836112,0.00022538142,0.00026298495,0.0006475247,0.00008470969,0.000058424186,0.000055207296,0.026936801,0.0009426309,0.32895038,0.20410559,0.437552],"study_design_scores_gemma":[0.000059521983,0.00005058638,0.00045313718,0.00023580276,0.00006401673,0.00024899156,0.00003799114,0.090422645,0.0012695462,0.70960706,0.19752502,0.000025684625],"about_ca_topic_score_codex":0.0015539607,"about_ca_topic_score_gemma":0.0015101611,"teacher_disagreement_score":0.038150005,"about_ca_system_score_codex":0.0025456387,"about_ca_system_score_gemma":0.001397267,"threshold_uncertainty_score":0.12762451},"labels":[],"label_agreement":null},{"id":"W4293716608","doi":"10.1145/3561074.3561086","title":"Online Selection with Convex Costs","year":2022,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; University of Alberta","funders":"","keywords":"Selection (genetic algorithm); Computer science; Sequence (biology); Regular polygon; Value (mathematics); Simple (philosophy); Online algorithm; Convex optimization; Mathematical optimization; Secretary problem; Operations research; Artificial intelligence; Mathematics; Machine learning; Algorithm; Optimal stopping","score_opus":0.07365050367698708,"score_gpt":0.3415781810257241,"score_spread":0.267927677348737,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293716608","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.042948846,0.00088488276,0.94384176,0.0015570752,0.00013565652,0.00016272558,0.00021695596,0.00040254678,0.009849599],"genre_scores_gemma":[0.83631265,0.0011405257,0.14660898,0.0005772262,0.0003712194,0.0003549667,0.00042103493,0.0002317505,0.0139816245],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9967249,0.0014448564,0.00011147542,0.0005536639,0.0006478542,0.00051736546],"domain_scores_gemma":[0.98505753,0.012066517,0.0008746334,0.00080485456,0.0006188535,0.00057765207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031457895,0.0014378465,0.0020428007,0.00066273723,0.00063635706,0.0023354504,0.0024297405,0.0017532603,0.0055647423],"category_scores_gemma":[0.013962354,0.00069426745,0.00082835805,0.0014251833,0.001585359,0.0043156384,0.0015665127,0.0025377895,0.00088186585],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004473737,0.0002695356,0.0011544661,0.00023422707,0.00008651744,0.00025017944,0.000085904016,0.8528619,0.0013758664,0.08749915,0.0054551484,0.05027973],"study_design_scores_gemma":[0.00003300665,0.000067700654,0.0001434534,0.000010843131,0.0000114956665,0.000054280325,0.000016048432,0.96683717,0.00040256223,0.03149572,0.0009191369,0.000008527551],"about_ca_topic_score_codex":0.0026658943,"about_ca_topic_score_gemma":0.0018213191,"teacher_disagreement_score":0.0055647423,"about_ca_system_score_codex":0.0023122139,"about_ca_system_score_gemma":0.0017502368,"threshold_uncertainty_score":0.018615961},"labels":[],"label_agreement":null},{"id":"W4293822285","doi":"10.32866/001c.37217","title":"An Improved Lower Bound on the Competitive Ratio of Deterministic Online Algorithms for the Multi-agent K-Canadian Traveler Problem","year":2022,"lang":"en","type":"article","venue":"Findings","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Competitive analysis; Online algorithm; Upper and lower bounds; Computer science; Algorithm; Mathematical optimization; Mathematics","score_opus":0.05006125387348197,"score_gpt":0.2932991362153282,"score_spread":0.24323788234184623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4293822285","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050600644,0.0063246572,0.80557406,0.0058660097,0.001167513,0.00092570926,0.0025727442,0.0028498694,0.124118686],"genre_scores_gemma":[0.5632817,0.004538232,0.39538732,0.002836399,0.0014583129,0.0016148327,0.0028587733,0.0019056953,0.02611869],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98961943,0.002206478,0.000328766,0.0017178974,0.003553654,0.0025737148],"domain_scores_gemma":[0.97216606,0.018898273,0.0011441888,0.0033558793,0.0027940082,0.0016416084],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067034727,0.0039634653,0.0045217946,0.0030655817,0.0034861332,0.006103275,0.010022385,0.00401596,0.02434826],"category_scores_gemma":[0.037461497,0.0013658433,0.0030757892,0.0055119423,0.0034869998,0.008430243,0.0049753413,0.00830527,0.0037630012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013820336,0.0010611498,0.0021527184,0.0012773101,0.00035073757,0.00029708585,0.00040817398,0.5729065,0.008944303,0.24062358,0.057097692,0.11349871],"study_design_scores_gemma":[0.0001506731,0.0002177034,0.0007427042,0.00009760145,0.000116402734,0.00021856737,0.00009846915,0.90795845,0.0023939942,0.07549542,0.012425626,0.000084451785],"about_ca_topic_score_codex":0.036752068,"about_ca_topic_score_gemma":0.03519222,"teacher_disagreement_score":0.036752068,"about_ca_system_score_codex":0.0088071115,"about_ca_system_score_gemma":0.012482632,"threshold_uncertainty_score":0.081453025},"labels":[],"label_agreement":null},{"id":"W4297251947","doi":"10.3233/fi-222128","title":"Gathering over Meeting Nodes in Infinite Grid*","year":2022,"lang":"en","type":"article","venue":"Fundamenta Informaticae","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Asynchronous communication; Computer science; Grid; Robot; Distributed computing; Upper and lower bounds; Distributed algorithm; Theoretical computer science; Mathematics; Computer network; Artificial intelligence","score_opus":0.01786361352679732,"score_gpt":0.25010612691852246,"score_spread":0.23224251339172514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4297251947","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18967177,0.00045789708,0.79791963,0.0005519297,0.00007291377,0.00009577198,0.00023735891,0.0004078533,0.010584939],"genre_scores_gemma":[0.83166504,0.0003118831,0.16169205,0.00006557268,0.000022307579,0.00013631233,0.0005364056,0.00008080738,0.0054895906],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994293,0.00024252672,0.000026639103,0.00010358281,0.00008732419,0.00011060857],"domain_scores_gemma":[0.99847,0.0009925073,0.00020189563,0.00013042412,0.0000893035,0.00011589965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007812626,0.0004434936,0.0007295676,0.000433886,0.0009077685,0.0009320594,0.0010307014,0.0006900734,0.0020480715],"category_scores_gemma":[0.0028888036,0.00030132913,0.00066346367,0.00082764094,0.0010494691,0.0014208095,0.0016939492,0.0007668363,0.00038609284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031982528,0.000055680375,0.0012401871,0.00018448842,0.00003648416,0.0004084254,0.00019892387,0.85784876,0.0038367764,0.11014502,0.002642298,0.023083124],"study_design_scores_gemma":[0.000040736664,0.000058371166,0.0002822267,0.00001290113,0.0000070949823,0.000104853694,0.000119193865,0.8955332,0.0010578951,0.10055227,0.002215748,0.000015526866],"about_ca_topic_score_codex":0.0025409854,"about_ca_topic_score_gemma":0.0021447765,"teacher_disagreement_score":0.0025409854,"about_ca_system_score_codex":0.00075591693,"about_ca_system_score_gemma":0.0006147121,"threshold_uncertainty_score":0.0068514943},"labels":[],"label_agreement":null},{"id":"W4302609198","doi":"10.1007/s00446-014-0216-5","title":"Deterministic polynomial approach in the plane","year":2014,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Mathematics; Polynomial; Plane (geometry); Geometry; Mathematical analysis","score_opus":0.017766937511078752,"score_gpt":0.2474252493438052,"score_spread":0.22965831183272645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302609198","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0140960235,0.0013025108,0.96707946,0.0018376817,0.00014899262,0.00003777794,0.000190267,0.00023245356,0.015074767],"genre_scores_gemma":[0.58711064,0.002666116,0.3824858,0.0006172451,0.0007027178,0.00028212133,0.0005302862,0.00042899518,0.025176095],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987664,0.0004380015,0.000041022526,0.00022872999,0.0003252593,0.00020051851],"domain_scores_gemma":[0.99624205,0.0027021675,0.00015434335,0.000444256,0.0003125964,0.00014457406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015746835,0.0008954377,0.0016761484,0.0008431322,0.00073235855,0.002075173,0.0019132402,0.0014177846,0.0068757175],"category_scores_gemma":[0.007685785,0.00060454255,0.0009938689,0.0014935269,0.0016515944,0.0034952261,0.0020923694,0.0033727733,0.00092012866],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001613285,0.000074311494,0.00031494032,0.00016764426,0.000046920533,0.00003778111,0.00005773956,0.2511245,0.0005830822,0.709961,0.0075549795,0.029915765],"study_design_scores_gemma":[0.00003983997,0.000014683811,0.00008159116,0.000012575227,0.0000112532625,0.000014695243,0.000014488332,0.6461815,0.00018269167,0.35080034,0.0026407316,0.0000057033217],"about_ca_topic_score_codex":0.0042159082,"about_ca_topic_score_gemma":0.0045876405,"teacher_disagreement_score":0.0068757175,"about_ca_system_score_codex":0.0025852188,"about_ca_system_score_gemma":0.0018112047,"threshold_uncertainty_score":0.023001611},"labels":[],"label_agreement":null},{"id":"W4302799385","doi":"10.1007/978-3-031-02008-7_6","title":"Flocking","year":2012,"lang":"en","type":"book-chapter","venue":"Synthesis lectures on distributed computing theory","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Flocking (texture); Robot; Mobile robot; Computer science; Artificial intelligence; Human–computer interaction; Swarm robotics; Visual arts; Art","score_opus":0.019716228258574123,"score_gpt":0.23803860213713104,"score_spread":0.2183223738785569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4302799385","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009436572,0.0137978885,0.17254156,0.0021346991,0.0029910489,0.00008059867,0.00025800182,0.0007773836,0.79798216],"genre_scores_gemma":[0.12279402,0.010207572,0.05460209,0.00086656655,0.0013531684,0.00018542015,0.00065594056,0.00081793655,0.80851734],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985826,0.00001539445,0.0000046143546,0.00004431181,0.000057326353,0.00001998717],"domain_scores_gemma":[0.9998921,0.000025889147,0.000006343174,0.000029589237,0.000029374321,0.000016700693],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017545423,0.0008250956,0.0005876584,0.0012341988,0.0010056219,0.0012685915,0.0006645863,0.0008442091,0.036969762],"category_scores_gemma":[0.00071577146,0.00032257795,0.00037056176,0.0007863228,0.0011591928,0.0023164484,0.0013100591,0.0014426593,0.00920706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003395438,0.00002538994,0.000104008956,0.00015150657,0.000013224099,0.000049251143,0.00021769166,0.004394828,0.003435428,0.6373342,0.08617651,0.26806393],"study_design_scores_gemma":[0.000013206452,0.000046706773,0.0003653999,0.00018394734,0.000013522433,0.0002306715,0.00009366667,0.012771588,0.0027225977,0.44962174,0.5339115,0.00002540796],"about_ca_topic_score_codex":0.0008510886,"about_ca_topic_score_gemma":0.0010286802,"teacher_disagreement_score":0.036969762,"about_ca_system_score_codex":0.00072385557,"about_ca_system_score_gemma":0.00031437114,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4311633653","doi":"10.1007/s00453-022-01075-y","title":"Algorithms for p-Faulty Search on a Half-Line","year":2022,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Monotone polygon; Theory of computation; Bernoulli trial; Conjecture; Mathematics; Combinatorics; Monotonic function; Sequence (biology); Upper and lower bounds; Line (geometry); Algorithm; Discrete mathematics; Path (computing); Search problem; Computer science","score_opus":0.061667502694890054,"score_gpt":0.324226032777739,"score_spread":0.2625585300828489,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4311633653","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025180073,0.00037889363,0.9603579,0.0009902774,0.0001331378,0.00013802153,0.00024061998,0.0017963202,0.010784697],"genre_scores_gemma":[0.30578974,0.00023587616,0.68110937,0.00039729563,0.000118835946,0.0004235491,0.00070634246,0.00061205373,0.010606931],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9983956,0.0006117722,0.00010995974,0.00031723676,0.0003281602,0.0002372871],"domain_scores_gemma":[0.9938471,0.0035693117,0.000295832,0.0015027156,0.0005457652,0.0002391876],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022556065,0.0010466658,0.0013151366,0.0011830459,0.0014942695,0.002298488,0.0033781566,0.0025144888,0.017129447],"category_scores_gemma":[0.012802904,0.00074912654,0.0012676349,0.0016271237,0.0018147808,0.004530418,0.003574975,0.0028125406,0.0025762254],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010287225,0.0003598769,0.002060339,0.00039558302,0.0001249665,0.00023997239,0.00030198012,0.44496313,0.0022584605,0.21266516,0.028916191,0.3066855],"study_design_scores_gemma":[0.00012311156,0.0000660645,0.00009420568,0.000024716372,0.000021008043,0.00006367573,0.000046694295,0.8490986,0.00087485026,0.14673199,0.0028449672,0.000010140551],"about_ca_topic_score_codex":0.0026203154,"about_ca_topic_score_gemma":0.003125471,"teacher_disagreement_score":0.017129447,"about_ca_system_score_codex":0.001559207,"about_ca_system_score_gemma":0.0019325431,"threshold_uncertainty_score":0.057303727},"labels":[],"label_agreement":null},{"id":"W4312335575","doi":"10.2139/ssrn.4240819","title":"A Distributed Approximation Algorithm for the Total Dominating Set Problem","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Dominating set; Algorithm; Set (abstract data type); Approximation algorithm; Computer science; Mathematics; Mathematical optimization; Theoretical computer science; Graph","score_opus":0.011870500548152621,"score_gpt":0.2517961040918203,"score_spread":0.23992560354366768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312335575","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015680114,0.00044159786,0.97836417,0.00045418792,0.00021696248,0.000120217286,0.00012693796,0.0005758566,0.004019924],"genre_scores_gemma":[0.35385042,0.0005043504,0.6365858,0.00032794208,0.00021264252,0.00046835077,0.00054598384,0.00019899686,0.007305402],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987153,0.00037209108,0.000055184642,0.00028938713,0.00039035737,0.00017767044],"domain_scores_gemma":[0.99811965,0.0010877792,0.00009740417,0.00027820838,0.0002689351,0.00014793119],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016918393,0.0011595223,0.0021286074,0.0009079345,0.0009151951,0.0016300613,0.0028616101,0.0014916614,0.0038591267],"category_scores_gemma":[0.00464308,0.00050744764,0.0008648229,0.0019482475,0.0007103538,0.0020730451,0.002361727,0.0017961407,0.00079450017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00076025276,0.0003817408,0.00053409836,0.0002728821,0.00012622555,0.000093533,0.00016912688,0.68653846,0.0038808768,0.037737347,0.011686522,0.25781897],"study_design_scores_gemma":[0.00013965649,0.00010646882,0.00009243143,0.000010282997,0.000028035727,0.00006040985,0.000029845842,0.9760519,0.0006145759,0.02094146,0.001916266,0.000008682272],"about_ca_topic_score_codex":0.0022695744,"about_ca_topic_score_gemma":0.0034775976,"teacher_disagreement_score":0.0038591267,"about_ca_system_score_codex":0.0016156466,"about_ca_system_score_gemma":0.0022919409,"threshold_uncertainty_score":0.012910068},"labels":[],"label_agreement":null},{"id":"W4312532973","doi":"10.1007/978-3-031-22050-0_6","title":"Triangle Evacuation of 2 Agents in the Wireless Model","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Equilateral triangle; Combinatorics; Perimeter; Mathematics; Point (geometry); Infimum and supremum; Enhanced Data Rates for GSM Evolution; Square (algebra); Unit square; Incircle and excircles of a triangle; Upper and lower bounds; Computer science; Discrete mathematics; Geometry; Artificial intelligence","score_opus":0.05684704296843068,"score_gpt":0.2945540914198583,"score_spread":0.2377070484514276,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312532973","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15173231,0.0015983233,0.659411,0.0068932427,0.0011227129,0.0002746508,0.0012327508,0.00035532998,0.1773797],"genre_scores_gemma":[0.8180491,0.0016115408,0.04561174,0.0008114397,0.0003673023,0.0003563897,0.00061726524,0.00024390077,0.13233136],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949646,0.00016745421,0.000019039406,0.00008744189,0.00008057499,0.00014900646],"domain_scores_gemma":[0.9988446,0.0005892331,0.00013689611,0.000086277076,0.00010069895,0.00024214755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005354086,0.0009368641,0.0014988348,0.0007091522,0.0014610529,0.0019756518,0.0030527185,0.0037470045,0.013900307],"category_scores_gemma":[0.003622711,0.00078360416,0.0012725015,0.0011639295,0.0017598011,0.003195905,0.0028568914,0.0025767537,0.001517911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018614314,0.000051183608,0.00027757953,0.00011680834,0.00003189859,0.0004457122,0.00021947398,0.5756178,0.0007429065,0.41001537,0.006958027,0.0053370288],"study_design_scores_gemma":[0.00007139523,0.000044504028,0.00008961145,0.000018156377,0.00001526889,0.000102580256,0.00014751988,0.8577788,0.0001520657,0.13717394,0.0043856865,0.000020506308],"about_ca_topic_score_codex":0.012105072,"about_ca_topic_score_gemma":0.006921315,"teacher_disagreement_score":0.013900307,"about_ca_system_score_codex":0.0014356942,"about_ca_system_score_gemma":0.0010034967,"threshold_uncertainty_score":0.04650116},"labels":[],"label_agreement":null},{"id":"W4313203312","doi":"10.1109/focs54457.2022.00064","title":"Maximum Flow and Minimum-Cost Flow in Almost-Linear Time","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":132,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Minimum-cost flow problem; Mathematics; Minimum cut; Separable space; Combinatorics; Amortized analysis; Bounded function; Regular polygon; Scaling; Time complexity; Maximum flow problem; Flow (mathematics); Discrete mathematics; Directed graph; Approximation algorithm; Mathematical optimization; Flow network; Computer science; Data structure","score_opus":0.013994209562291294,"score_gpt":0.2647044641196495,"score_spread":0.2507102545573582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313203312","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037795186,0.0002888965,0.94595224,0.0006176977,0.00007642456,0.00017629364,0.0008633588,0.006320792,0.007909143],"genre_scores_gemma":[0.25612992,0.00015840396,0.7361989,0.00021955874,0.000072559975,0.00025147916,0.002198395,0.00097480137,0.0037959057],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99894947,0.00017723076,0.00006627172,0.00031700585,0.00030240402,0.00018762998],"domain_scores_gemma":[0.99783945,0.0011207901,0.00018698409,0.00047833152,0.00029011414,0.00008426804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008325835,0.0017040654,0.0009124433,0.0011049459,0.0007990664,0.0017134618,0.0016825318,0.0014146825,0.008048496],"category_scores_gemma":[0.0070821866,0.00065632875,0.0010492691,0.0015527059,0.00084753067,0.0037563895,0.0014120123,0.0018137039,0.0020346467],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061319675,0.0002564256,0.0022163393,0.0003879997,0.00010311443,0.00013981177,0.00024711603,0.54354084,0.00979362,0.06977117,0.02081807,0.35211232],"study_design_scores_gemma":[0.00005676206,0.00003104318,0.00030683086,0.00001630047,0.000014639153,0.000059703623,0.00004459832,0.9175959,0.00338469,0.075881295,0.0025953818,0.000012748615],"about_ca_topic_score_codex":0.006984792,"about_ca_topic_score_gemma":0.009575842,"teacher_disagreement_score":0.008048496,"about_ca_system_score_codex":0.0021676177,"about_ca_system_score_gemma":0.0029751728,"threshold_uncertainty_score":0.026924908},"labels":[],"label_agreement":null},{"id":"W4313349371","doi":"10.1007/978-3-031-20350-3_13","title":"Two-Stage Submodular Maximization Under Knapsack and Matroid Constraints","year":2022,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Submodular set function; Matroid; Knapsack problem; Combinatorics; Constraint (computer-aided design); Maximization; Mathematics; Monotone polygon; Similarity (geometry); Discrete mathematics; Mathematical optimization; Computer science; Artificial intelligence","score_opus":0.021047011313328538,"score_gpt":0.2545204206725667,"score_spread":0.23347340935923816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313349371","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01441692,0.00057334354,0.95487493,0.00032072648,0.00008777076,0.0001244768,0.00037792724,0.00030584357,0.028918013],"genre_scores_gemma":[0.3192197,0.0015631648,0.6069951,0.00028162185,0.000255946,0.0005230134,0.0010092641,0.00059233233,0.06955983],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924517,0.0002204649,0.000030446316,0.00015481997,0.00020207916,0.00014707433],"domain_scores_gemma":[0.9992612,0.00041498698,0.0000641549,0.000101375015,0.000098177254,0.000060112616],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011193602,0.001467326,0.0013593044,0.00052401365,0.00046991667,0.0018265296,0.0021877121,0.0014813353,0.009355797],"category_scores_gemma":[0.0026310259,0.0010516049,0.0012285057,0.0017678131,0.00077220006,0.0033447694,0.0019501909,0.0025892647,0.001966271],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039994362,0.00040622495,0.00038206822,0.0009686984,0.000094745716,0.00032614364,0.00021262055,0.43050784,0.016259171,0.33546573,0.025086738,0.18989009],"study_design_scores_gemma":[0.00004659387,0.00015446045,0.0003481049,0.000048237045,0.000022731741,0.0001539177,0.000049571292,0.8083967,0.0048414674,0.17849515,0.0074065924,0.00003648294],"about_ca_topic_score_codex":0.0015149321,"about_ca_topic_score_gemma":0.0020036432,"teacher_disagreement_score":0.009355797,"about_ca_system_score_codex":0.001001272,"about_ca_system_score_gemma":0.001177566,"threshold_uncertainty_score":0.03129822},"labels":[],"label_agreement":null},{"id":"W4313598463","doi":"10.4230/lipics.mfcs.2023.13","title":"Rényi-Ulam Games and Online Computation with Imperfect Advice","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Agence Nationale de la Recherche","keywords":"Advice (programming); Imperfect; Computer science; Robustification; Perfect information; Competitive analysis; Computation; Upper and lower bounds; Online algorithm; Bidding; Overhead (engineering); Exploit; Knapsack problem; Theoretical computer science; Algorithm; Mathematics; Mathematical economics; Artificial intelligence; Computer security","score_opus":0.07780239002495741,"score_gpt":0.2124326388804439,"score_spread":0.13463024885548647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313598463","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.103970654,0.00043680094,0.87978405,0.0021514024,0.000112822214,0.0001187556,0.00014915473,0.0002796334,0.012996742],"genre_scores_gemma":[0.9241799,0.00032379464,0.068406366,0.00040473018,0.00013780406,0.00021836991,0.000068951165,0.00007037671,0.0061896234],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954015,0.0022017944,0.00016231662,0.0006992074,0.0009056834,0.0006294512],"domain_scores_gemma":[0.9768107,0.018256221,0.0019891465,0.0016038057,0.0006543618,0.0006858155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041124127,0.0015105596,0.0015703966,0.00087192503,0.00080058427,0.0022051255,0.0026254486,0.0023807532,0.003733215],"category_scores_gemma":[0.027027478,0.000598166,0.0010263665,0.00097054645,0.004136857,0.004970172,0.002257409,0.0038637873,0.00042249437],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021949317,0.00008772383,0.0005921265,0.00012178098,0.000057671095,0.0001691116,0.00021368192,0.36025578,0.0016868516,0.62647444,0.0010184944,0.009102887],"study_design_scores_gemma":[0.000036767153,0.000051668107,0.00008859849,0.000012633096,0.000010065548,0.000027081072,0.000020741592,0.73456,0.00056046864,0.2640647,0.0005520162,0.00001529182],"about_ca_topic_score_codex":0.0024460603,"about_ca_topic_score_gemma":0.0018583809,"teacher_disagreement_score":0.0041124127,"about_ca_system_score_codex":0.0024979773,"about_ca_system_score_gemma":0.001546513,"threshold_uncertainty_score":0.021748722},"labels":[],"label_agreement":null},{"id":"W4315488924","doi":"10.1109/cdc51059.2022.9993099","title":"Online Multi-Robot Task Assignment with Stochastic Blockages","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 61st Conference on Decision and Control (CDC)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Task (project management); Robot; Computer science; Routing (electronic design automation); Mathematical optimization; Assignment problem; Distributed computing; Path (computing); Greedy algorithm; Motion planning; Online and offline; Work (physics); Real-time computing; Artificial intelligence; Computer network; Algorithm; Engineering; Mathematics","score_opus":0.035682832148866375,"score_gpt":0.2750950731126994,"score_spread":0.239412240963833,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315488924","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08815653,0.0002837968,0.9078153,0.00023808688,0.000052271225,0.000121750476,0.0001388922,0.00050382037,0.0026895828],"genre_scores_gemma":[0.9093345,0.00015898702,0.08575893,0.00006533232,0.00003624471,0.00016648798,0.00020945197,0.000100079444,0.0041700527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990183,0.00028642648,0.0000326488,0.0002168342,0.00016856735,0.0002772421],"domain_scores_gemma":[0.99726546,0.0016413964,0.00043749073,0.0002658489,0.00012747968,0.00026233704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010495482,0.0009623262,0.001430314,0.0003956642,0.0005874388,0.00094804895,0.0015595611,0.001230234,0.004200947],"category_scores_gemma":[0.0038823518,0.0006717905,0.00071605324,0.0007234349,0.00094262953,0.0021268346,0.0014798859,0.0016738749,0.0004848835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068812486,0.000028579174,0.00016272272,0.00001864319,0.000008351812,0.000028664392,0.000016143138,0.99178493,0.00036449987,0.003051472,0.0002059827,0.004261203],"study_design_scores_gemma":[0.0000070718993,0.000029822231,0.000058706017,0.0000013189494,0.0000019712804,0.000008401669,0.0000069191356,0.9972632,0.00013598379,0.002317078,0.0001671462,0.0000023281696],"about_ca_topic_score_codex":0.007969482,"about_ca_topic_score_gemma":0.005497501,"teacher_disagreement_score":0.007969482,"about_ca_system_score_codex":0.0012396814,"about_ca_system_score_gemma":0.0015577022,"threshold_uncertainty_score":0.015846133},"labels":[],"label_agreement":null},{"id":"W4315589162","doi":"10.48550/arxiv.2301.03534","title":"The one-visibility Localization game","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Upper and lower bounds; Visibility; Combinatorics; Isoperimetric inequality; Mathematics; Constant (computer programming); Multiplicative function; Order (exchange); Discrete mathematics; Tree (set theory); Computer science; Mathematical analysis; Physics","score_opus":0.15790263674329108,"score_gpt":0.21962362572479235,"score_spread":0.061720988981501274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4315589162","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1985053,0.0003717138,0.7509146,0.0026595343,0.00011465845,0.00024794563,0.00078978034,0.0008267522,0.04556974],"genre_scores_gemma":[0.8829859,0.00028449466,0.099066205,0.00045311425,0.000063054875,0.00027447994,0.0004897583,0.00022283269,0.016160177],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99850875,0.0004320772,0.000060647915,0.00040073707,0.00020900127,0.0003886524],"domain_scores_gemma":[0.9964104,0.001864728,0.0002560425,0.0006798382,0.00022225761,0.0005666967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009974098,0.0008414633,0.0009403197,0.00042231823,0.0012893357,0.0022043074,0.002252951,0.0012697424,0.010684581],"category_scores_gemma":[0.0061247223,0.0005161788,0.00067735073,0.0005904315,0.002389626,0.00664629,0.0036742836,0.0030168232,0.0010998835],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00046069693,0.00017351784,0.001553768,0.00021395474,0.000045420682,0.00035131566,0.00067511236,0.061765056,0.010209834,0.8759092,0.008441751,0.04020025],"study_design_scores_gemma":[0.00012563703,0.0002364816,0.0008796997,0.000053279906,0.000044294153,0.0004088443,0.00047031604,0.33667228,0.007101791,0.63754827,0.016396124,0.00006293265],"about_ca_topic_score_codex":0.0024573372,"about_ca_topic_score_gemma":0.0024078416,"teacher_disagreement_score":0.010684581,"about_ca_system_score_codex":0.0015979656,"about_ca_system_score_gemma":0.0012657878,"threshold_uncertainty_score":0.035743475},"labels":[],"label_agreement":null},{"id":"W4318023126","doi":"10.1007/978-3-031-25211-2_7","title":"Rectilinear Voronoi Games with a Simple Rectilinear Obstacle in Plane","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Voronoi diagram; Polygon (computer graphics); Regular polygon; Simple (philosophy); Plane (geometry); Obstacle; Computer science; Metric (unit); Combinatorics; Euclidean geometry; Convex polygon; Mathematics; Geometry; Telecommunications; Geography","score_opus":0.025080428977623633,"score_gpt":0.26063191313751566,"score_spread":0.23555148415989202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4318023126","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18405098,0.0010629384,0.60387266,0.0012481596,0.0004086772,0.00031421747,0.000638006,0.00026540304,0.20813894],"genre_scores_gemma":[0.8085474,0.0010279005,0.12687756,0.00018917842,0.000121565216,0.00021688378,0.00024649294,0.00013487198,0.06263815],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99947757,0.0001846399,0.000022249584,0.0000714137,0.00013776237,0.000106426276],"domain_scores_gemma":[0.9994574,0.000278825,0.000062795574,0.00005148937,0.000043646898,0.00010589121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00034106427,0.0008506196,0.0013695596,0.00044296545,0.000865823,0.0022185694,0.0018554643,0.0018253304,0.0072368635],"category_scores_gemma":[0.0017135327,0.000573124,0.0008449511,0.0008348866,0.0013573226,0.002376952,0.002348566,0.0013789487,0.0009473861],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000121279576,0.00005628123,0.00016735958,0.00011635413,0.000029706898,0.00022187513,0.00012281175,0.20454714,0.0017297493,0.7780927,0.0037266326,0.011068105],"study_design_scores_gemma":[0.00008494679,0.00006698466,0.00015963471,0.000035640525,0.000016803726,0.00018713967,0.00012546686,0.4912526,0.0006689444,0.49630186,0.011071453,0.000028504073],"about_ca_topic_score_codex":0.003205433,"about_ca_topic_score_gemma":0.0036177454,"teacher_disagreement_score":0.0072368635,"about_ca_system_score_codex":0.0008758215,"about_ca_system_score_gemma":0.00084467663,"threshold_uncertainty_score":0.024209738},"labels":[],"label_agreement":null},{"id":"W4319304668","doi":"10.1007/s10044-023-01131-5","title":"Learning automata-based partitioning algorithms for stochastic grouping problems with non-equal partition sizes","year":2023,"lang":"en","type":"article","venue":"Pattern Analysis and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Partition (number theory); Theoretical computer science; Heuristic; Key (lock); Context (archaeology); Reinforcement learning; Learning automata; Constraint (computer-aided design); Automaton; Artificial intelligence; Algorithm; Mathematics","score_opus":0.027467271016067208,"score_gpt":0.28809909852615057,"score_spread":0.26063182751008335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4319304668","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015794387,0.00019643556,0.9824501,0.00012558441,0.000036498248,0.00006923125,0.00005082336,0.00033885307,0.00093803083],"genre_scores_gemma":[0.42666677,0.00033040709,0.568007,0.00025857205,0.00007719494,0.0005931416,0.00054469483,0.0002902998,0.0032320847],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988715,0.00037193496,0.00011105023,0.00030737603,0.00020961765,0.00012848238],"domain_scores_gemma":[0.9900817,0.0077127195,0.0004985294,0.0005681887,0.0008573166,0.0002815009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023682253,0.0010206228,0.0020333398,0.0015578853,0.0010283294,0.0017033386,0.0029458895,0.0019429178,0.0039146524],"category_scores_gemma":[0.0107974345,0.000954613,0.0014885335,0.0013908665,0.0013591672,0.003069373,0.002582628,0.002286255,0.0006736889],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013261744,0.00010363727,0.00092654495,0.000103748716,0.00006714241,0.000029421917,0.00015034534,0.8706801,0.0012383942,0.021003311,0.001338918,0.104225904],"study_design_scores_gemma":[0.0000076000506,0.000015983689,0.00004000439,0.000006391058,0.0000057983343,0.000006113577,0.000010734995,0.99020994,0.00016491924,0.009393769,0.00013526031,0.0000035055396],"about_ca_topic_score_codex":0.0072417576,"about_ca_topic_score_gemma":0.009795279,"teacher_disagreement_score":0.0072417576,"about_ca_system_score_codex":0.0017272087,"about_ca_system_score_gemma":0.001960479,"threshold_uncertainty_score":0.0143992305},"labels":[],"label_agreement":null},{"id":"W4320085883","doi":"10.1016/j.automatica.2023.110873","title":"From drinking philosophers to asynchronous path-following robots","year":2023,"lang":"en","type":"article","venue":"Automatica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Office of Naval Research; National Sleep Foundation; Defense Advanced Research Projects Agency; University of Southern California; National Aeronautics and Space Administration; Simon Fraser University; National Science Foundation","keywords":"Asynchronous communication; Robot; Asynchrony (computer programming); Deadlock; Computer science; Distributed computing; Path (computing); State (computer science); Deadlock prevention algorithms; Motion planning; Resource allocation; Collision avoidance; Resource (disambiguation); Control (management); Mathematical optimization; Collision; Artificial intelligence; Algorithm; Computer security; Computer network; Mathematics","score_opus":0.02461861265299646,"score_gpt":0.28312572606627223,"score_spread":0.25850711341327576,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4320085883","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06443761,0.001240564,0.8774003,0.00533389,0.00032580443,0.000051520303,0.00012795653,0.00034748143,0.050735045],"genre_scores_gemma":[0.764716,0.0012758435,0.19188966,0.0010649635,0.00036773074,0.00015184713,0.00015736057,0.00025588638,0.040120687],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993267,0.0003177762,0.000028442366,0.0001691001,0.00009931765,0.00005864991],"domain_scores_gemma":[0.99760145,0.0016368807,0.00015270177,0.0002786748,0.00015797318,0.00017235836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011439213,0.0004929745,0.0005775493,0.000571166,0.001308751,0.002191834,0.0013753742,0.0021768224,0.0107646035],"category_scores_gemma":[0.0067607383,0.00068495097,0.0007667223,0.00079330796,0.0041162656,0.005293977,0.0030164677,0.003071533,0.0008035298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000041483912,0.00002362314,0.0002392944,0.000052644216,0.000010544258,0.00004014781,0.0002530518,0.019681046,0.0004212847,0.9674356,0.0012841157,0.010517178],"study_design_scores_gemma":[0.000019293999,0.000017521475,0.00008598224,0.00001212733,0.000008039339,0.000020096191,0.00009524085,0.06095779,0.00023739347,0.93542624,0.003111638,0.0000087160815],"about_ca_topic_score_codex":0.0022111423,"about_ca_topic_score_gemma":0.0026594049,"teacher_disagreement_score":0.0107646035,"about_ca_system_score_codex":0.0009538306,"about_ca_system_score_gemma":0.0009972132,"threshold_uncertainty_score":0.03601116},"labels":[],"label_agreement":null},{"id":"W4322576860","doi":"10.1016/b978-0-32-391244-0.00013-9","title":"Modeling active tracers","year":2023,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science","score_opus":0.043333874872112946,"score_gpt":0.26679137004530185,"score_spread":0.2234574951731889,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4322576860","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009836391,0.002458448,0.852298,0.00060317,0.00041644118,0.0000631853,0.00042944172,0.001601987,0.13229288],"genre_scores_gemma":[0.40733638,0.005677244,0.20763196,0.00044719124,0.00035043043,0.00039451203,0.0012949868,0.0017021161,0.37516513],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998049,0.000037096357,0.000007691909,0.000047708814,0.000078294586,0.000024294513],"domain_scores_gemma":[0.9996661,0.00014593794,0.00003223296,0.00005964674,0.00006006768,0.000036129753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037350712,0.00087836874,0.00085343956,0.0008545048,0.0005994141,0.0029989732,0.0017478556,0.0020905402,0.022466686],"category_scores_gemma":[0.0016843715,0.0006948715,0.00057152455,0.00092474365,0.0010523675,0.0023895202,0.0016159011,0.0012829443,0.004941846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005547589,0.000054203094,0.00044298402,0.00014047566,0.000029186442,0.00012448196,0.000117864125,0.42632174,0.0044642626,0.4738964,0.014552431,0.079800524],"study_design_scores_gemma":[0.000012270437,0.000018242195,0.000090390764,0.00003485712,0.000011007123,0.0001039024,0.000026241694,0.8193,0.0015141034,0.14151265,0.037360623,0.000015740356],"about_ca_topic_score_codex":0.0029722604,"about_ca_topic_score_gemma":0.0019457919,"teacher_disagreement_score":0.022466686,"about_ca_system_score_codex":0.0009445727,"about_ca_system_score_gemma":0.000812199,"threshold_uncertainty_score":0.07515854},"labels":[],"label_agreement":null},{"id":"W4323659995","doi":"10.1016/j.ipl.2023.106391","title":"Optimal circle search despite the presence of faulty robots","year":2023,"lang":"en","type":"article","venue":"Information Processing Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Search and rescue; Computer science; Linear search; Crash; Search algorithm; Algorithm; Mobile robot; Artificial intelligence","score_opus":0.024219429274543396,"score_gpt":0.2745886169192998,"score_spread":0.2503691876447564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4323659995","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47671056,0.0011131822,0.49435464,0.0021532197,0.00018994423,0.000052201,0.00013953734,0.0010348067,0.02425194],"genre_scores_gemma":[0.9686581,0.00007572864,0.027729716,0.00006810019,0.000021579408,0.000023689541,0.00004968973,0.00006076384,0.0033126834],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995289,0.00014013905,0.000021889764,0.000107712,0.00011642481,0.000084910396],"domain_scores_gemma":[0.9948257,0.0031712635,0.00052159786,0.0005192119,0.0006298293,0.00033241816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009101216,0.00043313057,0.0011696818,0.0005788998,0.0006990833,0.0009267379,0.0009164839,0.0019750774,0.0018575698],"category_scores_gemma":[0.008788309,0.0004524903,0.00022836032,0.0007959044,0.0013550377,0.0014917651,0.0011968048,0.00069860177,0.0004880476],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00096084044,0.00006209468,0.0008313811,0.00011073437,0.000048499838,0.0003095501,0.0002144831,0.91469085,0.0069825985,0.0441769,0.0034547648,0.02815728],"study_design_scores_gemma":[0.000033586875,0.000054526194,0.00020829911,0.000004893571,0.0000048535117,0.00003971415,0.000028876073,0.9860848,0.00145678,0.011653618,0.00041975113,0.000010299538],"about_ca_topic_score_codex":0.003449551,"about_ca_topic_score_gemma":0.0022931297,"teacher_disagreement_score":0.003449551,"about_ca_system_score_codex":0.0007663034,"about_ca_system_score_gemma":0.0009410643,"threshold_uncertainty_score":0.006858945},"labels":[],"label_agreement":null},{"id":"W4327518366","doi":"10.1007/978-3-030-54621-2_739-1","title":"Bilevel Knapsack Problems","year":2023,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Optimization","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Knapsack problem; Bilevel optimization; Computer science; Mathematics; Mathematical optimization; Optimization problem","score_opus":0.029844876455141705,"score_gpt":0.24090091525612406,"score_spread":0.21105603880098237,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4327518366","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021244963,0.022577677,0.41010135,0.00114738,0.0014844944,0.000096630654,0.0008377984,0.0011809072,0.56044924],"genre_scores_gemma":[0.049347587,0.049608782,0.2700201,0.0010491468,0.0011347807,0.00044602348,0.0035965575,0.0015353743,0.6232617],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999574,0.000056536654,0.000022538323,0.00006876499,0.00023810494,0.000040136245],"domain_scores_gemma":[0.9997242,0.00010956107,0.000017708586,0.00004389003,0.00008302797,0.000021555017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003233187,0.0018649251,0.0015309601,0.0010354626,0.0007673531,0.0043073012,0.0014688455,0.0013075423,0.046238028],"category_scores_gemma":[0.0013559103,0.0007877328,0.00065859134,0.0035235258,0.0008201435,0.002324447,0.0019702916,0.0029260751,0.026849888],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006739877,0.00013619353,0.00014019487,0.0010072279,0.00004849003,0.00014234219,0.00010479872,0.05754928,0.0020611486,0.31582958,0.15239719,0.47051618],"study_design_scores_gemma":[0.000020444375,0.000046335786,0.00019001585,0.00048473125,0.000023733128,0.0003289537,0.000095308525,0.07654866,0.0019748432,0.36535132,0.5548938,0.000041772277],"about_ca_topic_score_codex":0.0010689268,"about_ca_topic_score_gemma":0.0017064875,"teacher_disagreement_score":0.046238028,"about_ca_system_score_codex":0.000668848,"about_ca_system_score_gemma":0.0009831707,"threshold_uncertainty_score":0.15468162},"labels":[],"label_agreement":null},{"id":"W4327814720","doi":"10.1145/3588437","title":"Almost-Optimal Deterministic Treasure Hunt in Unweighted Graphs","year":2023,"lang":"en","type":"article","venue":"ACM Transactions on Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Treasure; Combinatorics; Mathematics; Graph; Discrete mathematics; Node (physics); Algorithm; Computer science","score_opus":0.035051444683297794,"score_gpt":0.288405559114852,"score_spread":0.2533541144315542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4327814720","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32646286,0.00070454605,0.65921384,0.00059159484,0.000069707705,0.00020593485,0.0005626508,0.0012340888,0.01095475],"genre_scores_gemma":[0.876715,0.00036786354,0.117359884,0.00018438006,0.00003504574,0.0001307423,0.0006419678,0.00017811076,0.00438701],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99848855,0.00030904377,0.00007468283,0.00050831976,0.00017632714,0.0004431997],"domain_scores_gemma":[0.9938212,0.0039937724,0.00062716455,0.00082295795,0.0002734897,0.00046146172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009214446,0.0011727118,0.0018051474,0.0005489128,0.0007309563,0.0013133147,0.003021491,0.0018635642,0.0027393275],"category_scores_gemma":[0.006778449,0.0009761713,0.0012706618,0.0007288286,0.0014177158,0.0035619067,0.0020720353,0.0014495945,0.0005249232],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040879476,0.00014587109,0.00080111745,0.00021472806,0.00005933631,0.00016704947,0.00013700212,0.94304067,0.004934687,0.03223132,0.0015447193,0.016314734],"study_design_scores_gemma":[0.00005783609,0.00014415575,0.00021165854,0.000013855716,0.000018605258,0.000076165394,0.000047985126,0.9491847,0.001030133,0.04865787,0.00053893146,0.000018038889],"about_ca_topic_score_codex":0.0039301603,"about_ca_topic_score_gemma":0.003734079,"teacher_disagreement_score":0.0039301603,"about_ca_system_score_codex":0.0014820725,"about_ca_system_score_gemma":0.0011461399,"threshold_uncertainty_score":0.010753214},"labels":[],"label_agreement":null},{"id":"W4364377325","doi":"10.1007/s10044-023-01163-x","title":"The object migration automata: its field, scope, applications, and future research challenges","year":2023,"lang":"en","type":"article","venue":"Pattern Analysis and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Automaton; Artificial intelligence; Scope (computer science); Benchmark (surveying); Cellular automaton; Theoretical computer science; Field (mathematics); Data science; Machine learning; Programming language; Mathematics","score_opus":0.04986487048192982,"score_gpt":0.34974039894459075,"score_spread":0.2998755284626609,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4364377325","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.058918964,0.32309788,0.45482394,0.114368394,0.0028439686,0.00014571821,0.0006666298,0.0009636728,0.044170838],"genre_scores_gemma":[0.49376115,0.22560802,0.25110677,0.005424808,0.0075642657,0.00030948443,0.0007815591,0.00030538085,0.015138501],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979354,0.000697692,0.00015210689,0.00062008045,0.00045479508,0.0001399083],"domain_scores_gemma":[0.9832214,0.011187022,0.0006705517,0.0017046616,0.0024688507,0.0007475004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050987103,0.0006768855,0.00220664,0.0020698751,0.0011723689,0.008772012,0.0033700797,0.0035436533,0.0062348624],"category_scores_gemma":[0.011595373,0.00057242194,0.0010237659,0.0042931847,0.0048601725,0.013349451,0.002158681,0.0034310385,0.0016491119],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013399278,0.00022510858,0.0047004838,0.0010506443,0.000059641297,0.00011917258,0.0004416947,0.014001348,0.0011531458,0.514998,0.01481983,0.44829682],"study_design_scores_gemma":[0.000018048846,0.0001195763,0.001221008,0.00050518115,0.000041543135,0.0004985888,0.0011237226,0.10202422,0.0008687834,0.83431256,0.059213724,0.00005310677],"about_ca_topic_score_codex":0.002583385,"about_ca_topic_score_gemma":0.0025627972,"teacher_disagreement_score":0.008772012,"about_ca_system_score_codex":0.0020719436,"about_ca_system_score_gemma":0.0034637544,"threshold_uncertainty_score":0.026964903},"labels":[],"label_agreement":null},{"id":"W4366733065","doi":"10.48550/arxiv.2304.10028","title":"Minimizing the Size of the Uncertainty Regions for Centers of Moving Entities","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Institute for Computing, Information and Cognitive Systems","keywords":"Center (category theory); Centroid; Bounded function; Competitive analysis; Scheduling (production processes); Object (grammar); Computer science; Facility location problem; Algorithm; Mathematics; Mathematical optimization; Upper and lower bounds; Artificial intelligence","score_opus":0.12959671890829533,"score_gpt":0.21220062471596027,"score_spread":0.08260390580766494,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366733065","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13181311,0.001194963,0.8620029,0.00088855135,0.000062800194,0.00018897199,0.00027621837,0.0009852585,0.002587255],"genre_scores_gemma":[0.5911955,0.00064103835,0.40478572,0.00022389302,0.00015877649,0.0002480036,0.0005842025,0.0003693034,0.0017935159],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99522,0.0013605722,0.00021676612,0.0013365755,0.0010372456,0.00082885765],"domain_scores_gemma":[0.98054117,0.014258823,0.0018764278,0.001456634,0.0011741214,0.0006928331],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0053851446,0.0016772161,0.002926445,0.0014121776,0.001862103,0.00325913,0.004827027,0.0028697704,0.0023101806],"category_scores_gemma":[0.027089015,0.0013271518,0.0015683614,0.0024517355,0.0020871786,0.007906177,0.003752762,0.0021037443,0.0005588804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00080263615,0.00021077294,0.0024857027,0.0002484602,0.00011964828,0.00012260205,0.00031594766,0.8913122,0.004169609,0.04166854,0.0028592318,0.05568466],"study_design_scores_gemma":[0.00004613442,0.00010561402,0.00038204962,0.000012848726,0.000028019163,0.00008956074,0.00014005922,0.96980685,0.0032990677,0.024919003,0.0011446174,0.000026275146],"about_ca_topic_score_codex":0.0064081373,"about_ca_topic_score_gemma":0.0043235035,"teacher_disagreement_score":0.0064081373,"about_ca_system_score_codex":0.0034516433,"about_ca_system_score_gemma":0.0029354137,"threshold_uncertainty_score":0.028479695},"labels":[],"label_agreement":null},{"id":"W4366809744","doi":"10.5220/0006091600001482","title":"Search-and-Fetch with 2 Robots on a Disk","year":2017,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; McMaster University; Toronto Metropolitan University","funders":"","keywords":"Fetch; Robot; Computer science; Artificial intelligence; Geology","score_opus":0.03486497973415568,"score_gpt":0.28953936542862124,"score_spread":0.25467438569446554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4366809744","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.27961674,0.0013001869,0.65389544,0.0022167782,0.00084121677,0.00075092865,0.0012255879,0.013950451,0.04620267],"genre_scores_gemma":[0.613877,0.00019515143,0.3533652,0.00022264944,0.00010431438,0.000435246,0.0007139848,0.0004412038,0.0306453],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99906677,0.00018936148,0.000057888516,0.0002523148,0.00017722149,0.00025648135],"domain_scores_gemma":[0.99826956,0.00065699895,0.00006066404,0.00070568593,0.00016627456,0.0001407482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008387183,0.001397283,0.0023416413,0.00080668944,0.0022061141,0.0013820311,0.0026308682,0.003209618,0.038534943],"category_scores_gemma":[0.003945746,0.0009103687,0.0008712955,0.0013621041,0.0011962405,0.0037688748,0.0042035053,0.0017621642,0.0050987904],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0062329317,0.0009611001,0.0032792066,0.0006196118,0.00024865594,0.0011775487,0.00054501975,0.46905595,0.017207453,0.04137015,0.039640494,0.4196619],"study_design_scores_gemma":[0.0006136641,0.0005533191,0.00068436004,0.00003676735,0.00005273917,0.00027004475,0.0003187276,0.93424463,0.009407384,0.042874828,0.010882805,0.000060649185],"about_ca_topic_score_codex":0.005740857,"about_ca_topic_score_gemma":0.009786662,"teacher_disagreement_score":0.038534943,"about_ca_system_score_codex":0.0008911789,"about_ca_system_score_gemma":0.001859848,"threshold_uncertainty_score":0.12891221},"labels":[],"label_agreement":null},{"id":"W4367183818","doi":"10.3390/a16050222","title":"Asynchronous Gathering in a Dangerous Ring","year":2023,"lang":"en","type":"article","venue":"Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Gruppo Nazionale per il Calcolo Scientifico; Natural Sciences and Engineering Research Council of Canada; Università di Pisa; Istituto Nazionale di Alta Matematica \"Francesco Severi\"","keywords":"Rendezvous; Asynchronous communication; Computer science; Node (physics); Mathematical proof; Ring (chemistry); Constructive; Set (abstract data type); Mobile agent; A priori and a posteriori; Ring network; Process (computing); Distributed computing; Computer network; Mathematics","score_opus":0.02803209220788296,"score_gpt":0.2773430951888817,"score_spread":0.24931100298099876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4367183818","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.33180696,0.00021804811,0.65889156,0.00054850493,0.00004570633,0.00014187064,0.00012726604,0.00034347008,0.007876679],"genre_scores_gemma":[0.8895392,0.00017412525,0.105875924,0.000071245966,0.000038442784,0.00012041087,0.00012342902,0.00004122641,0.004016045],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99826956,0.0005244628,0.00008155271,0.0004899016,0.0003269212,0.00030769658],"domain_scores_gemma":[0.9939865,0.0031994206,0.0009878777,0.00082043296,0.00031998876,0.0006858362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018476511,0.00055652525,0.0008036359,0.00061030115,0.0016494752,0.001507506,0.0017370111,0.0010393601,0.0025575892],"category_scores_gemma":[0.00808928,0.00045077986,0.00089514774,0.0004984059,0.0017031052,0.0034909258,0.0032886253,0.0011467629,0.00046390275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011538339,0.00015315137,0.0046911878,0.0002835252,0.00012429811,0.0019463392,0.0015454389,0.63242835,0.02566842,0.30569112,0.0017536158,0.024560763],"study_design_scores_gemma":[0.00008140017,0.00023646175,0.00064845476,0.000018837627,0.000041885116,0.00039616833,0.0004243755,0.9078639,0.006529411,0.07931367,0.0044066086,0.000038798848],"about_ca_topic_score_codex":0.0010766356,"about_ca_topic_score_gemma":0.00075999676,"teacher_disagreement_score":0.0025575892,"about_ca_system_score_codex":0.0007831018,"about_ca_system_score_gemma":0.0006404683,"threshold_uncertainty_score":0.009771466},"labels":[],"label_agreement":null},{"id":"W4372272740","doi":"10.4230/lipics.icalp.2023.80","title":"Efficient Caching with Reserves via Marking","year":2023,"lang":"en","type":"preprint","venue":"London School of Economics and Political Science Research Online (London School of Economics and Political Science)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; European Commission","keywords":"Competitive analysis; Online algorithm; Paging; Computer science; Randomized algorithm; Cache; Upper and lower bounds; Simple (philosophy); Function (biology); Rounding; Randomized rounding; Dual (grammatical number); Time complexity; Freivalds' algorithm; CPU cache; Algorithm; Mathematical optimization; Theoretical computer science; Approximation algorithm; Mathematics; Parallel computing; Computer network","score_opus":0.07166955629201377,"score_gpt":0.36170394450319693,"score_spread":0.29003438821118316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4372272740","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08786732,0.00045252952,0.89946157,0.0009713321,0.00009775542,0.000121882484,0.00023118561,0.0015733277,0.009223102],"genre_scores_gemma":[0.81830955,0.0002355366,0.17649972,0.00017092841,0.00007409495,0.000114169816,0.00016942833,0.00019299876,0.004233439],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982614,0.0005168744,0.000099096884,0.00037216465,0.00038486565,0.00036565543],"domain_scores_gemma":[0.9953791,0.0021568078,0.0005191335,0.0014463596,0.0003045862,0.00019401543],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015245497,0.00064737233,0.0011249074,0.0006247477,0.0009300653,0.002675238,0.002664357,0.0014203524,0.002905149],"category_scores_gemma":[0.008619271,0.00041972895,0.00065410754,0.0013352807,0.0013307495,0.0058006896,0.0019666154,0.0014972035,0.0006444397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009264294,0.0002542671,0.0015870742,0.00031660718,0.000070241666,0.00028496273,0.00028747358,0.4496805,0.01993589,0.39624524,0.009928962,0.12048236],"study_design_scores_gemma":[0.00004488968,0.00007092646,0.00018076072,0.000022109818,0.000021610438,0.00015520258,0.00005441243,0.86080056,0.006820339,0.12872854,0.0030800707,0.000020569953],"about_ca_topic_score_codex":0.0014448618,"about_ca_topic_score_gemma":0.0014701434,"teacher_disagreement_score":0.002905149,"about_ca_system_score_codex":0.0014834392,"about_ca_system_score_gemma":0.0016840028,"threshold_uncertainty_score":0.010763168},"labels":[],"label_agreement":null},{"id":"W4376607417","doi":"10.1137/1.9781611977714.16","title":"Exponential Convergence of Sinkhorn Under Regularization Scheduling","year":2023,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Logarithm; Scaling; Regularization (linguistics); Mathematical optimization; Exponential function; Rate of convergence; Computer science; Applied mathematics; Convergence (economics); Mathematics; Key (lock); Artificial intelligence","score_opus":0.09839758548177648,"score_gpt":0.25992012151857014,"score_spread":0.16152253603679367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376607417","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017603826,0.00031798967,0.9744717,0.0003704565,0.000108304295,0.000046796114,0.000044655335,0.00041379844,0.0066225366],"genre_scores_gemma":[0.32913685,0.00048512555,0.65410286,0.0005968526,0.00012453548,0.00029022602,0.00028957243,0.0006214269,0.014352496],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99933064,0.00023218693,0.00003091934,0.00012361909,0.00020734884,0.00007514592],"domain_scores_gemma":[0.9975714,0.0014759487,0.00013831636,0.0003442597,0.00037062727,0.00009943495],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017390605,0.0009577209,0.0008928614,0.0006509924,0.0005832693,0.00083124574,0.0011007405,0.0012766861,0.0031104838],"category_scores_gemma":[0.00853894,0.00037393143,0.0007593185,0.00051875075,0.0015800678,0.0018759337,0.0016935759,0.0020250124,0.0007993002],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002953976,0.00010133832,0.0012168365,0.0002370919,0.00007619595,0.00013450508,0.00021050138,0.56986403,0.013209887,0.32137087,0.008674004,0.08460928],"study_design_scores_gemma":[0.000007897287,0.00001882048,0.00004792572,0.000009347749,0.0000031236416,0.000013477895,0.000008616775,0.97109187,0.0011559769,0.026572278,0.0010652269,0.0000054245074],"about_ca_topic_score_codex":0.002067782,"about_ca_topic_score_gemma":0.00239564,"teacher_disagreement_score":0.0031104838,"about_ca_system_score_codex":0.00095295184,"about_ca_system_score_gemma":0.0009320759,"threshold_uncertainty_score":0.01040566},"labels":[],"label_agreement":null},{"id":"W4376874338","doi":"10.1007/s10107-023-01971-3","title":"A colorful Steinitz Lemma with application to block-structured integer programs","year":2023,"lang":"en","type":"article","venue":"Mathematical Programming","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Einstein Stiftung Berlin; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Combinatorics; Lemma (botany); Norm (philosophy); Integer (computer science); Bounded function; Upper and lower bounds; Integer programming; Discrete mathematics; Sequence (biology); Algorithm; Computer science","score_opus":0.022556172994474082,"score_gpt":0.2743292564063316,"score_spread":0.2517730834118575,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376874338","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024679808,0.0006776609,0.9356374,0.0012230832,0.0003760947,0.000059999562,0.00019236773,0.0003793214,0.036774248],"genre_scores_gemma":[0.5752297,0.0028028355,0.37307724,0.0013922788,0.000755092,0.00038049102,0.00042038228,0.0008118779,0.045130014],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99938154,0.00021638577,0.000025261666,0.000098334705,0.00019290255,0.00008556512],"domain_scores_gemma":[0.9972421,0.0016470836,0.0001886362,0.00028393502,0.00042739007,0.00021090724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018382549,0.0010002418,0.0009434147,0.001516563,0.0008759888,0.0024212557,0.0012265414,0.0010223555,0.009744936],"category_scores_gemma":[0.008582969,0.00056478643,0.0010549442,0.002286241,0.0023420646,0.004303164,0.002750672,0.00382158,0.0016525696],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047150275,0.000040409268,0.00017623282,0.00005410736,0.000011677213,0.000054875734,0.000074233554,0.009517716,0.0015124456,0.9660393,0.003920966,0.01855078],"study_design_scores_gemma":[0.000020974763,0.00003350869,0.0001205083,0.000021441654,0.000015028679,0.00004750325,0.000029967869,0.116960615,0.0009698406,0.87687904,0.0048833177,0.000018273868],"about_ca_topic_score_codex":0.0021373243,"about_ca_topic_score_gemma":0.0024712582,"teacher_disagreement_score":0.009744936,"about_ca_system_score_codex":0.0012824856,"about_ca_system_score_gemma":0.0013843898,"threshold_uncertainty_score":0.032600105},"labels":[],"label_agreement":null},{"id":"W4377966775","doi":"10.46254/na07.20220065","title":"A novel sorting approach under uncertainty: A Monte-Carlo simulation with temporal evaluations","year":2023,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"Université du Québec à Rimouski","funders":"","keywords":"Monte Carlo method; Computer science; Sorting; Statistical physics; Algorithm; Statistics; Mathematics; Physics","score_opus":0.11107833854571146,"score_gpt":0.34866918914694145,"score_spread":0.23759085060122997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377966775","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10100477,0.00032226267,0.8852224,0.00084990443,0.00007759497,0.00015162655,0.00028001895,0.00027426553,0.011817149],"genre_scores_gemma":[0.7016377,0.00035729722,0.29317132,0.0002054021,0.00005767375,0.00026879786,0.00023726224,0.00008336643,0.003981199],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991015,0.00050455885,0.000039589515,0.00009872053,0.00016728224,0.00008833988],"domain_scores_gemma":[0.9950795,0.003907109,0.00028232296,0.00018832284,0.00040504697,0.00013765333],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026801648,0.00051018666,0.0009785262,0.0010176343,0.0007647328,0.0016006015,0.0015897689,0.0018367594,0.0049220156],"category_scores_gemma":[0.008998163,0.00048985105,0.0010329369,0.0015707286,0.0009422573,0.0017857365,0.0009891052,0.0011614646,0.00023647986],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003362012,0.000025377363,0.0004327963,0.000015727406,0.0000155203,0.000021711587,0.00002398969,0.98301667,0.00010298368,0.011578269,0.00015396049,0.0045794277],"study_design_scores_gemma":[0.000007481882,0.000009776527,0.00004312483,0.000003717279,0.00000392209,0.0000039561965,0.0000052123432,0.9972849,0.000043373457,0.0024461783,0.00014532675,0.0000030406254],"about_ca_topic_score_codex":0.031233966,"about_ca_topic_score_gemma":0.027378444,"teacher_disagreement_score":0.031233966,"about_ca_system_score_codex":0.0016059949,"about_ca_system_score_gemma":0.0024553684,"threshold_uncertainty_score":0.062104344},"labels":[],"label_agreement":null},{"id":"W4377971906","doi":"10.1007/978-3-031-32733-9_23","title":"Overcoming Probabilistic Faults in Disoriented Linear Search","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University","funders":"","keywords":"Probabilistic logic; Computer science; Randomized algorithm; Competitive analysis; Deterministic algorithm; Path (computing); Bernoulli's principle; Constant (computer programming); Algorithm; Leverage (statistics); Mathematics; Mathematical optimization; Combinatorics; Artificial intelligence; Upper and lower bounds","score_opus":0.03432631466397401,"score_gpt":0.2869286109457508,"score_spread":0.2526022962817768,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377971906","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07054213,0.0018416005,0.9104122,0.00078231154,0.00024903135,0.000058781512,0.00007725763,0.003180629,0.012856046],"genre_scores_gemma":[0.7743045,0.00070092274,0.21505149,0.00031972132,0.0001385584,0.00008180733,0.00014495946,0.00051945605,0.008738753],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999236,0.00021521316,0.000047321257,0.00010223458,0.00029842026,0.000100948644],"domain_scores_gemma":[0.9955413,0.0029677677,0.00029108112,0.00066040235,0.00039564914,0.00014382007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012340388,0.0005806731,0.00086128345,0.0006046218,0.00043364207,0.0011614441,0.0018200687,0.0009578682,0.003704751],"category_scores_gemma":[0.0086779175,0.00044403592,0.0003503222,0.0011202913,0.001249303,0.0028752405,0.0017853115,0.0017262857,0.00054859684],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00056481606,0.00007845274,0.0011094338,0.00030797702,0.000045133365,0.00016771237,0.00018346688,0.5941389,0.004425224,0.1100201,0.0056312373,0.28332758],"study_design_scores_gemma":[0.000025925483,0.000074858865,0.00015049554,0.00002014461,0.000016365224,0.000084254425,0.000033956814,0.90276724,0.001526526,0.09316217,0.0021280926,0.000009937794],"about_ca_topic_score_codex":0.0016416532,"about_ca_topic_score_gemma":0.0022202083,"teacher_disagreement_score":0.003704751,"about_ca_system_score_codex":0.00091786037,"about_ca_system_score_gemma":0.0009585356,"threshold_uncertainty_score":0.012393653},"labels":[],"label_agreement":null},{"id":"W4378469689","doi":"10.1016/j.artint.2023.103950","title":"Conflict-tolerant and conflict-free multi-agent meeting","year":2023,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Israel Science Foundation; National Sleep Foundation; United States-Israel Binational Science Foundation; National Science Foundation","keywords":"Heuristics; Task (project management); Mathematical optimization; Computer science; Heuristic; Function (biology); Path (computing); Point (geometry); Operations research; Artificial intelligence; Mathematics; Engineering","score_opus":0.15850144781698802,"score_gpt":0.3451729614154096,"score_spread":0.18667151359842157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378469689","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.062243562,0.00026792675,0.91687346,0.00076257205,0.00016013796,0.00021493052,0.00009984888,0.0002267972,0.01915072],"genre_scores_gemma":[0.8798887,0.00022517476,0.110769086,0.00013824357,0.00009917347,0.000255433,0.0001471817,0.00005520935,0.008421874],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971865,0.0013789448,0.00014271315,0.00035451233,0.0006303466,0.00030691168],"domain_scores_gemma":[0.9956689,0.0023495476,0.0004706488,0.00042791845,0.00051584834,0.0005671562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002674406,0.0010572734,0.0016791606,0.0009496522,0.0022499047,0.002636418,0.003738021,0.002002629,0.0048909723],"category_scores_gemma":[0.012308116,0.0006713265,0.00074559473,0.0011081072,0.0014100819,0.0037651134,0.0039617866,0.0015281498,0.0007845568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009053003,0.0003256414,0.0009593604,0.00026835725,0.00014546636,0.00065799535,0.00075771136,0.7107188,0.006189694,0.20408966,0.0049670395,0.07001494],"study_design_scores_gemma":[0.000049728118,0.000118675074,0.00016896479,0.000011797853,0.00002263323,0.0001373442,0.0001704167,0.90430516,0.000983575,0.091777846,0.0022289082,0.000024984725],"about_ca_topic_score_codex":0.0009470829,"about_ca_topic_score_gemma":0.00066975626,"teacher_disagreement_score":0.0048909723,"about_ca_system_score_codex":0.0008798636,"about_ca_system_score_gemma":0.001111673,"threshold_uncertainty_score":0.016361952},"labels":[],"label_agreement":null},{"id":"W4378801305","doi":"10.1145/3558481.3591084","title":"An Associativity Threshold Phenomenon in Set-Associative Caches","year":2023,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Associative property; Cache; Parallel computing; Cache algorithms; Set (abstract data type); Disjoint sets; Paging; Hash function; Bus sniffing; Latency (audio); CPU cache; Cache pollution; Concurrency; Theoretical computer science; Distributed computing; Computer network; Programming language; Mathematics; Discrete mathematics","score_opus":0.057175379651249615,"score_gpt":0.3263075660319567,"score_spread":0.2691321863807071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378801305","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5812503,0.0095817065,0.3528585,0.0030319926,0.0009430291,0.00021615236,0.00067962945,0.0030687216,0.048369918],"genre_scores_gemma":[0.9806528,0.00091561343,0.011334722,0.00068845664,0.00015454042,0.00010703252,0.00014597754,0.00009165696,0.0059092464],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981547,0.00020002491,0.00015265975,0.00034315474,0.0007863821,0.00036308938],"domain_scores_gemma":[0.9928604,0.0033687297,0.0007710397,0.0015125521,0.001148998,0.00033832676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009877011,0.0003308715,0.0009183038,0.0007396826,0.0010594024,0.002517229,0.0015292955,0.0014939536,0.0053419787],"category_scores_gemma":[0.01003765,0.00064317446,0.0003543372,0.0020090684,0.0014954859,0.006057335,0.0014574608,0.0020167104,0.0010514942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017033849,0.0006352852,0.014545936,0.0009722548,0.00020635808,0.0023729585,0.0017072767,0.06506211,0.11087005,0.64813936,0.021334602,0.13245042],"study_design_scores_gemma":[0.0003272654,0.00097434776,0.0071196314,0.0002604104,0.00024429042,0.0059145642,0.0009017081,0.33610794,0.0992571,0.4958251,0.052847277,0.00022040607],"about_ca_topic_score_codex":0.0011448807,"about_ca_topic_score_gemma":0.0011018194,"teacher_disagreement_score":0.0053419787,"about_ca_system_score_codex":0.0011831383,"about_ca_system_score_gemma":0.001135535,"threshold_uncertainty_score":0.017870665},"labels":[],"label_agreement":null},{"id":"W4382239271","doi":"10.1609/aaai.v37i6.25864","title":"The Sufficiency of Off-Policyness and Soft Clipping: PPO Is Still Insufficient according to an Off-Policy Measure","year":2023,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Alberta Machine Intelligence Institute","keywords":"Clipping (morphology); Computer science; Space (punctuation); Metric (unit); Measure (data warehouse); Mathematical optimization; Sigmoid function; Code (set theory); Function (biology); Algorithm; Mathematics; Data mining; Artificial intelligence; Economics; Operations management; Programming language","score_opus":0.1051787284617897,"score_gpt":0.34265991363007636,"score_spread":0.23748118516828665,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382239271","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07217481,0.0010469449,0.9125005,0.002105315,0.00023782584,0.00015791315,0.00017394352,0.00086931087,0.0107334405],"genre_scores_gemma":[0.85290474,0.00049504347,0.13966514,0.0012918502,0.00020427868,0.00030816198,0.00030724143,0.00047709674,0.004346514],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9965593,0.0011708566,0.00025707323,0.00068320084,0.00090241275,0.0004271451],"domain_scores_gemma":[0.9769598,0.017572047,0.0011924908,0.0018195291,0.0014387197,0.0010174839],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006092813,0.0014090316,0.0025301618,0.0007949966,0.0009953713,0.0025316651,0.0019292387,0.002744474,0.0037007385],"category_scores_gemma":[0.042211458,0.00074774894,0.0007523607,0.0006247009,0.0030511837,0.0043464494,0.0033548705,0.0046407185,0.0005215592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008140879,0.00040611826,0.0059023225,0.00078968547,0.00020265854,0.000560746,0.0005362919,0.7064517,0.0059812544,0.1321394,0.009447197,0.13676849],"study_design_scores_gemma":[0.000043722885,0.00024230462,0.00062428496,0.00010575093,0.000024237246,0.00016403565,0.0000641161,0.94264275,0.002341168,0.05200065,0.0017196496,0.000027243601],"about_ca_topic_score_codex":0.002211566,"about_ca_topic_score_gemma":0.0012906644,"teacher_disagreement_score":0.006092813,"about_ca_system_score_codex":0.0011980325,"about_ca_system_score_gemma":0.0030357665,"threshold_uncertainty_score":0.03222227},"labels":[],"label_agreement":null},{"id":"W4383109118","doi":"10.1109/icra48891.2023.10160912","title":"Approximation Algorithms for Robot Tours in Random Fields with Guaranteed Estimation Accuracy","year":2023,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Computer science; Sample (material); Regular polygon; Algorithm; Random field; Mathematical optimization; Approximation algorithm; Estimation; Upper and lower bounds; Mathematics; Artificial intelligence; Statistics; Engineering","score_opus":0.0396993950952113,"score_gpt":0.31117966896045424,"score_spread":0.2714802738652429,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4383109118","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008357025,0.0003221213,0.9895536,0.00023371329,0.0000256765,0.00003332433,0.00005845842,0.00040829513,0.0010077012],"genre_scores_gemma":[0.42255464,0.00091814896,0.5711238,0.00029907378,0.000116964555,0.00043129016,0.00059962255,0.00048286363,0.0034736986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984944,0.0006042175,0.000060723898,0.00025143853,0.00033050656,0.00025867275],"domain_scores_gemma":[0.98780966,0.010037465,0.0007122318,0.00071552384,0.0004675411,0.00025773284],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002919751,0.0016391105,0.0018746547,0.001229372,0.000720159,0.0013321938,0.0025167298,0.0018622368,0.0032640253],"category_scores_gemma":[0.02015869,0.00086360413,0.0012893602,0.0016439854,0.0016935919,0.0031680865,0.0023507413,0.002847561,0.00074689393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001328376,0.00004337738,0.00044329543,0.0000907985,0.000030651114,0.000033802513,0.00009276186,0.95069677,0.0005893298,0.02567739,0.0016390495,0.020529954],"study_design_scores_gemma":[0.000015072673,0.000019573745,0.000047075944,0.0000074971354,0.0000042749543,0.000011656582,0.0000098811015,0.9860681,0.00015766325,0.013348963,0.00030651005,0.0000036470128],"about_ca_topic_score_codex":0.0063933586,"about_ca_topic_score_gemma":0.006299739,"teacher_disagreement_score":0.0063933586,"about_ca_system_score_codex":0.0024113227,"about_ca_system_score_gemma":0.0020077245,"threshold_uncertainty_score":0.017495453},"labels":[],"label_agreement":null},{"id":"W4385359901","doi":"10.1007/978-3-031-38906-1_14","title":"Online Interval Scheduling with Predictions","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Disjoint sets; Competitive analysis; Scheduling (production processes); Upper and lower bounds; Algorithm; Mathematical optimization; Mathematics; Combinatorics","score_opus":0.03238855091904636,"score_gpt":0.2731777316503188,"score_spread":0.24078918073127242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385359901","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021435244,0.0009755612,0.94049406,0.00054211775,0.00081548165,0.0001641335,0.00075462885,0.003207893,0.031610806],"genre_scores_gemma":[0.62822425,0.0008912586,0.33817562,0.0003739455,0.000953888,0.00033122377,0.0016295322,0.00069369667,0.028726568],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989693,0.00020954442,0.000045269215,0.00029662228,0.0002765406,0.00020274057],"domain_scores_gemma":[0.997758,0.0012280808,0.00013830054,0.0005020131,0.00020740593,0.00016615546],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015913441,0.0012799144,0.00178705,0.00057243963,0.00067703874,0.001802129,0.0025247964,0.0009094488,0.017077817],"category_scores_gemma":[0.004990948,0.0006410953,0.0007170072,0.0015659998,0.0005970323,0.0021033199,0.0012914514,0.0027680616,0.0035561942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012521109,0.0004750975,0.00034675805,0.0002405765,0.000051442672,0.0001070394,0.00006951245,0.58817613,0.00421675,0.06838645,0.030906135,0.305772],"study_design_scores_gemma":[0.000045206983,0.000100282305,0.00009015647,0.000015046413,0.000011826903,0.00002606127,0.000013703364,0.9532782,0.001183829,0.042285133,0.0029394606,0.00001113638],"about_ca_topic_score_codex":0.0017946435,"about_ca_topic_score_gemma":0.0016956999,"teacher_disagreement_score":0.017077817,"about_ca_system_score_codex":0.0008940477,"about_ca_system_score_gemma":0.0017163124,"threshold_uncertainty_score":0.057130933},"labels":[],"label_agreement":null},{"id":"W4385549512","doi":"10.21203/rs.3.rs-3207161/v1","title":"A Soft Obstacle Search Strategy for Various Solitary Robots in an Unknown Environment","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Robot; Obstacle; A priori and a posteriori; Artificial intelligence; Computer science; Robotics; Search and rescue; Interference (communication); Distributed computing; Human–computer interaction; Computer network; Geography","score_opus":0.21788459314159045,"score_gpt":0.42644286257360714,"score_spread":0.2085582694320167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385549512","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.26079586,0.00024687318,0.7326764,0.00028892473,0.00004329998,0.000087461354,0.000035774392,0.00016407343,0.0056614107],"genre_scores_gemma":[0.96005267,0.00006642375,0.037671395,0.000044680914,0.000007035609,0.000087278575,0.000021583523,0.000013577202,0.002035464],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998093,0.000051132356,0.000008238096,0.00003054114,0.000047590784,0.000053284923],"domain_scores_gemma":[0.9995528,0.00017254421,0.0000705216,0.000028969816,0.00005513777,0.00011995409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00043463882,0.00073186425,0.0008348679,0.00062486087,0.0005745575,0.00078053254,0.0008441958,0.000749164,0.0015600972],"category_scores_gemma":[0.0010469556,0.0002568254,0.00036400315,0.00032169957,0.0007525589,0.0005798325,0.0014783209,0.0003939827,0.00020374707],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025801445,0.000091174516,0.0009975935,0.00010466686,0.00005577177,0.0002967653,0.00020873974,0.9329209,0.01212608,0.020932535,0.0007622912,0.031245444],"study_design_scores_gemma":[0.000020021322,0.000081652994,0.00012818981,0.0000058485825,0.000008632772,0.000020325193,0.000043172542,0.99623966,0.0006937821,0.0025212674,0.0002315469,0.0000059507033],"about_ca_topic_score_codex":0.0023447145,"about_ca_topic_score_gemma":0.0017501486,"teacher_disagreement_score":0.0023447145,"about_ca_system_score_codex":0.00052224396,"about_ca_system_score_gemma":0.00063909765,"threshold_uncertainty_score":0.0052190423},"labels":[],"label_agreement":null},{"id":"W4385741168","doi":"10.1016/j.ins.2023.119487","title":"Pioneering approaches for enhancing the speed of hierarchical LA by ordering the actions","year":2023,"lang":"en","type":"article","venue":"Information Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Estimator; A priori and a posteriori; Benchmark (surveying); Assertion; Automaton; Tree (set theory); Salient; Theoretical computer science; Action (physics); Convergence (economics); Algorithm; Artificial intelligence; Mathematics","score_opus":0.10418225204715947,"score_gpt":0.31282389437804803,"score_spread":0.20864164233088855,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385741168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0064079734,0.0014961078,0.9813405,0.00035241348,0.00014935965,0.00012511069,0.00013307032,0.002585691,0.0074097114],"genre_scores_gemma":[0.120049804,0.0010321705,0.8715006,0.0004188757,0.00020321978,0.00023268088,0.00026143802,0.0004557539,0.005845431],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982888,0.00053527084,0.00013395766,0.00033030083,0.0005008736,0.00021066601],"domain_scores_gemma":[0.99456716,0.0024670786,0.00020451726,0.0018295234,0.00071732496,0.00021439441],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022988752,0.001617841,0.0013189907,0.0016076717,0.0010934622,0.0021699208,0.0028926793,0.0015852457,0.011033092],"category_scores_gemma":[0.0097564915,0.00088336354,0.0013233054,0.0021091579,0.0016304144,0.0043953964,0.0026700802,0.004539789,0.003984686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006023322,0.00039301848,0.00091743405,0.00083648873,0.00015270326,0.000080416416,0.00040424478,0.080186255,0.023237748,0.22381596,0.01365495,0.6557185],"study_design_scores_gemma":[0.00017281348,0.00027869054,0.00046672992,0.00012643762,0.00010489337,0.0001272271,0.0001134857,0.79310924,0.025245886,0.14928932,0.030862192,0.00010298685],"about_ca_topic_score_codex":0.007100757,"about_ca_topic_score_gemma":0.011830556,"teacher_disagreement_score":0.011033092,"about_ca_system_score_codex":0.0016950163,"about_ca_system_score_gemma":0.003010853,"threshold_uncertainty_score":0.03690934},"labels":[],"label_agreement":null},{"id":"W4386155733","doi":"10.1007/978-3-031-39344-0_18","title":"Constrained Graph Searching on Trees","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Regina","funders":"","keywords":"Combinatorics; Path graph; Computer science; Distance; Wheel graph; Graph; Time complexity; Mathematics; Discrete mathematics; Graph power; Line graph","score_opus":0.03391685590947484,"score_gpt":0.2761777690574971,"score_spread":0.24226091314802223,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386155733","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018830413,0.004391434,0.8635879,0.0008910362,0.0002760536,0.00011702551,0.00062526297,0.0010857051,0.11019515],"genre_scores_gemma":[0.22003244,0.0048113856,0.6854718,0.0005407651,0.00023307934,0.00030686505,0.0017930487,0.0013085162,0.085502096],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997094,0.00007895374,0.000009900992,0.00006452896,0.00010560101,0.000031619787],"domain_scores_gemma":[0.99940836,0.00037677615,0.000030081024,0.00010112341,0.00005124617,0.000032448883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022927027,0.0006729449,0.0010137768,0.0010128582,0.0004969716,0.0010173726,0.0013325905,0.0010039131,0.019446388],"category_scores_gemma":[0.0024239628,0.0005646771,0.0005091769,0.0031002155,0.0007247715,0.0021276828,0.0014356675,0.0014741984,0.0028302774],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014251054,0.00010481715,0.0002130478,0.0005422625,0.00004733264,0.00010621425,0.000121647674,0.24821065,0.0050528618,0.32044953,0.053504717,0.37150443],"study_design_scores_gemma":[0.000036434405,0.00005316039,0.00022957876,0.000112812515,0.000016693506,0.00013953289,0.0000580852,0.5056088,0.0022123891,0.4512865,0.040224142,0.000021812424],"about_ca_topic_score_codex":0.002522235,"about_ca_topic_score_gemma":0.0033229063,"teacher_disagreement_score":0.019446388,"about_ca_system_score_codex":0.0007461748,"about_ca_system_score_gemma":0.0005896706,"threshold_uncertainty_score":0.065054715},"labels":[],"label_agreement":null},{"id":"W4386159662","doi":"10.1109/csci58124.2022.00090","title":"The 2-MAXSAT Problem Can Be Solved in Polynomial Time","year":2022,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg; Manitoba Beekeepers' Association","funders":"","keywords":"Maximum satisfiability problem; Computer science; Polynomial; Bounded function; Combinatorics; Algorithm; Artificial intelligence; Discrete mathematics; Mathematics; Boolean function","score_opus":0.013694384641439772,"score_gpt":0.2278928376202346,"score_spread":0.21419845297879483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386159662","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046663776,0.0065031215,0.68251324,0.011843024,0.00188284,0.00083387847,0.025255395,0.010840767,0.21366398],"genre_scores_gemma":[0.4223002,0.0057625216,0.46938846,0.0035442177,0.0015603834,0.0012126692,0.027735451,0.003880286,0.064615786],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989303,0.00021201346,0.000057074736,0.00040347397,0.00018904981,0.00020813792],"domain_scores_gemma":[0.99798113,0.0013154398,0.00016768147,0.00032707403,0.0001382302,0.00007047474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080678327,0.002384929,0.0015440454,0.00060295896,0.0011316432,0.0040128194,0.0017294771,0.0019301348,0.04419946],"category_scores_gemma":[0.0036071606,0.0008834789,0.0020539782,0.0023972292,0.001123906,0.004680245,0.0017201975,0.0030774171,0.011277143],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012749231,0.00048026364,0.0011830562,0.0034652664,0.00025793767,0.00092011475,0.00022794482,0.14051493,0.016300822,0.2624127,0.27062178,0.30234024],"study_design_scores_gemma":[0.00033074542,0.00016642838,0.0011579482,0.00029584573,0.00013119745,0.0011672488,0.00021785492,0.32058287,0.010382633,0.51810765,0.14738232,0.000077264376],"about_ca_topic_score_codex":0.0016999681,"about_ca_topic_score_gemma":0.005197106,"teacher_disagreement_score":0.04419946,"about_ca_system_score_codex":0.0016386674,"about_ca_system_score_gemma":0.0024378595,"threshold_uncertainty_score":0.14786196},"labels":[],"label_agreement":null},{"id":"W4386255660","doi":"10.28924/2291-8639-21-2023-94","title":"Sum Connectivity Index Under the Cartesian and Strong Products Graph of Monogenic Semigroup","year":2023,"lang":"en","type":"article","venue":"International Journal of Analysis and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Cartesian product; Cartesian coordinate system; Semigroup; Mathematics; Graph; Index (typography); Topological index; Undirected graph; Discrete mathematics; Combinatorics; Computer science; Geometry","score_opus":0.01760620007882813,"score_gpt":0.28951913163907445,"score_spread":0.2719129315602463,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386255660","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2109223,0.00034177286,0.77627826,0.00022397687,0.000091929825,0.000053518896,0.00037143487,0.0005390494,0.011177728],"genre_scores_gemma":[0.71136063,0.0003716809,0.27907655,0.00010936822,0.00019535,0.00013923857,0.0008866903,0.00022586562,0.0076345215],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99944156,0.00007950396,0.000039605176,0.00021192888,0.00016949396,0.000057865684],"domain_scores_gemma":[0.9989415,0.000368328,0.00012954239,0.00019616247,0.00024668637,0.00011776075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005169843,0.00037545452,0.00036934993,0.0013436165,0.00068975356,0.0014061963,0.0006318303,0.0004010614,0.003936867],"category_scores_gemma":[0.0026971395,0.00019744766,0.0005839535,0.0009838444,0.001112478,0.0026008044,0.0009806321,0.0006688547,0.00053004833],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023757864,0.000066108114,0.005427867,0.0002787006,0.000049584327,0.00035558324,0.0010458217,0.03552007,0.017619886,0.7846208,0.0039958125,0.1507821],"study_design_scores_gemma":[0.000027917748,0.00021400391,0.0037423654,0.00004251974,0.0000705564,0.0009115212,0.0003892305,0.26440725,0.016364815,0.7031828,0.0105895335,0.000057447567],"about_ca_topic_score_codex":0.0009493898,"about_ca_topic_score_gemma":0.0008591016,"teacher_disagreement_score":0.003936867,"about_ca_system_score_codex":0.00062793837,"about_ca_system_score_gemma":0.0005124484,"threshold_uncertainty_score":0.013170123},"labels":[],"label_agreement":null},{"id":"W4386880161","doi":"10.1007/978-3-031-43587-4_12","title":"Minimizing Query Frequency to Bound Congestion Potential for Moving Entities at a Fixed Target Time","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Bounded function; Intersection (aeronautics); Exploit; Reciprocal; Graph; Query optimization; Upper and lower bounds; Mathematical optimization; Theoretical computer science; Data mining; Mathematics","score_opus":0.020696146411820125,"score_gpt":0.2513531505849658,"score_spread":0.2306570041731457,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386880161","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.063624546,0.00092334836,0.92781854,0.00037910318,0.00011318733,0.00012269062,0.00011837272,0.0005699105,0.0063303285],"genre_scores_gemma":[0.90660065,0.0004925941,0.08723928,0.00010207424,0.00015958138,0.00010404937,0.000119194134,0.00018960792,0.0049928245],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988965,0.00021477454,0.000042552518,0.00022995405,0.0002723635,0.00034387087],"domain_scores_gemma":[0.9976647,0.0014617455,0.00015909158,0.0002006225,0.00035835637,0.00015545485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014119047,0.0010385335,0.0015923361,0.00086268794,0.00071029563,0.0015341355,0.0025271657,0.0013478827,0.0037447924],"category_scores_gemma":[0.0080824485,0.00043161365,0.00047012212,0.0015992922,0.0006905991,0.002331473,0.0014036782,0.0009623161,0.0005290953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038249427,0.00013127556,0.00082455506,0.00022040127,0.00006529119,0.00008716278,0.0000841266,0.8887355,0.015922777,0.02427293,0.0036546534,0.06561891],"study_design_scores_gemma":[0.000007673256,0.0000833739,0.00017270104,0.000005223651,0.000020378704,0.000045751094,0.000024960558,0.9926643,0.001252286,0.0052247597,0.0004922432,0.000006211456],"about_ca_topic_score_codex":0.0037950687,"about_ca_topic_score_gemma":0.0034612927,"teacher_disagreement_score":0.0037950687,"about_ca_system_score_codex":0.0013791589,"about_ca_system_score_gemma":0.0012794945,"threshold_uncertainty_score":0.012527525},"labels":[],"label_agreement":null},{"id":"W4387197967","doi":"10.1007/978-3-031-44274-2_31","title":"Dispersion of Mobile Robots in Spite of Faults","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Robot; Algorithm; Combinatorics; Binary logarithm; A priori and a posteriori; Computer science; Node (physics); Discrete mathematics; Topology (electrical circuits); Physics; Mathematics; Artificial intelligence","score_opus":0.020573518830420332,"score_gpt":0.2671426386499722,"score_spread":0.24656911981955185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387197967","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7571499,0.0021324386,0.21281026,0.0015638429,0.00039605278,0.000044113724,0.00016478036,0.00037673587,0.02536194],"genre_scores_gemma":[0.9925788,0.00025067438,0.0026538866,0.000039792925,0.00007348211,0.000013253111,0.000044864722,0.00004186992,0.004303308],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978024,0.000031337127,0.000011406239,0.000048087866,0.00008302304,0.000045813442],"domain_scores_gemma":[0.99853706,0.0006327804,0.00031579225,0.00015023645,0.00019584216,0.00016829521],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028831355,0.00043879036,0.00081967935,0.0011755442,0.0007137861,0.0011093414,0.0010661483,0.0015384473,0.0017300928],"category_scores_gemma":[0.0035885726,0.0003820329,0.00039286693,0.00071794493,0.0013366237,0.0012573051,0.0011580636,0.0007853946,0.0003327048],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006006745,0.00008055428,0.0045701135,0.00022729668,0.00009990964,0.001192,0.00080784777,0.8374165,0.029393615,0.0844755,0.0032874013,0.037848584],"study_design_scores_gemma":[0.000035255485,0.0001737689,0.0021836676,0.00002613948,0.000022933766,0.0003589638,0.00029717738,0.94413126,0.002512908,0.04847954,0.00174786,0.000030570816],"about_ca_topic_score_codex":0.0013153915,"about_ca_topic_score_gemma":0.00069206004,"teacher_disagreement_score":0.0017300928,"about_ca_system_score_codex":0.0006443169,"about_ca_system_score_gemma":0.0002468494,"threshold_uncertainty_score":0.00578773},"labels":[],"label_agreement":null},{"id":"W4387198151","doi":"10.1007/978-3-031-44274-2_13","title":"The Fagnano Triangle Patrolling Problem (Extended Abstract)","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Patrolling; Dynamical billiards; Optimization problem; Computer science; Trajectory; Inscribed figure; Enhanced Data Rates for GSM Evolution; Mathematics; Mathematical optimization; Algorithm; Artificial intelligence; Geometry; Physics","score_opus":0.02806134879993998,"score_gpt":0.2626317303766687,"score_spread":0.23457038157672871,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387198151","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06791516,0.0057050716,0.5424234,0.0034547218,0.0019615653,0.0003737841,0.001819286,0.0011393094,0.3752077],"genre_scores_gemma":[0.41718042,0.0048570205,0.32631904,0.00090276316,0.00092643197,0.00043927965,0.0032988908,0.00066773075,0.24540846],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99979526,0.000029272538,0.000005925372,0.000072147675,0.00005842658,0.000038985505],"domain_scores_gemma":[0.9998311,0.00007750528,0.000018752433,0.000032744992,0.000019931922,0.000019998162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016375941,0.0008014189,0.000801033,0.00053259544,0.0008268262,0.0012272572,0.0012066598,0.0014832279,0.038704567],"category_scores_gemma":[0.0010398097,0.00030160736,0.0006159883,0.0011120468,0.00073786365,0.0014628266,0.0011922069,0.0016546092,0.004336875],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003100265,0.00016433159,0.00054695195,0.0007344229,0.000034078774,0.000520494,0.00017465219,0.17992164,0.008097755,0.22777434,0.09445192,0.48726946],"study_design_scores_gemma":[0.00009248208,0.00016929003,0.0011225017,0.00022196026,0.000029734225,0.0006988384,0.00022022057,0.33955243,0.004391807,0.47182018,0.18163443,0.0000461108],"about_ca_topic_score_codex":0.00371426,"about_ca_topic_score_gemma":0.003675363,"teacher_disagreement_score":0.038704567,"about_ca_system_score_codex":0.00062033214,"about_ca_system_score_gemma":0.00043835072,"threshold_uncertainty_score":0.1294797},"labels":[],"label_agreement":null},{"id":"W4387253309","doi":"10.32920/24231046.v1","title":"A Multi-Objective Optimization Problem on Evacuating 2 Robots from the Disk in the Face-to-Face Model; Trade-Offs between Worst-Case and Average-Case Analysis","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Parameterized complexity; Face (sociological concept); Computer science; Robot; Mathematical optimization; Mathematics; Algorithm; Artificial intelligence","score_opus":0.09051657174406798,"score_gpt":0.32414557347285106,"score_spread":0.2336290017287831,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387253309","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03842275,0.00092602207,0.95140165,0.0016294072,0.00013181029,0.00023862477,0.00058477605,0.00033233847,0.006332619],"genre_scores_gemma":[0.59161776,0.00093431456,0.3931905,0.0007632383,0.00026715946,0.00084433967,0.0011154764,0.00048973074,0.0107775135],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99726605,0.0011847637,0.00009735726,0.00077476725,0.0002944851,0.0003825356],"domain_scores_gemma":[0.9929073,0.0054188636,0.0006051905,0.00033272675,0.00026936783,0.0004665075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038891342,0.0032233237,0.003497793,0.00089532894,0.0011102516,0.0023287635,0.0038842515,0.0044696424,0.008491391],"category_scores_gemma":[0.011273926,0.0012228783,0.0024354279,0.0011731829,0.0018649191,0.0038159348,0.0027130574,0.0038368788,0.00094068074],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016227328,0.000085622174,0.00027630478,0.000169094,0.000064634885,0.00011697429,0.000049882994,0.97566944,0.00039202353,0.011759001,0.0022497457,0.009004957],"study_design_scores_gemma":[0.000027222448,0.00006828037,0.00012072857,0.000019769313,0.000014187305,0.00003857006,0.000035764875,0.98764044,0.00018815276,0.011308988,0.0005258614,0.000012087356],"about_ca_topic_score_codex":0.0059398892,"about_ca_topic_score_gemma":0.004037305,"teacher_disagreement_score":0.008491391,"about_ca_system_score_codex":0.0021674929,"about_ca_system_score_gemma":0.0018672148,"threshold_uncertainty_score":0.02840656},"labels":[],"label_agreement":null},{"id":"W4387409735","doi":"10.1007/s00454-023-00597-8","title":"On the Spanning and Routing Ratio of the Directed Theta-Four Graph","year":2023,"lang":"en","type":"article","venue":"Discrete & Computational Geometry","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa; Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Combinatorics; Vertex (graph theory); Mathematics; Computer science; Graph; Euclidean distance; Discrete mathematics; Artificial intelligence","score_opus":0.030246869920199745,"score_gpt":0.26529246000904205,"score_spread":0.2350455900888423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387409735","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.82678056,0.0047468613,0.095196754,0.0032169097,0.00021759115,0.00007238343,0.0007544383,0.00038365292,0.06863079],"genre_scores_gemma":[0.9765113,0.0017957406,0.016427357,0.00027223115,0.00022477271,0.000054528482,0.0003703039,0.00018163634,0.0041622417],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989054,0.000514615,0.000032932203,0.00019036108,0.00018117117,0.00017546906],"domain_scores_gemma":[0.98307496,0.013773287,0.0012335902,0.00047122312,0.0006540302,0.0007929461],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022308347,0.00089582003,0.0010601999,0.0031521823,0.0007627738,0.0019521473,0.0020334772,0.0009306614,0.00828416],"category_scores_gemma":[0.01902897,0.00048271695,0.00048610638,0.001981483,0.00181181,0.0034786703,0.0011690552,0.0014837133,0.0008385745],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0014186228,0.00024842084,0.0075347237,0.0005516429,0.00015534893,0.0003282578,0.0007122278,0.19306593,0.011414364,0.6843354,0.014048451,0.08618668],"study_design_scores_gemma":[0.000106730535,0.0002751631,0.0052926075,0.0001092472,0.00015430718,0.00075278484,0.00062619726,0.51480716,0.003995458,0.46895027,0.004864847,0.000065194],"about_ca_topic_score_codex":0.0019182768,"about_ca_topic_score_gemma":0.0012277424,"teacher_disagreement_score":0.00828416,"about_ca_system_score_codex":0.0016113926,"about_ca_system_score_gemma":0.00066768436,"threshold_uncertainty_score":0.02771324},"labels":[],"label_agreement":null},{"id":"W4387730855","doi":"10.36227/techrxiv.24311155","title":"A Dynamic Vacancy-Applicant Matching System Considering Locking Periods and Break-up Penalties","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Flexibility (engineering); Computer science; Workload; The Internet; Blossom algorithm; Stability (learning theory); Distributed computing; Labour economics; Economics; Mathematics; Machine learning; World Wide Web; Management","score_opus":0.03398303610395465,"score_gpt":0.28568218080100743,"score_spread":0.2516991446970528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387730855","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.072483696,0.00019931856,0.92130023,0.0004928404,0.00010141011,0.00016379714,0.0001639606,0.00039250418,0.0047022793],"genre_scores_gemma":[0.84060836,0.00015277525,0.14969376,0.00017285028,0.00008358406,0.00022112044,0.00021674432,0.00006084669,0.0087899575],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985886,0.0004101618,0.000079004865,0.0004484634,0.00017941932,0.0002943076],"domain_scores_gemma":[0.9982424,0.0007475056,0.00024807,0.00016044811,0.00029352732,0.0003080414],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024141714,0.0005404408,0.0015440367,0.0007947319,0.0012902803,0.0017478,0.002890488,0.0017021374,0.0054380163],"category_scores_gemma":[0.0040212674,0.0004896641,0.0005476849,0.0015208522,0.0007265405,0.0015488614,0.0015980881,0.0010353837,0.0008102865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006065128,0.00034409773,0.0020620353,0.00014674336,0.000076070304,0.00023850893,0.000209708,0.7972755,0.0058376016,0.05201761,0.0057268497,0.13545875],"study_design_scores_gemma":[0.00003824437,0.00009521915,0.00019736229,0.000004553612,0.000011233182,0.00006425711,0.000023704612,0.99219185,0.00047471072,0.005555626,0.0013305213,0.000012702305],"about_ca_topic_score_codex":0.0038820251,"about_ca_topic_score_gemma":0.0022894572,"teacher_disagreement_score":0.0054380163,"about_ca_system_score_codex":0.0013005444,"about_ca_system_score_gemma":0.0025453654,"threshold_uncertainty_score":0.018191993},"labels":[],"label_agreement":null},{"id":"W4387730956","doi":"10.36227/techrxiv.24311155.v1","title":"A Dynamic Vacancy-Applicant Matching System Considering Locking Periods and Break-up Penalties","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Matching (statistics); Flexibility (engineering); Workload; Computer science; The Internet; Stability (learning theory); Blossom algorithm; Distributed computing; Labour economics; Economics; Mathematics; Machine learning; World Wide Web","score_opus":0.03398303610395465,"score_gpt":0.28568218080100743,"score_spread":0.2516991446970528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387730956","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07741348,0.00016658727,0.91706115,0.0004392319,0.00009820367,0.0001874862,0.00013771246,0.00041330623,0.004082806],"genre_scores_gemma":[0.82562304,0.00013967355,0.16616818,0.00016358717,0.000087029846,0.00024633599,0.00019077351,0.00005748297,0.0073239254],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861,0.00040229972,0.00008005207,0.00042896476,0.00019519935,0.00028341377],"domain_scores_gemma":[0.9982626,0.0007107683,0.00024859657,0.00017049948,0.00029710607,0.00031037076],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024546643,0.00053099316,0.001456642,0.00084193045,0.0014180419,0.001628031,0.00282507,0.0016000058,0.004735333],"category_scores_gemma":[0.004137354,0.0004430877,0.0005307174,0.0014966498,0.00070852943,0.0014887077,0.0015332199,0.0010028697,0.00072975433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00065445533,0.00048035744,0.0026958967,0.00016165772,0.00008440596,0.00026140094,0.00026028437,0.7470371,0.008185406,0.058615595,0.005925983,0.17563748],"study_design_scores_gemma":[0.000051732513,0.00012844964,0.00028904012,0.0000052061164,0.000014542827,0.00009061458,0.000029791718,0.9896813,0.0007433911,0.006950279,0.0019989717,0.00001660751],"about_ca_topic_score_codex":0.0032584963,"about_ca_topic_score_gemma":0.002032771,"teacher_disagreement_score":0.004735333,"about_ca_system_score_codex":0.001282052,"about_ca_system_score_gemma":0.0027482428,"threshold_uncertainty_score":0.015841246},"labels":[],"label_agreement":null},{"id":"W4387872170","doi":"10.1016/j.ipl.2023.106455","title":"Deterministic treasure hunt and rendezvous in arbitrary connected graphs","year":2023,"lang":"en","type":"article","venue":"Information Processing Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Treasure; Rendezvous; Traverse; Time complexity; Computer science; Algorithm; Node (physics); Connectivity; Combinatorics; Mathematics; Graph; Discrete mathematics; Theoretical computer science","score_opus":0.01283665702480478,"score_gpt":0.23167264811662977,"score_spread":0.218835991091825,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387872170","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5889347,0.0010330473,0.36300805,0.002366001,0.00022792297,0.00016831,0.0006453889,0.0006772784,0.04293937],"genre_scores_gemma":[0.9626957,0.00035511455,0.021901522,0.00019015564,0.00004716567,0.00008868107,0.00026494171,0.00017621172,0.014280523],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991855,0.00024251635,0.000029838084,0.00019743365,0.00012665661,0.00021801685],"domain_scores_gemma":[0.99287754,0.0052291984,0.0005332571,0.0005495924,0.00024898688,0.00056136504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009159305,0.0007272388,0.0018204491,0.0012183007,0.0017608847,0.0023745245,0.0026053651,0.002569356,0.0071164607],"category_scores_gemma":[0.010497676,0.0010143656,0.0011306459,0.0016251829,0.0032056663,0.0040520453,0.0031961587,0.0021929627,0.000661219],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000731273,0.00009278977,0.0010890376,0.00018773567,0.00010628462,0.0004598803,0.00031261734,0.5292956,0.0024211318,0.4470129,0.0049377615,0.013352997],"study_design_scores_gemma":[0.00007281315,0.00004276988,0.00029230805,0.000020324827,0.000021380543,0.00009772725,0.00012225767,0.6220347,0.00079112704,0.3755867,0.0008888313,0.000029018505],"about_ca_topic_score_codex":0.005110996,"about_ca_topic_score_gemma":0.005728913,"teacher_disagreement_score":0.0071164607,"about_ca_system_score_codex":0.0014921025,"about_ca_system_score_gemma":0.0010435539,"threshold_uncertainty_score":0.02380693},"labels":[],"label_agreement":null},{"id":"W4388184697","doi":"10.48550/arxiv.2310.20401","title":"Utilitarian Algorithm Configuration","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Machine Intelligence Institute; Compute Canada; Defense Advanced Research Projects Agency; Canadian Institute for Advanced Research; National Science Foundation","keywords":"Computer science; Heuristic; Bounded function; Contrast (vision); Monotonic function; Runtime verification; Heuristics; Algorithm; Minification; Mathematical optimization; Mathematics; Programming language; Artificial intelligence","score_opus":0.13566098039637664,"score_gpt":0.21102936714132473,"score_spread":0.07536838674494808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388184697","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018219734,0.00022452426,0.9623785,0.00050336064,0.000069946305,0.0002444856,0.00010314684,0.0031211749,0.015135053],"genre_scores_gemma":[0.47533196,0.00020114452,0.51654893,0.0004159076,0.00010806969,0.0008049679,0.0004053864,0.0011387019,0.0050450144],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9874865,0.005823906,0.0007962548,0.0016416118,0.0031997135,0.0010520838],"domain_scores_gemma":[0.97506106,0.009200555,0.0015225094,0.01164883,0.0018399943,0.00072713074],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006920076,0.0016730648,0.0013522299,0.0018289369,0.0015261386,0.0037614107,0.004245139,0.0025531214,0.010039001],"category_scores_gemma":[0.03914866,0.0011015822,0.0012211703,0.0015945717,0.0043171695,0.0051126764,0.006508326,0.004444274,0.003905706],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008986694,0.0004546556,0.002690957,0.00053746375,0.00017317489,0.0003163939,0.0006871989,0.22675894,0.012314972,0.5011903,0.011324534,0.24265267],"study_design_scores_gemma":[0.00013491236,0.00038468707,0.00037245912,0.00011858267,0.000061968276,0.0004000082,0.00014361428,0.6149567,0.012766606,0.35567325,0.014912268,0.00007495817],"about_ca_topic_score_codex":0.00034099584,"about_ca_topic_score_gemma":0.00060153025,"teacher_disagreement_score":0.010039001,"about_ca_system_score_codex":0.0016912346,"about_ca_system_score_gemma":0.0029083,"threshold_uncertainty_score":0.036597252},"labels":[],"label_agreement":null},{"id":"W4388734332","doi":"10.37236/11548","title":"Separating the Online and Offline DP-Chromatic Numbers","year":2023,"lang":"en","type":"article","venue":"The Electronic Journal of Combinatorics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Chromatic scale; Combinatorics; Mathematics; Fractional coloring; List coloring; Cover (algebra); Graph; Greedy coloring; Generalization; Edge coloring; Discrete mathematics; Transversal (combinatorics); Graph coloring; Graph power; Line graph","score_opus":0.012988599195016078,"score_gpt":0.2682370579565959,"score_spread":0.2552484587615798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388734332","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5128515,0.0010612595,0.41034532,0.0036367236,0.00025182526,0.0002185018,0.0015302572,0.001269145,0.06883546],"genre_scores_gemma":[0.91613495,0.00032253662,0.07393804,0.00040476152,0.00009971358,0.00021422391,0.0006431242,0.00039470653,0.007847971],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99678636,0.0007347559,0.00009284071,0.0010922172,0.00055255013,0.0007413086],"domain_scores_gemma":[0.9819786,0.010833053,0.00096545933,0.0042808936,0.0009268302,0.0010152225],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026424583,0.00084459817,0.0011778902,0.0008952591,0.001405021,0.0031887689,0.0036617666,0.0016562161,0.009072241],"category_scores_gemma":[0.014389164,0.0006811902,0.0006675807,0.0011839839,0.0030877846,0.011193225,0.0036385856,0.003941305,0.00089669373],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.002142042,0.00072167267,0.006281996,0.0005317887,0.00008537014,0.00029929922,0.0007448058,0.15511853,0.02135435,0.65909517,0.014018629,0.13960637],"study_design_scores_gemma":[0.00020388061,0.00021692093,0.0034642667,0.000112061374,0.00005500119,0.0003161266,0.00044299685,0.4134292,0.014868022,0.5554376,0.011374925,0.000079065045],"about_ca_topic_score_codex":0.0020612963,"about_ca_topic_score_gemma":0.002964507,"teacher_disagreement_score":0.009072241,"about_ca_system_score_codex":0.0035934013,"about_ca_system_score_gemma":0.0024392144,"threshold_uncertainty_score":0.030349672},"labels":[],"label_agreement":null},{"id":"W4388750673","doi":"10.1145/3610940","title":"Almost-Linear-Time Algorithms for Maximum Flow and Minimum-Cost Flow","year":2023,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Minimum-cost flow problem; Amortized analysis; Mathematics; Minimum cut; Separable space; Algorithm; Time complexity; Maximum flow problem; Bounded function; Regular polygon; Combinatorics; Directed graph; Discrete mathematics; Mathematical optimization; Computer science; Flow network; Data structure","score_opus":0.09238388434712162,"score_gpt":0.3403967687830984,"score_spread":0.24801288443597674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388750673","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009647456,0.00026032646,0.98207366,0.00033543585,0.000044915796,0.00010233845,0.00033396596,0.0032762985,0.003925614],"genre_scores_gemma":[0.12858796,0.00017763245,0.8667542,0.00014356882,0.00007058881,0.00027380933,0.0011054819,0.00054840074,0.0023383843],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988171,0.0002618127,0.00008183809,0.00031603873,0.00034026182,0.00018300042],"domain_scores_gemma":[0.9974254,0.0013106237,0.00024038508,0.0005919894,0.00034520967,0.00008640841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010397057,0.0017030654,0.0009422389,0.0013768878,0.00089703844,0.0013399803,0.0023474912,0.0012846335,0.008552251],"category_scores_gemma":[0.0072115255,0.0007496468,0.0010186009,0.0020521737,0.00090223347,0.0041487273,0.0018194407,0.001993864,0.0020820464],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044094215,0.00027150274,0.0011996891,0.00041006523,0.00008189956,0.0001074336,0.00020560525,0.44005775,0.005867892,0.1024219,0.021665946,0.4272693],"study_design_scores_gemma":[0.0000638083,0.00003400598,0.00018782206,0.000016153293,0.00001242491,0.000060040296,0.000036233334,0.89682835,0.0023243027,0.09744128,0.0029811668,0.000014369942],"about_ca_topic_score_codex":0.0044949623,"about_ca_topic_score_gemma":0.0067623034,"teacher_disagreement_score":0.008552251,"about_ca_system_score_codex":0.0021233703,"about_ca_system_score_gemma":0.0025079434,"threshold_uncertainty_score":0.02861011},"labels":[],"label_agreement":null},{"id":"W4388822224","doi":"10.1080/10236198.2023.2284831","title":"Controlled two-dimensional Markov chains between two absorbing barriers","year":2023,"lang":"en","type":"article","venue":"The Journal of Difference Equations and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Markov chain; Constructive; Continuation; Mathematics; Balance equation; Chain (unit); Bellman equation; Mathematical economics; Combinatorics; Discrete mathematics; Pure mathematics; Calculus (dental); Applied mathematics; Markov model; Computer science; Statistics; Process (computing)","score_opus":0.03146093346602658,"score_gpt":0.30175801773249183,"score_spread":0.27029708426646526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388822224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39615726,0.00058599224,0.5826992,0.0012449877,0.00017444858,0.00013218322,0.00033762943,0.00028013467,0.018388119],"genre_scores_gemma":[0.9701332,0.00021237822,0.01922742,0.00011796641,0.000029375951,0.00021696743,0.00015294476,0.000026022028,0.009883727],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9992925,0.00019388902,0.000036887035,0.00017697943,0.00012524016,0.00017451517],"domain_scores_gemma":[0.99683255,0.0018354541,0.00048747414,0.00016496604,0.00025631394,0.00042326283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001195893,0.00061509275,0.0010974407,0.0007453709,0.0007227913,0.0021626942,0.0016753227,0.0016292972,0.005103388],"category_scores_gemma":[0.0042113787,0.0005666774,0.0008235329,0.0004746425,0.0028111995,0.0016565938,0.0018234964,0.0016134467,0.00033625436],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00042663867,0.00011697438,0.0015769058,0.00009786484,0.00007979973,0.000528789,0.00022241489,0.593268,0.006605962,0.39246023,0.0007266503,0.0038897719],"study_design_scores_gemma":[0.00007925883,0.000057023623,0.00019545098,0.000016951893,0.00001774332,0.00002151691,0.000030778578,0.9630465,0.0007588376,0.035276663,0.00047466467,0.000024655546],"about_ca_topic_score_codex":0.0050949673,"about_ca_topic_score_gemma":0.0029628612,"teacher_disagreement_score":0.005103388,"about_ca_system_score_codex":0.001620859,"about_ca_system_score_gemma":0.0011669336,"threshold_uncertainty_score":0.017072499},"labels":[],"label_agreement":null},{"id":"W4388906604","doi":"10.1016/j.tcs.2023.114313","title":"Deterministic rendezvous in infinite trees","year":2023,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Rendezvous; Computer science; Combinatorics; Node (physics); Tree (set theory); Mathematics; Discrete mathematics; Time complexity; Graph; Binary logarithm; Set (abstract data type); Algorithm","score_opus":0.02155835231924106,"score_gpt":0.28771762123303984,"score_spread":0.26615926891379876,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388906604","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47950968,0.0015877119,0.47962266,0.0016567041,0.00014960223,0.00007715109,0.0004400731,0.00092727685,0.036029153],"genre_scores_gemma":[0.9562811,0.0003933478,0.03151479,0.00011646992,0.000043460495,0.00006779676,0.00022119694,0.00024127423,0.011120567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99881375,0.00035914226,0.00006108886,0.0002586536,0.00024156207,0.00026575298],"domain_scores_gemma":[0.98833627,0.009085203,0.00060447585,0.0009203326,0.00041987118,0.0006337249],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00136147,0.00044325713,0.0014519771,0.0010528944,0.002191788,0.0027019135,0.0021027406,0.0018383372,0.006584801],"category_scores_gemma":[0.0141587015,0.0009825914,0.000735672,0.0013700083,0.003257925,0.005173117,0.003544029,0.0024003477,0.0007734074],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003716151,0.00006646927,0.00085925584,0.00016676335,0.000043502652,0.000308825,0.00052929827,0.20962049,0.002596789,0.76829284,0.0025532185,0.014590873],"study_design_scores_gemma":[0.000043842647,0.00002310537,0.00014158127,0.00003080068,0.000018033837,0.00011430108,0.00015790362,0.37936053,0.0010592764,0.6172289,0.0018019398,0.00001985469],"about_ca_topic_score_codex":0.0029910668,"about_ca_topic_score_gemma":0.0037538798,"teacher_disagreement_score":0.006584801,"about_ca_system_score_codex":0.0017150595,"about_ca_system_score_gemma":0.000866532,"threshold_uncertainty_score":0.022028327},"labels":[],"label_agreement":null},{"id":"W4388964502","doi":"10.48550/arxiv.2311.12976","title":"Fast Deterministic Rendezvous in Labeled Lines","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Rendezvous; Upper and lower bounds; Node (physics); Combinatorics; Matching (statistics); Path (computing); Binary logarithm; Integer (computer science); Mathematics; Time complexity; Discrete mathematics; Line (geometry); Position (finance); Computer science; Physics; Computer network; Geometry; Mathematical analysis","score_opus":0.1485900232893051,"score_gpt":0.22110459024087997,"score_spread":0.07251456695157488,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388964502","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.170986,0.0003932653,0.81310266,0.0005737306,0.000058429734,0.00019212144,0.00037857285,0.0035251838,0.010789964],"genre_scores_gemma":[0.7281204,0.00025378508,0.2570208,0.00025087912,0.00003283786,0.00021002015,0.0008317698,0.0005107158,0.012768791],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.997736,0.00048658298,0.00010448546,0.000693101,0.00039228017,0.000587666],"domain_scores_gemma":[0.9960705,0.0019583649,0.00055840786,0.0008979735,0.00030060508,0.00021401176],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008768101,0.00092875777,0.0009657757,0.00067630125,0.001568318,0.0017483725,0.0023783806,0.0017146579,0.0057225362],"category_scores_gemma":[0.0051624067,0.00060201064,0.00088914804,0.0013312293,0.0018111444,0.0043351864,0.0026834155,0.0012825882,0.0017170479],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015661427,0.00024697647,0.002169175,0.00033446634,0.0001315407,0.00067409273,0.001074301,0.71052456,0.033082042,0.14725536,0.0062529524,0.09668838],"study_design_scores_gemma":[0.00016769458,0.0001645449,0.0002995578,0.000035071505,0.000025433046,0.00022456737,0.00025997355,0.85790235,0.019907739,0.11182892,0.009130431,0.000053666077],"about_ca_topic_score_codex":0.006039602,"about_ca_topic_score_gemma":0.0053529353,"teacher_disagreement_score":0.006039602,"about_ca_system_score_codex":0.0021733886,"about_ca_system_score_gemma":0.00095026096,"threshold_uncertainty_score":0.01914376},"labels":[],"label_agreement":null},{"id":"W4389151102","doi":"10.1017/s0269888923000103","title":"Adaptive learning with artificial barriers yielding Nash equilibria in general games","year":2023,"lang":"en","type":"article","venue":"The Knowledge Engineering Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Nash equilibrium; Computer science; Reinforcement learning; Learning automata; Game theory; Fictitious play; Convergence (economics); Saddle point; Mathematical economics; Normal-form game; Repeated game; Artificial intelligence; Mathematical optimization; Mathematics; Automaton; Economics","score_opus":0.027753008466118806,"score_gpt":0.2696783488624332,"score_spread":0.2419253403963144,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389151102","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1563983,0.0011999822,0.8283564,0.00071768736,0.000058922717,0.000093985356,0.000032772765,0.00017819542,0.012963796],"genre_scores_gemma":[0.95290524,0.00057551055,0.04424997,0.00009074985,0.000022134998,0.000104187995,0.000020890506,0.000015820859,0.0020154202],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99934953,0.00034323902,0.00003752141,0.00009501889,0.000113088616,0.00006165943],"domain_scores_gemma":[0.9981165,0.0013607179,0.00017585812,0.00008567208,0.00017017435,0.000091118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012880818,0.000396091,0.0006084693,0.00047950997,0.00032981831,0.0010190372,0.00082406704,0.00078560447,0.0016219782],"category_scores_gemma":[0.004704352,0.00022567053,0.00048800194,0.00030674276,0.0014746366,0.0013607396,0.0012103671,0.00085535436,0.00018790686],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006417306,0.0000840619,0.0008275435,0.0002633214,0.000090912356,0.000111671696,0.00015367311,0.64256483,0.0054932125,0.32296515,0.00060090283,0.026780477],"study_design_scores_gemma":[0.000017733955,0.000056596185,0.00013359862,0.000021109381,0.000010109989,0.000027213093,0.000020788375,0.91326356,0.0008431767,0.08465705,0.00094065117,0.000008443781],"about_ca_topic_score_codex":0.0012307568,"about_ca_topic_score_gemma":0.0008598861,"teacher_disagreement_score":0.0016219782,"about_ca_system_score_codex":0.00074332417,"about_ca_system_score_gemma":0.0005598795,"threshold_uncertainty_score":0.0068121552},"labels":[],"label_agreement":null},{"id":"W4389486639","doi":"10.1007/978-3-031-49190-0_27","title":"Delaying Decisions and Reservation Costs","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Reservation; Upper and lower bounds; Vertex cover; Competitive analysis; Vertex (graph theory); Edge cover; Computer science; Graph; Set (abstract data type); Online algorithm; Mathematical optimization; Combinatorics; Mathematics; Algorithm; Theoretical computer science","score_opus":0.0560672355227835,"score_gpt":0.29522076528910074,"score_spread":0.23915352976631724,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389486639","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.121778175,0.018420642,0.33325484,0.0077133398,0.002297695,0.00010507167,0.0004287621,0.00030508378,0.5156963],"genre_scores_gemma":[0.8154564,0.008285309,0.01981263,0.0003556573,0.0008981211,0.0000724408,0.00016125166,0.00012974533,0.15482841],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99955696,0.0001406381,0.000021988611,0.00006938904,0.00011895029,0.00009205819],"domain_scores_gemma":[0.99593806,0.003326258,0.00021340145,0.00021089656,0.00016744243,0.00014403157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010938648,0.0006485927,0.00061753165,0.00041699485,0.00051931676,0.002640157,0.001334399,0.0012184572,0.025324741],"category_scores_gemma":[0.0069414517,0.00053942,0.00037229416,0.0010632438,0.0009648239,0.0029810015,0.00045814496,0.0025592148,0.0016059292],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00023905627,0.00008468489,0.00031914047,0.00012982634,0.000017809196,0.00015220838,0.00010010793,0.055272073,0.0011645551,0.8707389,0.009585561,0.062196106],"study_design_scores_gemma":[0.0000417421,0.0000769175,0.00044073965,0.000048857062,0.000029019357,0.00018474793,0.00011634784,0.08213698,0.0005216831,0.8969872,0.019390156,0.000025638788],"about_ca_topic_score_codex":0.0011545484,"about_ca_topic_score_gemma":0.0009799368,"teacher_disagreement_score":0.025324741,"about_ca_system_score_codex":0.0017404103,"about_ca_system_score_gemma":0.0007815902,"threshold_uncertainty_score":0.08471966},"labels":[],"label_agreement":null},{"id":"W4390015024","doi":"10.1007/978-3-031-47126-1_5","title":"Discrete Planar Two-Watchtower Problem for k-Visibility","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes on data engineering and communications technologies","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Visibility; Planar; Computer science; Physics; Optics; Computer graphics (images)","score_opus":0.06622032969838589,"score_gpt":0.29840739100140007,"score_spread":0.2321870613030142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390015024","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19854586,0.0010611586,0.70455045,0.0034521765,0.00044540034,0.00030839656,0.002639695,0.0005751126,0.08842177],"genre_scores_gemma":[0.7458314,0.0015690052,0.17432898,0.000447282,0.00038933498,0.000382182,0.0032356412,0.0004648456,0.07335127],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99957365,0.00008038863,0.000020115547,0.00012575071,0.00008664367,0.00011346533],"domain_scores_gemma":[0.99907184,0.00047216102,0.000114696726,0.000101415164,0.00008121775,0.00015869092],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004194633,0.00093803334,0.0015662011,0.00060919585,0.00096908415,0.003137225,0.002412548,0.0025307995,0.014977185],"category_scores_gemma":[0.0028647957,0.0005671632,0.0009334832,0.001242089,0.0013407335,0.004081546,0.0026639185,0.003311003,0.0011582004],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000754284,0.00023907967,0.0006829814,0.0007615237,0.00008126441,0.0004066312,0.0004410681,0.15906739,0.0068008937,0.7008399,0.03370352,0.09622152],"study_design_scores_gemma":[0.00017836364,0.00011671076,0.0005227467,0.00007722952,0.00003291297,0.0002407224,0.00035019073,0.3784568,0.002449846,0.6037514,0.013774262,0.00004879726],"about_ca_topic_score_codex":0.0032536248,"about_ca_topic_score_gemma":0.0019539525,"teacher_disagreement_score":0.014977185,"about_ca_system_score_codex":0.0012497832,"about_ca_system_score_gemma":0.0011542982,"threshold_uncertainty_score":0.050103664},"labels":[],"label_agreement":null},{"id":"W4390072545","doi":"10.1007/978-3-031-49815-2_2","title":"A Frequency-Competitive Query Strategy for Maintaining Low Collision Potential Among Moving Entities","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Intersection (aeronautics); Granularity; Graph; Bounded function; Collision; Upper and lower bounds; Query optimization; Theoretical computer science; Data mining; Mathematics","score_opus":0.021075625155129417,"score_gpt":0.2584254129373303,"score_spread":0.23734978778220087,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390072545","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053551026,0.0007757273,0.9371281,0.00032592786,0.00016268816,0.00024176652,0.00014790127,0.00084059266,0.0068262215],"genre_scores_gemma":[0.7753745,0.0004704922,0.21601447,0.00025364646,0.00023624691,0.00022553673,0.0002754076,0.00012350795,0.007026176],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99884063,0.00015787057,0.000054782904,0.00021838163,0.00050419144,0.00022418403],"domain_scores_gemma":[0.99759585,0.0008858523,0.00017388309,0.00041363272,0.00070832175,0.00022252226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009823379,0.0009213849,0.001903975,0.0017311531,0.0017391267,0.0015579973,0.004955022,0.0019279014,0.0034291933],"category_scores_gemma":[0.0049834116,0.0004355212,0.0005360824,0.002396049,0.0009172497,0.0022833017,0.0018809662,0.00085335993,0.0010775329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001206366,0.0008650244,0.00304882,0.0004977418,0.0002006023,0.0008030871,0.00066049147,0.24601282,0.115300074,0.11996168,0.024092078,0.48735118],"study_design_scores_gemma":[0.00006076378,0.00033076244,0.000419749,0.000009072079,0.000055592354,0.0006991145,0.00012703828,0.9748989,0.006857111,0.013817368,0.0026753093,0.000049201957],"about_ca_topic_score_codex":0.0057721897,"about_ca_topic_score_gemma":0.0051975423,"teacher_disagreement_score":0.0057721897,"about_ca_system_score_codex":0.0010527911,"about_ca_system_score_gemma":0.0017811346,"threshold_uncertainty_score":0.011477232},"labels":[],"label_agreement":null},{"id":"W4390072547","doi":"10.1007/978-3-031-49815-2_13","title":"Any-Order Online Interval Selection","year":2023,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Competitive analysis; Online algorithm; Computer science; Bounded function; Scheduling (production processes); Interval (graph theory); Algorithm; Randomized algorithm; Selection (genetic algorithm); Deterministic algorithm; Order (exchange); Mathematical optimization; Mathematics; Upper and lower bounds; Artificial intelligence; Combinatorics","score_opus":0.03156848898930621,"score_gpt":0.28337998220595023,"score_spread":0.25181149321664403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390072547","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013298373,0.0015978705,0.8522152,0.00065556896,0.00075820525,0.00014301167,0.0008447733,0.002348966,0.12813805],"genre_scores_gemma":[0.34727532,0.0027561372,0.50026524,0.0006982949,0.0011806332,0.00029814008,0.00229467,0.0013604641,0.1438711],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991623,0.00014489346,0.000045269757,0.00015054531,0.00037797345,0.00011904197],"domain_scores_gemma":[0.99846435,0.000707954,0.000056514084,0.00053424085,0.00015282615,0.00008413991],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009800354,0.0008149636,0.001191251,0.0005692426,0.00052157737,0.0018444029,0.0016295997,0.0005752561,0.039256744],"category_scores_gemma":[0.0038723806,0.00041823095,0.00086771516,0.0016387266,0.00051078346,0.002460644,0.0013266078,0.0021840306,0.008071713],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00062771334,0.0002451241,0.00036930127,0.00038224194,0.000044358156,0.00015236903,0.00007521236,0.034861658,0.00564393,0.21597433,0.054755393,0.6868683],"study_design_scores_gemma":[0.00018892044,0.0003648926,0.00067369535,0.000117158044,0.000074030155,0.0005629419,0.000071831295,0.33956987,0.0076148855,0.55055654,0.100149125,0.000056133485],"about_ca_topic_score_codex":0.00047086322,"about_ca_topic_score_gemma":0.0008899172,"teacher_disagreement_score":0.039256744,"about_ca_system_score_codex":0.00060982694,"about_ca_system_score_gemma":0.0008883571,"threshold_uncertainty_score":0.13132691},"labels":[],"label_agreement":null},{"id":"W4390075113","doi":"10.2139/ssrn.4672523","title":"Adjoint-Based Enforcement of State Constraints in Pde Optimization Problems","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"","keywords":"Enforcement; State (computer science); Mathematical optimization; Computer science; Optimization problem; Mathematics; Political science; Algorithm; Law","score_opus":0.026846365907648717,"score_gpt":0.27087519831248386,"score_spread":0.24402883240483514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390075113","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015694724,0.00019045897,0.97567195,0.0005223797,0.00015420411,0.000044647575,0.000050346618,0.00025519647,0.0074160453],"genre_scores_gemma":[0.70498896,0.00028312163,0.28649426,0.00044981908,0.00016176476,0.00015565715,0.0001819098,0.000319307,0.0069651934],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988563,0.0005607462,0.000057330715,0.00009382185,0.00034293023,0.00008889908],"domain_scores_gemma":[0.99613273,0.0026466963,0.00026400058,0.0003710121,0.00042196547,0.00016371126],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029654894,0.0005438132,0.0012908679,0.0005629151,0.0005304314,0.0020824901,0.0010265422,0.0019260828,0.003755396],"category_scores_gemma":[0.009507243,0.0006510991,0.0005804509,0.0005408997,0.0016958185,0.0016313748,0.0028549249,0.0035321435,0.0003852162],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027745438,0.00022899082,0.0005202533,0.00022071367,0.000037381833,0.00013344019,0.00015640647,0.7057765,0.0073434077,0.21461691,0.0035638814,0.06712455],"study_design_scores_gemma":[0.000015210016,0.000023585584,0.00003393051,0.000012241807,0.0000023178827,0.0000106221305,0.000007854484,0.9783165,0.00063171715,0.020356169,0.000584689,0.0000051363795],"about_ca_topic_score_codex":0.0017422455,"about_ca_topic_score_gemma":0.0017457713,"teacher_disagreement_score":0.003755396,"about_ca_system_score_codex":0.000543066,"about_ca_system_score_gemma":0.0014390834,"threshold_uncertainty_score":0.015683234},"labels":[],"label_agreement":null},{"id":"W4390099784","doi":"10.1109/robio58561.2023.10354912","title":"ANMIP: Adaptive Navigation based on Mutual Information Perception in Uncertain Environments","year":2023,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Ministry of Education; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China; National Science Foundation","keywords":"Computer science; Perception; Mutual information; Human–computer interaction; Computer vision; Artificial intelligence; Psychology; Neuroscience","score_opus":0.025031853341866445,"score_gpt":0.26065721521859725,"score_spread":0.2356253618767308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390099784","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008972888,0.00012492109,0.9890211,0.00006853597,0.000028227849,0.000023909188,0.000028404265,0.0004408602,0.0012910926],"genre_scores_gemma":[0.64866424,0.0003575657,0.34693468,0.00014047282,0.00008494146,0.00022640245,0.00024940385,0.00013130896,0.0032109765],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995252,0.00007852622,0.00002748822,0.00012843215,0.000180801,0.000059619284],"domain_scores_gemma":[0.99951684,0.00021079244,0.00007061645,0.000041222593,0.0001214011,0.000039030405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005397293,0.0008136162,0.0009295121,0.0005966713,0.0006391868,0.0006958383,0.0014126679,0.00066757115,0.0019633884],"category_scores_gemma":[0.0016510944,0.00038976397,0.0007497215,0.0006225191,0.0005406528,0.0015109349,0.0015329015,0.0010095182,0.00023160006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00021065453,0.000097192744,0.0017629933,0.00018419209,0.00010697903,0.00018884012,0.00024778972,0.7235142,0.008708148,0.022919627,0.0037539639,0.23830543],"study_design_scores_gemma":[0.000011392059,0.000036472637,0.00019793543,0.0000037643267,0.000010486352,0.000030329033,0.000013443033,0.99482083,0.0009293433,0.0032158548,0.0007215232,0.000008719548],"about_ca_topic_score_codex":0.00869756,"about_ca_topic_score_gemma":0.004942317,"teacher_disagreement_score":0.00869756,"about_ca_system_score_codex":0.0006390952,"about_ca_system_score_gemma":0.0013082419,"threshold_uncertainty_score":0.01729387},"labels":[],"label_agreement":null},{"id":"W4391090600","doi":"10.1145/3631461.3631557","title":"Renting Servers in the Cloud: Parameterized Analysis of FirstFit","year":2024,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Server; Computer science; Cloud computing; Competitive analysis; Renting; Parameterized complexity; Online algorithm; Computer network; Distributed computing; Operating system; Upper and lower bounds; Algorithm; Mathematics","score_opus":0.029754977645739606,"score_gpt":0.2957998667472194,"score_spread":0.26604488910147983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391090600","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35936594,0.0025979974,0.59678686,0.0027617216,0.00017780164,0.0005093175,0.0018921673,0.0012150885,0.034693174],"genre_scores_gemma":[0.8909714,0.0017581919,0.0986435,0.0006399686,0.00027292516,0.00049488957,0.0017031817,0.0009395757,0.0045762346],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99656796,0.00082592334,0.000114724484,0.0006129038,0.000657072,0.0012213116],"domain_scores_gemma":[0.98104984,0.0123282,0.00244936,0.0016574733,0.0010048678,0.0015102169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030226961,0.0030847874,0.00287471,0.0016927714,0.0017231494,0.0044256523,0.0038257646,0.0026590847,0.008600934],"category_scores_gemma":[0.02253288,0.001156382,0.0029733258,0.0026772337,0.0028198587,0.006232529,0.0029312968,0.0046704016,0.0008233825],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005339939,0.00034871837,0.0042457706,0.000496723,0.00016209202,0.00034526282,0.0002706894,0.843615,0.00637985,0.121087775,0.0051604835,0.017353592],"study_design_scores_gemma":[0.000042720945,0.00014362464,0.0008768775,0.00004877927,0.00004086628,0.00017843854,0.000115576906,0.93072784,0.0014508225,0.0641573,0.002182801,0.000034370158],"about_ca_topic_score_codex":0.004799012,"about_ca_topic_score_gemma":0.0029121325,"teacher_disagreement_score":0.008600934,"about_ca_system_score_codex":0.0046860552,"about_ca_system_score_gemma":0.0028630826,"threshold_uncertainty_score":0.03399986},"labels":[],"label_agreement":null},{"id":"W4391095687","doi":"10.1145/3631461.3631543","title":"Maximal Independent Set via Mobile Agents","year":2024,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Set (abstract data type); Programming language","score_opus":0.029842197941870166,"score_gpt":0.30058255182076987,"score_spread":0.2707403538788997,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391095687","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10768382,0.0011724393,0.8784068,0.00082734774,0.00007774604,0.000105528794,0.0002245772,0.00024197467,0.011259663],"genre_scores_gemma":[0.7765197,0.0010659436,0.21212353,0.00015190008,0.00014185648,0.0003228694,0.00046905616,0.00008476076,0.009120353],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99922943,0.00033904202,0.000023938495,0.00019220792,0.00012403415,0.000091370224],"domain_scores_gemma":[0.9980842,0.001296785,0.00022274311,0.00013409775,0.000096152275,0.00016611563],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092687656,0.00067090365,0.0008625893,0.0009869434,0.0007015086,0.0011305322,0.0013129483,0.0009067982,0.0020934378],"category_scores_gemma":[0.0037037388,0.00045554602,0.0007829786,0.0010601247,0.0013329909,0.0019594175,0.0018472272,0.0011520364,0.00036745938],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001941871,0.00007788643,0.0011545472,0.00022257018,0.00014548187,0.00031188075,0.00026029328,0.61249787,0.0027205134,0.3433032,0.0030896754,0.03602196],"study_design_scores_gemma":[0.000038896982,0.000059407164,0.00019249646,0.000015675207,0.000026982314,0.00006654613,0.0000482188,0.76223457,0.0008823462,0.23310152,0.003318331,0.000014919605],"about_ca_topic_score_codex":0.0015989838,"about_ca_topic_score_gemma":0.0015169609,"teacher_disagreement_score":0.0020934378,"about_ca_system_score_codex":0.0009785477,"about_ca_system_score_gemma":0.00075770944,"threshold_uncertainty_score":0.007099867},"labels":[],"label_agreement":null},{"id":"W4391233586","doi":"10.2139/ssrn.4706325","title":"Approximate Linear Programming for a Queueing Control Problem","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Queueing theory; Linear programming; Computer science; Layered queueing network; Control (management); Mathematical optimization; Queueing system; Mathematics; Computer network; Artificial intelligence","score_opus":0.014583319534774082,"score_gpt":0.2810955688250589,"score_spread":0.2665122492902848,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391233586","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019434871,0.0008152099,0.96917266,0.0015548163,0.00012126735,0.00008638069,0.00015872424,0.00012104019,0.008534966],"genre_scores_gemma":[0.7738922,0.0015091912,0.19483107,0.0006049247,0.00050193374,0.0006861305,0.00050186506,0.0002738993,0.027198728],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986683,0.00064898835,0.000043044853,0.0001890435,0.000289376,0.00016113099],"domain_scores_gemma":[0.9933361,0.0057547526,0.00021485478,0.00013758919,0.00037357162,0.00018312946],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002716038,0.0014130701,0.0021802823,0.0010627817,0.0007850242,0.003093857,0.0020722,0.0038231232,0.0067911097],"category_scores_gemma":[0.014531576,0.001042311,0.000926083,0.0015914805,0.0017082887,0.0025445665,0.0021961264,0.002833917,0.0004266945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012082437,0.00007895132,0.0001833843,0.000120196746,0.000029345401,0.000043647073,0.000054767836,0.9262691,0.00034675509,0.061396394,0.0015485546,0.0098080505],"study_design_scores_gemma":[0.000009582331,0.0000112712505,0.000021626513,0.000004757153,0.000003974754,0.0000042223764,0.00000767214,0.98395777,0.000040759158,0.015755676,0.00017991468,0.0000027968604],"about_ca_topic_score_codex":0.012891107,"about_ca_topic_score_gemma":0.0055435128,"teacher_disagreement_score":0.012891107,"about_ca_system_score_codex":0.0028932833,"about_ca_system_score_gemma":0.0026003874,"threshold_uncertainty_score":0.025632143},"labels":[],"label_agreement":null},{"id":"W4391321941","doi":"10.1137/23m1552231","title":"The Power of Filling in Balanced Allocations","year":2024,"lang":"en","type":"article","venue":"SIAM Journal on Discrete Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"European Research Council; Engineering and Physical Sciences Research Council","keywords":"Mathematics; Power (physics); Combinatorics; Discrete mathematics; Mathematical economics; Mathematical optimization","score_opus":0.02026844332587755,"score_gpt":0.2940535587910843,"score_spread":0.27378511546520673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391321941","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.074469924,0.0020969128,0.8835961,0.0029176804,0.00022636715,0.0001241238,0.00026356144,0.00094432867,0.035361018],"genre_scores_gemma":[0.8111812,0.0016794066,0.16347587,0.0011517942,0.00048491746,0.00037190906,0.0002976609,0.00076230336,0.02059497],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9954537,0.0016058406,0.00017497766,0.00087991345,0.0011165745,0.00076895294],"domain_scores_gemma":[0.9843217,0.009535269,0.0013331377,0.0034257914,0.0007738564,0.00061026035],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042997287,0.0012426422,0.001480685,0.0009890905,0.0019097705,0.004389883,0.0024836631,0.0021112845,0.01235154],"category_scores_gemma":[0.026809448,0.00092168956,0.0012125872,0.001676501,0.00435369,0.011478532,0.005469822,0.0029837862,0.00204064],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060889585,0.00011406606,0.0011963139,0.00021985862,0.00004649822,0.00013880825,0.00035257603,0.06894203,0.0037734658,0.83990026,0.0047285897,0.079978704],"study_design_scores_gemma":[0.000060791182,0.00011446933,0.00034003,0.00005067619,0.000030844865,0.00019032237,0.0000848075,0.2280856,0.0042204894,0.75622904,0.010565723,0.000027165912],"about_ca_topic_score_codex":0.0013170507,"about_ca_topic_score_gemma":0.0007888524,"teacher_disagreement_score":0.01235154,"about_ca_system_score_codex":0.0022866891,"about_ca_system_score_gemma":0.0017423144,"threshold_uncertainty_score":0.041320026},"labels":[],"label_agreement":null},{"id":"W4392368986","doi":"10.1016/j.cie.2024.110008","title":"A robust optimization approach to multi-period competitive location problem for bank branches considering first-mover advantage","year":2024,"lang":"en","type":"article","venue":"Computers & Industrial Engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"First-mover advantage; Period (music); Competitive advantage; Computer science; Mathematical optimization; Business; Mathematics; Industrial organization; Marketing; Physics","score_opus":0.05734668844502962,"score_gpt":0.24529953030984614,"score_spread":0.18795284186481653,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392368986","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019133177,0.000981609,0.9700163,0.00070418674,0.000108620174,0.000116226,0.00024250877,0.00014761668,0.008549744],"genre_scores_gemma":[0.82375747,0.0013633325,0.15727703,0.00021828407,0.00021944875,0.00046884757,0.00041455048,0.00022551381,0.016055552],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989435,0.00047364944,0.000040009076,0.00023906339,0.00015314946,0.00015065321],"domain_scores_gemma":[0.9966114,0.002447468,0.00037964882,0.00008562517,0.00033912467,0.00013673758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003037367,0.0015966067,0.00392108,0.0015923588,0.0007510486,0.0033625688,0.0029782336,0.0043128897,0.006144605],"category_scores_gemma":[0.007333875,0.0017133445,0.0019678439,0.0015815594,0.0016086218,0.0023211485,0.001982364,0.0019727638,0.00058258587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000045397504,0.000025067104,0.0001480083,0.00009701643,0.00005555904,0.00008834617,0.000024123474,0.9825258,0.00035689908,0.012417587,0.00071559555,0.0035005896],"study_design_scores_gemma":[0.00000903805,0.000021572627,0.000054425745,0.0000063105927,0.000011601811,0.000008460926,0.00001047239,0.9967248,0.00006284429,0.002886563,0.00019646007,0.000007431846],"about_ca_topic_score_codex":0.015177982,"about_ca_topic_score_gemma":0.00811502,"teacher_disagreement_score":0.015177982,"about_ca_system_score_codex":0.0022071723,"about_ca_system_score_gemma":0.0022543566,"threshold_uncertainty_score":0.030179322},"labels":[],"label_agreement":null},{"id":"W4392923947","doi":"10.1002/msd2.12098","title":"An introductory review of swarm technology for spacecraft on‐orbit servicing","year":2024,"lang":"en","type":"article","venue":"International journal of mechanical system dynamics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Spacecraft; Computer science; Swarm behaviour; Systems engineering; Field (mathematics); Parallels; Satellite; Perspective (graphical); Space (punctuation); Artificial intelligence; Aerospace engineering; Engineering; Mechanical engineering","score_opus":0.011082894579561903,"score_gpt":0.3112667918387998,"score_spread":0.3001838972592379,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392923947","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007865285,0.9814105,0.0056693093,0.0005701491,0.0014407813,0.000026321986,0.00006428976,0.00005281981,0.009979302],"genre_scores_gemma":[0.006389898,0.9845807,0.0034056143,0.00043450636,0.0012389336,0.000033649278,0.00012285315,0.000021988495,0.0037718918],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996506,0.000059764705,0.000047989783,0.00008162987,0.00012567647,0.00003428936],"domain_scores_gemma":[0.99945515,0.00030412443,0.00005652141,0.000022991431,0.00013438777,0.000026873246],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005041915,0.0010077779,0.0008872316,0.0023557495,0.00042656984,0.001629792,0.0007558989,0.0013228913,0.005859719],"category_scores_gemma":[0.0010917,0.000462243,0.000871428,0.002601204,0.0005406896,0.0020343328,0.00075779576,0.0013639345,0.0029564027],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008983327,0.00016426134,0.00074610434,0.03090605,0.00012449501,0.0005622151,0.00038317023,0.005102628,0.008671527,0.044917457,0.056993745,0.8513385],"study_design_scores_gemma":[0.000004859202,0.00017866361,0.00081598473,0.0029562889,0.00006736906,0.0007894425,0.00012895551,0.0013118946,0.0015310925,0.005381782,0.9867958,0.000037778907],"about_ca_topic_score_codex":0.0012524066,"about_ca_topic_score_gemma":0.0009067597,"teacher_disagreement_score":0.005859719,"about_ca_system_score_codex":0.0005642933,"about_ca_system_score_gemma":0.0009888456,"threshold_uncertainty_score":0.019602776},"labels":[],"label_agreement":null},{"id":"W4393454360","doi":"10.5281/zenodo.8177271","title":"Continent-scale inventory routing solutions","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Scale (ratio); Routing (electronic design automation); Computer science; Environmental science; Geography; Cartography; Computer network","score_opus":0.07112794725969027,"score_gpt":0.26417643504289445,"score_spread":0.1930484877832042,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393454360","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0051085027,0.00068915315,0.00066433504,0.00073198986,0.00018963037,0.000080840546,0.985213,0.001969138,0.0053534633],"genre_scores_gemma":[0.0033852858,0.00013570151,0.0017753858,0.000115892915,0.00001486155,0.00006850743,0.9936492,0.0000891972,0.00076610106],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99853337,0.0002628219,0.00012939662,0.000461871,0.0004086668,0.00020389083],"domain_scores_gemma":[0.99846077,0.0003876493,0.00011327471,0.00041777224,0.00043318613,0.0001873596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011845478,0.0036519263,0.001759044,0.0027333028,0.0011824471,0.002500111,0.005651909,0.003931346,0.020094685],"category_scores_gemma":[0.004967984,0.00067845685,0.0022438231,0.0077174082,0.0006931505,0.0016115246,0.0015497797,0.0031776843,0.024090473],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014202042,0.00016916858,0.0010660653,0.0005988132,0.00006993821,0.000087878245,0.000028914435,0.0052158227,0.00018744337,0.0012314016,0.9854183,0.0057842084],"study_design_scores_gemma":[0.00095123856,0.00016040872,0.0070471424,0.00040854653,0.00007672903,0.0004772106,0.00033665285,0.029296981,0.0014247203,0.006538378,0.95318973,0.000092195485],"about_ca_topic_score_codex":0.030253615,"about_ca_topic_score_gemma":0.060887016,"teacher_disagreement_score":0.030253615,"about_ca_system_score_codex":0.0026678552,"about_ca_system_score_gemma":0.0023268147,"threshold_uncertainty_score":0.06722343},"labels":[],"label_agreement":null},{"id":"W4394601352","doi":"10.1007/s00446-024-00463-7","title":"On the power of bounded asynchrony: convergence by autonomous robots with limited visibility","year":2024,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of British Columbia","funders":"Gruppo Nazionale per il Calcolo Scientifico; Università di Pisa; Istituto Nazionale di Alta Matematica \"Francesco Severi\"","keywords":"Asynchrony (computer programming); Visibility; Bounded function; Convergence (economics); Power (physics); Computer science; Robot; Mathematics; Artificial intelligence; Telecommunications; Economics; Geography; Asynchronous communication; Mathematical analysis; Physics; Meteorology","score_opus":0.012521853781385211,"score_gpt":0.247799545274655,"score_spread":0.2352776914932698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394601352","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09730536,0.0005401739,0.8937159,0.0012545246,0.000063515996,0.00005806685,0.000058283003,0.00033974476,0.006664471],"genre_scores_gemma":[0.9470812,0.00034629504,0.049131602,0.00018040287,0.000076005446,0.00014419765,0.00006589031,0.00012649652,0.002847952],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99605477,0.0019101381,0.00019740792,0.00069106766,0.0007621638,0.0003843131],"domain_scores_gemma":[0.95786124,0.033772048,0.0028127485,0.002498151,0.001624792,0.0014309969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005102524,0.0008346702,0.0016596825,0.0009674596,0.0011526791,0.0020272734,0.0023480377,0.0015584856,0.002427571],"category_scores_gemma":[0.037367467,0.0007819505,0.0012339355,0.0006560073,0.0043170564,0.0043096063,0.005191385,0.002789019,0.00039896826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059244194,0.00006562598,0.0016042565,0.00016958067,0.00007564757,0.00030253403,0.00046013354,0.7649187,0.0033433216,0.210305,0.0013338998,0.016828826],"study_design_scores_gemma":[0.000061019247,0.00007654302,0.00014475117,0.000022801618,0.000013261248,0.000028298431,0.00004199539,0.9127785,0.0006829216,0.08558559,0.0005516449,0.00001262374],"about_ca_topic_score_codex":0.0023985582,"about_ca_topic_score_gemma":0.0015239002,"teacher_disagreement_score":0.005102524,"about_ca_system_score_codex":0.0014004356,"about_ca_system_score_gemma":0.0015088458,"threshold_uncertainty_score":0.026985109},"labels":[],"label_agreement":null},{"id":"W4395095509","doi":"10.1017/9781108682404","title":"Computational Principles of Mobile Robotics","year":2024,"lang":"en","type":"book","venue":"Cambridge University Press eBooks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; McGill University","funders":"","keywords":"Robotics; Artificial intelligence; Computer science; Mobile robot; Human–computer interaction; Robot","score_opus":0.030121199146705885,"score_gpt":0.2285061262564518,"score_spread":0.19838492710974592,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395095509","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026936256,0.07360023,0.3153979,0.011082068,0.0036029024,0.000118285905,0.00066765316,0.0008684502,0.59196883],"genre_scores_gemma":[0.17018493,0.0899021,0.24371406,0.005174157,0.0047721425,0.00089946983,0.0013538112,0.0006696045,0.48332974],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99960274,0.00007790178,0.000021614293,0.000078624485,0.0001809154,0.000038355443],"domain_scores_gemma":[0.9997969,0.0000898078,0.000016950578,0.000040789913,0.000039049235,0.000016449554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003509292,0.0010854101,0.0007820946,0.0008796649,0.0008232147,0.0032675643,0.0011490171,0.0012880653,0.013273988],"category_scores_gemma":[0.0009652794,0.00047228773,0.0007040124,0.0009205952,0.002803796,0.0029208756,0.0017245921,0.0025588984,0.006304054],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003106024,0.0000035864648,0.000041128966,0.00010120471,0.000008555552,0.000041092622,0.00010202016,0.0024765343,0.00024292778,0.94396085,0.028340975,0.024677947],"study_design_scores_gemma":[0.0000046430873,0.0000084817975,0.00011669087,0.00009889325,0.0000047704702,0.0001550264,0.000051811345,0.0046374216,0.00013015112,0.6381432,0.35663918,0.000009666325],"about_ca_topic_score_codex":0.0012405277,"about_ca_topic_score_gemma":0.0012762351,"teacher_disagreement_score":0.013273988,"about_ca_system_score_codex":0.0010218055,"about_ca_system_score_gemma":0.0010461131,"threshold_uncertainty_score":0.044405878},"labels":[],"label_agreement":null},{"id":"W4395095515","doi":"10.1017/9781108682404.019","title":"The Future of Mobile Robotics","year":2024,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University; McGill University","funders":"","keywords":"Robotics; Artificial intelligence; Computer science; Robot","score_opus":0.014953934929542969,"score_gpt":0.20570373519094645,"score_spread":0.19074980026140348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395095515","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0021257512,0.40527433,0.041302178,0.03316949,0.00700983,0.000047482154,0.00021696778,0.0007008954,0.5101531],"genre_scores_gemma":[0.041810952,0.28408682,0.043895423,0.006887144,0.0061879135,0.00015529672,0.00037027182,0.0003705753,0.6162356],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961936,0.00007456447,0.000013258756,0.000057036374,0.00019315041,0.00004263638],"domain_scores_gemma":[0.99971217,0.000113348666,0.000017983124,0.000037141093,0.00007096392,0.000048364953],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005075913,0.00070176466,0.0006344017,0.0008609573,0.0008495212,0.004762508,0.0009064107,0.0018647743,0.024816675],"category_scores_gemma":[0.0010026905,0.0003660596,0.0004214849,0.0009317905,0.0016578267,0.0047949054,0.0016278838,0.0022540092,0.012492929],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000017120894,0.0000134951215,0.00009977262,0.00045787683,0.000012272048,0.000069905924,0.0003148172,0.0014091143,0.00066147005,0.45556733,0.21170717,0.32966962],"study_design_scores_gemma":[0.0000016733836,0.0000101874875,0.00007819719,0.00023108843,0.000001972367,0.00010362508,0.00007654415,0.00048651706,0.000055208024,0.04798037,0.9509691,0.000005536068],"about_ca_topic_score_codex":0.0012710571,"about_ca_topic_score_gemma":0.0019627467,"teacher_disagreement_score":0.024816675,"about_ca_system_score_codex":0.0012530407,"about_ca_system_score_gemma":0.0014074302,"threshold_uncertainty_score":0.08302003},"labels":[],"label_agreement":null},{"id":"W4395470976","doi":"10.2139/ssrn.4804794","title":"Quality Versus Quantity in Dynamic Matching with Impatient Agents","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Quality (philosophy); Matching (statistics); Computer science; Statistics; Mathematics; Physics","score_opus":0.023568945361679316,"score_gpt":0.331891409282994,"score_spread":0.3083224639213147,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4395470976","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37836426,0.001720992,0.58245355,0.0073556937,0.0002213536,0.00033875354,0.00030636534,0.00041047818,0.02882863],"genre_scores_gemma":[0.9582702,0.0002582431,0.03138933,0.00022812377,0.00013518413,0.0000907805,0.000059658185,0.00006659414,0.009501909],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9946056,0.0033217587,0.00022149607,0.00065382296,0.00063685497,0.0005605773],"domain_scores_gemma":[0.94466144,0.04602666,0.003613524,0.0019964112,0.0011724281,0.002529517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012979706,0.00091380056,0.0029137323,0.0024068456,0.0013296809,0.0037725521,0.003256397,0.0045813927,0.010052174],"category_scores_gemma":[0.06602634,0.0010725515,0.0008829344,0.0026990345,0.004303869,0.009387981,0.003631229,0.0026643658,0.0006789769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0017321486,0.00053369504,0.006159928,0.0004254432,0.00023916966,0.00028512013,0.00076787756,0.3609248,0.0009861765,0.55675244,0.002900474,0.06829268],"study_design_scores_gemma":[0.00022069846,0.00040168708,0.0009249412,0.00003969298,0.00008103525,0.00010387474,0.00021059344,0.47982967,0.0003134914,0.51669836,0.0011369596,0.000039066235],"about_ca_topic_score_codex":0.0027551267,"about_ca_topic_score_gemma":0.001864279,"teacher_disagreement_score":0.012979706,"about_ca_system_score_codex":0.0028723136,"about_ca_system_score_gemma":0.0011322016,"threshold_uncertainty_score":0.06864405},"labels":[],"label_agreement":null},{"id":"W4399167020","doi":"10.2139/ssrn.4848615","title":"On the Computational Power of Energy-Constrained Mobile Robots","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Power (physics); Mobile robot; Computer science; Energy (signal processing); Robot; Artificial intelligence; Physics","score_opus":0.010207806511504665,"score_gpt":0.25424299666228856,"score_spread":0.2440351901507839,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399167020","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25853968,0.0068840436,0.6159171,0.009368599,0.00052120496,0.00007661673,0.00047670258,0.00029619638,0.10791979],"genre_scores_gemma":[0.9609011,0.0016909671,0.02750872,0.00030097205,0.00019019216,0.00007775025,0.00010492857,0.00013587963,0.009089661],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948823,0.00020000963,0.000020020667,0.00007672174,0.00013552057,0.00007954726],"domain_scores_gemma":[0.9934149,0.005784507,0.00018673623,0.00030906743,0.00016836957,0.00013636415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094339804,0.0006474819,0.00091979204,0.0005821538,0.00057253265,0.0015191537,0.0013739315,0.0010332312,0.009432052],"category_scores_gemma":[0.012786756,0.00038605934,0.0004424622,0.0011103479,0.0018422717,0.003113337,0.0023969123,0.0011281816,0.0006049613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003758379,0.000050891107,0.0008126457,0.00024483333,0.0000504944,0.00014026208,0.0001407795,0.69480884,0.002151749,0.25424042,0.0032021883,0.04378094],"study_design_scores_gemma":[0.000025617803,0.00003217768,0.00024483373,0.000026280168,0.000010991957,0.000030402463,0.00004328308,0.8429319,0.00047813234,0.15476404,0.0014050846,0.0000072771395],"about_ca_topic_score_codex":0.0014369676,"about_ca_topic_score_gemma":0.0010833477,"teacher_disagreement_score":0.009432052,"about_ca_system_score_codex":0.0004406611,"about_ca_system_score_gemma":0.00045062648,"threshold_uncertainty_score":0.031553328},"labels":[],"label_agreement":null},{"id":"W4399254466","doi":"10.1145/3652963.3655074","title":"Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms","year":2024,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Algorithm; Artificial intelligence","score_opus":0.01702083849957166,"score_gpt":0.24947373007213117,"score_spread":0.2324528915725595,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399254466","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023430461,0.00067971105,0.96701425,0.000733647,0.00011745143,0.00013292552,0.00012800083,0.0011354287,0.006628116],"genre_scores_gemma":[0.7154235,0.0004888887,0.27727488,0.0005527301,0.00019808009,0.0002994045,0.0003588798,0.0003472812,0.0050563174],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9979697,0.00070427277,0.000114949085,0.00047066237,0.00039890845,0.00034155903],"domain_scores_gemma":[0.9907736,0.0068314034,0.0007421718,0.0008369459,0.00053620036,0.00027962594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032968381,0.0019984439,0.0024283044,0.00089577603,0.0007123078,0.0030041046,0.0033934938,0.0029600004,0.005519708],"category_scores_gemma":[0.014574549,0.0008903201,0.0010708403,0.0015382577,0.0018574938,0.0040705493,0.0021139244,0.0039273314,0.00094414124],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001799927,0.00021421985,0.0005893325,0.00009980112,0.00004109026,0.00004551696,0.000041346553,0.9271552,0.00044352814,0.021983998,0.0020132586,0.047192737],"study_design_scores_gemma":[0.000015780228,0.00002235935,0.000035960547,0.0000053225494,0.0000044843105,0.000009922649,0.0000056675644,0.9908661,0.00015827849,0.0086676115,0.00020475822,0.0000038100918],"about_ca_topic_score_codex":0.00444485,"about_ca_topic_score_gemma":0.0033197654,"teacher_disagreement_score":0.005519708,"about_ca_system_score_codex":0.001698774,"about_ca_system_score_gemma":0.002681909,"threshold_uncertainty_score":0.01846528},"labels":[],"label_agreement":null},{"id":"W4399371091","doi":"10.7155/jgaa.v28i1.2929","title":"The Minimum Consistent Spanning Subset Problem on Trees","year":2024,"lang":"en","type":"article","venue":"Journal of Graph Algorithms and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Spanning tree; Combinatorics; Minimum spanning tree; Mathematics; Computer science","score_opus":0.018457793447468035,"score_gpt":0.2757615769877305,"score_spread":0.2573037835402625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399371091","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20521507,0.0016245953,0.7719636,0.002409119,0.00014468476,0.00036629222,0.0029348347,0.000987104,0.014354727],"genre_scores_gemma":[0.544148,0.0015681208,0.4426407,0.00038866643,0.0001648139,0.00045088158,0.00483182,0.00030041861,0.0055065514],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990742,0.0003160369,0.00006299525,0.00023036002,0.00018519412,0.00013116421],"domain_scores_gemma":[0.99835557,0.00097548764,0.00015257954,0.00021962405,0.0001629047,0.00013379003],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00078072114,0.0007004514,0.0012932867,0.0006925041,0.0008726299,0.0012961315,0.0012587557,0.001084591,0.002943641],"category_scores_gemma":[0.004502841,0.000535839,0.0008171791,0.0019130892,0.0006309556,0.0036447814,0.0012882664,0.001035355,0.00047883828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00059216324,0.00028263003,0.0023093254,0.0007048797,0.00018637418,0.0005292962,0.00054031605,0.5337527,0.010828677,0.2458779,0.03580451,0.16859117],"study_design_scores_gemma":[0.0001375696,0.000102916536,0.0007284792,0.000050355742,0.000051948857,0.00034092375,0.0002551821,0.6717678,0.003709871,0.31219846,0.010634349,0.00002225569],"about_ca_topic_score_codex":0.0022964627,"about_ca_topic_score_gemma":0.0024960353,"teacher_disagreement_score":0.002943641,"about_ca_system_score_codex":0.0008210658,"about_ca_system_score_gemma":0.0010057421,"threshold_uncertainty_score":0.009847462},"labels":[],"label_agreement":null},{"id":"W4399411102","doi":"10.1109/jas.2024.124356","title":"Semi-Decentralized Convex Optimization on $\\mathcal{SO}(3)$","year":2024,"lang":"en","type":"article","venue":"IEEE/CAA Journal of Automatica Sinica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"National Key Research and Development Program of China; Science and Technology Commission of Shanghai Municipality; National Natural Science Foundation of China","keywords":"Conic optimization; Regular polygon; Convex optimization; Mathematical optimization; Convex analysis; Mathematics; Computer science; Geometry","score_opus":0.020985921517236397,"score_gpt":0.30264534218709926,"score_spread":0.2816594206698629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399411102","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077817817,0.0016927188,0.9617365,0.01329091,0.0064027254,0.000046090427,0.00018049814,0.0002755745,0.00859332],"genre_scores_gemma":[0.5079919,0.0052496037,0.38600352,0.0050700065,0.024053786,0.0003437387,0.0005646351,0.0009669634,0.06975582],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99943537,0.00018943891,0.000032290216,0.00014744967,0.00015690278,0.000038538197],"domain_scores_gemma":[0.9992009,0.00040906807,0.0000611586,0.00005032775,0.00023267278,0.00004597241],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093958713,0.0007919076,0.0009107913,0.00027079164,0.00038617587,0.0010966319,0.0010152096,0.0011075342,0.0049473965],"category_scores_gemma":[0.0026624077,0.00027014283,0.0004949867,0.0005820165,0.00078425254,0.00094805344,0.00059437566,0.0017973235,0.0018131419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037248162,0.000090586946,0.00064485666,0.00051290984,0.00013846954,0.00083297596,0.00015293715,0.3523965,0.0047557415,0.194497,0.2156281,0.22997747],"study_design_scores_gemma":[0.00004443803,0.000052859512,0.00021532514,0.000027453509,0.000025345347,0.00018175997,0.000015277059,0.91543055,0.0015980956,0.034570187,0.0478149,0.000023799397],"about_ca_topic_score_codex":0.0014178711,"about_ca_topic_score_gemma":0.0021636134,"teacher_disagreement_score":0.0049473965,"about_ca_system_score_codex":0.0008049107,"about_ca_system_score_gemma":0.0007954994,"threshold_uncertainty_score":0.01655066},"labels":[],"label_agreement":null},{"id":"W4399412507","doi":"10.1016/j.dam.2024.05.024","title":"Graph exploration by a deterministic memoryless automaton with pebbles","year":2024,"lang":"en","type":"article","venue":"Discrete Applied Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Mathematics; Deterministic automaton; Two-way deterministic finite automaton; Automaton; Graph; Büchi automaton; Combinatorics; Theoretical computer science; Discrete mathematics; Nondeterministic finite automaton; Algorithm; Finite-state machine; Computer science; Automata theory","score_opus":0.01631122847895078,"score_gpt":0.2548495017715611,"score_spread":0.23853827329261035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399412507","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.48008704,0.00029717057,0.50543004,0.0006893735,0.00012707018,0.00007134287,0.00018231006,0.0013561728,0.011759471],"genre_scores_gemma":[0.9368954,0.0000812467,0.057495918,0.00007521748,0.000011873337,0.000072569426,0.000062345294,0.00008031194,0.005225096],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997234,0.000068543726,0.000016400978,0.00008638559,0.000052223702,0.000053048483],"domain_scores_gemma":[0.9986815,0.0008435773,0.000081621845,0.00016829338,0.00011139437,0.00011352364],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033014358,0.00037188677,0.00073297886,0.0005550642,0.00086051686,0.0009767979,0.0011898477,0.0012474622,0.0043542567],"category_scores_gemma":[0.0020957044,0.00040293843,0.00063398527,0.00046040703,0.0012064248,0.0013377845,0.0015003134,0.0008695829,0.00034256766],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005483016,0.00013591,0.0016280499,0.00017445699,0.00007393423,0.00045238767,0.0002454908,0.81143206,0.017320223,0.13045003,0.0011896826,0.03634951],"study_design_scores_gemma":[0.000034253186,0.0000631879,0.000119556506,0.000009906182,0.000012844921,0.000039239312,0.000020403364,0.9590362,0.001993901,0.038213387,0.00044410507,0.000013062313],"about_ca_topic_score_codex":0.0027413785,"about_ca_topic_score_gemma":0.0031080225,"teacher_disagreement_score":0.0043542567,"about_ca_system_score_codex":0.00061737245,"about_ca_system_score_gemma":0.0008006319,"threshold_uncertainty_score":0.014566481},"labels":[],"label_agreement":null},{"id":"W4399554409","doi":"10.48550/arxiv.2406.06460","title":"Towards Real-World Efficiency: Domain Randomization in Reinforcement Learning for Pre-Capture of Free-Floating Moving Targets by Autonomous Robots","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Space Agency","keywords":"Reinforcement learning; Robot; Computer science; Domain (mathematical analysis); Artificial intelligence; Randomization; Human–computer interaction; Mathematics; Randomized controlled trial","score_opus":0.02910153536264999,"score_gpt":0.21804519692698826,"score_spread":0.18894366156433828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399554409","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03185726,0.00016520818,0.96566576,0.00019307242,0.000022754646,0.00006484458,0.000014951835,0.00034650828,0.0016696133],"genre_scores_gemma":[0.87231153,0.00011066903,0.125508,0.00016561708,0.000024629533,0.0001863593,0.00003890183,0.00011272002,0.0015416363],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992248,0.00035465407,0.00003615405,0.000148208,0.00014967128,0.00008640807],"domain_scores_gemma":[0.9963535,0.0023820526,0.00041814017,0.0004020078,0.0002830135,0.00016136022],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029755628,0.00095024914,0.0008418951,0.00035432333,0.00035052045,0.00078312936,0.0012336351,0.0009494935,0.0014377438],"category_scores_gemma":[0.008867381,0.00044344203,0.00039063013,0.0002227608,0.0016707153,0.0014939415,0.0016331924,0.001702395,0.00027553356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000120238,0.00009296333,0.0008259716,0.00006836172,0.00003572951,0.000047784015,0.000068566085,0.95394903,0.0038407254,0.012882088,0.00044107836,0.027627438],"study_design_scores_gemma":[0.000015059639,0.00004656433,0.000088058376,0.0000069945118,0.0000035462792,0.000009050647,0.000006032188,0.99324095,0.00078567053,0.0055775354,0.00021622967,0.000004297895],"about_ca_topic_score_codex":0.0022226083,"about_ca_topic_score_gemma":0.0017905674,"teacher_disagreement_score":0.0029755628,"about_ca_system_score_codex":0.0011088802,"about_ca_system_score_gemma":0.001405494,"threshold_uncertainty_score":0.01573652},"labels":[],"label_agreement":null},{"id":"W4399718769","doi":"10.1109/cdc56724.2024.10886085","title":"A Parallel in Time Algorithm Based on ParaExp for Optimal Control Problems","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Mitacs; Institut national de recherche en informatique et en automatique (INRIA); Agence Nationale de la Recherche; City University of Hong Kong","keywords":"Computer science; Control (management); Algorithm design; Algorithm; Parallel computing; Artificial intelligence","score_opus":0.021526549232450946,"score_gpt":0.27568797591531463,"score_spread":0.2541614266828637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399718769","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018710684,0.000028635071,0.9966973,0.00006660216,0.000022627959,0.00002176834,0.000013797965,0.00019664246,0.0010815677],"genre_scores_gemma":[0.07172979,0.00011865983,0.9235054,0.00008889279,0.00004010011,0.00028243443,0.00011223328,0.00024595964,0.0038765527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997255,0.00006564454,0.000015635456,0.00004599519,0.000121402234,0.000025765334],"domain_scores_gemma":[0.99964845,0.00013659245,0.00003232946,0.000066180044,0.00009138135,0.000025076315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005690674,0.0006702394,0.00058781606,0.00034028137,0.00044528316,0.0005760907,0.0012116054,0.00069544284,0.005071664],"category_scores_gemma":[0.0011819443,0.0003350229,0.00039820644,0.0004243054,0.0006430936,0.0009779708,0.0012518568,0.001419833,0.0010794047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025365033,0.00014913038,0.00062256184,0.00019886509,0.000044236873,0.00021896252,0.00014416713,0.5792468,0.023472322,0.15382838,0.0053768004,0.23644425],"study_design_scores_gemma":[0.000032910735,0.00003889195,0.000043801898,0.000004443335,0.0000044215817,0.000037323418,0.000008471519,0.9762548,0.0029798062,0.016185319,0.0044037164,0.000006036058],"about_ca_topic_score_codex":0.0014839649,"about_ca_topic_score_gemma":0.0017692433,"teacher_disagreement_score":0.005071664,"about_ca_system_score_codex":0.00041615457,"about_ca_system_score_gemma":0.00089500233,"threshold_uncertainty_score":0.016966403},"labels":[],"label_agreement":null},{"id":"W4399888593","doi":"10.1007/978-3-031-63021-7_30","title":"Linear Search for an Escaping Target with Unknown Speed","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Artificial intelligence; Algorithm","score_opus":0.03745006556088688,"score_gpt":0.29406948813272427,"score_spread":0.2566194225718374,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399888593","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.055161647,0.0005726722,0.9110833,0.00048040663,0.00013200886,0.000064466,0.00010814737,0.001165383,0.03123193],"genre_scores_gemma":[0.5817238,0.0006344585,0.32865003,0.00040726262,0.00014235856,0.00034733245,0.00035712632,0.0006336875,0.087103985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997708,0.00004121616,0.000009089078,0.00004994176,0.00008414402,0.000044846685],"domain_scores_gemma":[0.9993524,0.00040725747,0.00004166579,0.000058433292,0.00010647427,0.00003369298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041254653,0.00074388715,0.000820812,0.00061578286,0.00060960645,0.0010048293,0.0011895626,0.0016500759,0.0072460026],"category_scores_gemma":[0.002785928,0.0005228362,0.0005692594,0.00095465215,0.0007874975,0.0013961046,0.0017316188,0.001490016,0.0021123358],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00033059475,0.0001090597,0.0004693018,0.0003050059,0.00007021173,0.00019970466,0.00017869755,0.7394849,0.012936834,0.10117762,0.008448105,0.13628994],"study_design_scores_gemma":[0.000015739077,0.000068601774,0.0000647525,0.000014929965,0.000007969318,0.0000462734,0.000018424955,0.9830567,0.0017544493,0.013260783,0.0016818437,0.000009490651],"about_ca_topic_score_codex":0.001788942,"about_ca_topic_score_gemma":0.001247615,"teacher_disagreement_score":0.0072460026,"about_ca_system_score_codex":0.00082018407,"about_ca_system_score_gemma":0.00053036795,"threshold_uncertainty_score":0.024240255},"labels":[],"label_agreement":null},{"id":"W4399889184","doi":"10.1007/978-3-031-63021-7_3","title":"Weighted Group Search on the Disk and Improved LP-Based Lower Bounds for Priority Evacuation","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Group (periodic table)","score_opus":0.021702256398009257,"score_gpt":0.27178199063311365,"score_spread":0.2500797342351044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399889184","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016147578,0.0019928638,0.9479976,0.0011349908,0.00037354298,0.00017344544,0.0003855082,0.0005502788,0.031244162],"genre_scores_gemma":[0.39689016,0.002895999,0.5526896,0.001178261,0.0009952411,0.0009921934,0.0012979883,0.0015602711,0.04150026],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971986,0.0011126138,0.0000928993,0.00033088226,0.00070402195,0.0005611496],"domain_scores_gemma":[0.98823404,0.008974147,0.00041989464,0.00093813293,0.000899023,0.0005348285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041861837,0.0029397951,0.0033311318,0.0024056537,0.0012516553,0.0038096136,0.0055654235,0.0028061033,0.018167462],"category_scores_gemma":[0.02047326,0.0009751818,0.0018755854,0.0040745996,0.0020710742,0.0074757496,0.0040616593,0.007071422,0.002466605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00060055254,0.00034214862,0.0003784424,0.00052790495,0.00009272388,0.00009394617,0.00021330755,0.6879427,0.0024711974,0.2144732,0.01968761,0.07317638],"study_design_scores_gemma":[0.000031057432,0.00007523117,0.00009527358,0.000050783994,0.00002270943,0.000022406617,0.000044299657,0.90045005,0.0005572786,0.096302606,0.0023351808,0.00001321117],"about_ca_topic_score_codex":0.0043388004,"about_ca_topic_score_gemma":0.0045694117,"teacher_disagreement_score":0.018167462,"about_ca_system_score_codex":0.0032993553,"about_ca_system_score_gemma":0.002490746,"threshold_uncertainty_score":0.060776234},"labels":[],"label_agreement":null},{"id":"W4399910498","doi":"10.1007/978-3-031-63021-7_36","title":"The Minimum Algorithm Size of k-Grouping by Silent Oblivious Robots","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science; Algorithm; Robot; Artificial intelligence","score_opus":0.012286328378413605,"score_gpt":0.2474559018471405,"score_spread":0.2351695734687269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399910498","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28547415,0.0022167345,0.65321875,0.004795138,0.00050059776,0.00042467398,0.0019869902,0.0037956855,0.047587294],"genre_scores_gemma":[0.725253,0.00083774154,0.25804192,0.0004696616,0.00025756695,0.0005561998,0.0010451976,0.0018424472,0.011696329],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974981,0.0008318466,0.00014452128,0.0005924335,0.0004723094,0.00046077714],"domain_scores_gemma":[0.9835535,0.011203315,0.00084452576,0.0029548586,0.0006868713,0.0007569218],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002662186,0.001231461,0.002587519,0.0007004547,0.0016605945,0.00300439,0.004891873,0.0026103572,0.011666315],"category_scores_gemma":[0.0190257,0.0011445197,0.0013062982,0.0015915995,0.0024113469,0.008882913,0.0032993334,0.0024314346,0.0017821142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006020157,0.00032548493,0.002320037,0.0017844428,0.00029820815,0.00024507605,0.0012878226,0.4797977,0.031078873,0.21815595,0.035683066,0.2230032],"study_design_scores_gemma":[0.00037311614,0.00039897312,0.0011686671,0.00012542267,0.00014844055,0.000262206,0.00029284044,0.63847214,0.009689931,0.344511,0.0044885334,0.00006875604],"about_ca_topic_score_codex":0.0012911642,"about_ca_topic_score_gemma":0.0018188243,"teacher_disagreement_score":0.011666315,"about_ca_system_score_codex":0.0025091148,"about_ca_system_score_gemma":0.003512191,"threshold_uncertainty_score":0.03902775},"labels":[],"label_agreement":null},{"id":"W4399999583","doi":"10.1016/j.comgeo.2024.102120","title":"Online class cover problem","year":2024,"lang":"en","type":"article","venue":"Computational Geometry","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Science and Engineering Research Board; Natural Sciences and Engineering Research Council of Canada; Human Resource Development Group; Council of Scientific and Industrial Research, India","keywords":"Cover (algebra); Class (philosophy); Computer science; Artificial intelligence; Engineering","score_opus":0.02232847278315972,"score_gpt":0.29096735695886516,"score_spread":0.2686388841757055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399999583","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11636597,0.0047561093,0.6077309,0.019269325,0.0017962005,0.0007888884,0.0137273185,0.0026129254,0.23295237],"genre_scores_gemma":[0.7745648,0.0028395709,0.11337735,0.0018554828,0.0025146555,0.0006450598,0.008719992,0.000880798,0.09460237],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99799156,0.00047088147,0.00005663647,0.00056268333,0.00054634357,0.0003719704],"domain_scores_gemma":[0.99545383,0.0028456138,0.00027157605,0.0007275858,0.0002780396,0.0004233287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012272582,0.0012305593,0.0028548585,0.0010178641,0.0015036173,0.004883343,0.0029152704,0.0043530804,0.040712643],"category_scores_gemma":[0.008100627,0.0006402831,0.0011559861,0.0023079463,0.0013691827,0.006819988,0.002414547,0.0047050216,0.0043613217],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001078521,0.000950916,0.0012970474,0.0006853167,0.0001561316,0.00034475845,0.00017674152,0.12136566,0.002088957,0.39784282,0.21584547,0.25816774],"study_design_scores_gemma":[0.00024689696,0.00014134069,0.00079094735,0.0001151169,0.00007604018,0.00042830873,0.00013003305,0.40598208,0.002364723,0.5395581,0.050132725,0.000033635155],"about_ca_topic_score_codex":0.0026441868,"about_ca_topic_score_gemma":0.0028596774,"teacher_disagreement_score":0.040712643,"about_ca_system_score_codex":0.0029564884,"about_ca_system_score_gemma":0.0023900385,"threshold_uncertainty_score":0.13619739},"labels":[],"label_agreement":null},{"id":"W4400084250","doi":"10.1007/978-3-031-57603-4_7","title":"Models for Network Flow and Network Design Problems with Piecewise Linear Costs","year":2024,"lang":"en","type":"book-chapter","venue":"International series in management science/operations research/International series in operations research & management science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Piecewise linear function; Flow network; Flow (mathematics); Computer science; Network planning and design; Mathematical optimization; Mathematics; Computer network; Mathematical analysis; Geometry","score_opus":0.08004079593170674,"score_gpt":0.3732164675606285,"score_spread":0.2931756716289218,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400084250","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007535708,0.0027930983,0.9521687,0.0013216581,0.00024629326,0.00007955142,0.00048097782,0.00022164945,0.035152346],"genre_scores_gemma":[0.49482986,0.012037256,0.3040936,0.000800157,0.00081253407,0.0010176441,0.0012675177,0.0005220379,0.18461953],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994814,0.00024871356,0.000017603554,0.00008006792,0.00010823429,0.00006410481],"domain_scores_gemma":[0.9986981,0.00097526127,0.00011703118,0.00005583184,0.0001037462,0.00005008482],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001187415,0.002088653,0.0013713137,0.0010808216,0.0005424478,0.002217588,0.00332251,0.0028182075,0.016974112],"category_scores_gemma":[0.0043470603,0.0013303687,0.0017637106,0.0024102586,0.0011990663,0.0032901932,0.0010042359,0.0033331506,0.0017015646],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000018327803,0.000031403728,0.000087608656,0.00011570102,0.00001971367,0.000031866766,0.00003131323,0.8155567,0.00022719732,0.16823809,0.0042770207,0.011365036],"study_design_scores_gemma":[0.000011948472,0.000018061039,0.0000682992,0.000031312327,0.000018374383,0.000027004708,0.00001676877,0.89079654,0.00007478793,0.104197554,0.0047285506,0.000010750175],"about_ca_topic_score_codex":0.005687436,"about_ca_topic_score_gemma":0.0065955305,"teacher_disagreement_score":0.016974112,"about_ca_system_score_codex":0.0026164788,"about_ca_system_score_gemma":0.001155898,"threshold_uncertainty_score":0.056784093},"labels":[],"label_agreement":null},{"id":"W4400102744","doi":"10.1007/978-3-031-57603-4_2","title":"Variable Neighborhood Search with Dynamic Exploration for the Set Union Knapsack Problem","year":2024,"lang":"en","type":"book-chapter","venue":"International series in management science/operations research/International series in operations research & management science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Knapsack problem; Set (abstract data type); Variable (mathematics); Mathematical optimization; Variable neighborhood search; Computer science; Mathematics; Metaheuristic","score_opus":0.06572608255923652,"score_gpt":0.39040621065674097,"score_spread":0.32468012809750446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400102744","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026371127,0.002012847,0.9517194,0.00031067416,0.00018225139,0.00007345583,0.000080377315,0.00018355368,0.019066352],"genre_scores_gemma":[0.44445452,0.0020341151,0.5246516,0.00019807025,0.00023516276,0.0004906738,0.0003385123,0.00030548254,0.027291922],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996101,0.00015705405,0.0000105692425,0.000051837716,0.00013124257,0.000039225335],"domain_scores_gemma":[0.9996394,0.00026134943,0.000024342273,0.000022543323,0.000032114494,0.00002038524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00065570726,0.0006519349,0.0010182002,0.0006704317,0.0004892393,0.00081953255,0.0013116066,0.001044889,0.00459047],"category_scores_gemma":[0.002026094,0.00040842255,0.0006420332,0.00140103,0.000621673,0.0014453015,0.0016064284,0.0016649069,0.0004969088],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012819676,0.0001145921,0.0002126318,0.00014237218,0.00003911835,0.000055595996,0.00007761428,0.80325544,0.0015333319,0.06589002,0.005780761,0.12277038],"study_design_scores_gemma":[0.00001533784,0.000051965733,0.00006155554,0.000015868422,0.0000065144736,0.000024839517,0.000012793472,0.9796622,0.00022607054,0.018013468,0.0019027346,0.0000066695193],"about_ca_topic_score_codex":0.0021170205,"about_ca_topic_score_gemma":0.0021931443,"teacher_disagreement_score":0.00459047,"about_ca_system_score_codex":0.0005018222,"about_ca_system_score_gemma":0.0005724421,"threshold_uncertainty_score":0.0153567195},"labels":[],"label_agreement":null},{"id":"W4400909999","doi":"10.1109/icde60146.2024.00156","title":"PrestigeBFT: Revolutionizing View Changes in BFT Consensus Algorithms with Reputation Mechanisms","year":2024,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Reputation; Algorithm; Political science","score_opus":0.026729554656408628,"score_gpt":0.2711238063916415,"score_spread":0.24439425173523288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400909999","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026650028,0.00022666914,0.96781564,0.00047615834,0.00009829213,0.00010105235,0.000061271596,0.0015369772,0.0030338843],"genre_scores_gemma":[0.62351155,0.0002025318,0.37162212,0.00028093613,0.0001551734,0.00022575856,0.00026364767,0.0002801645,0.0034580838],"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","domain_scores_codex":[0.99825543,0.00052923,0.00009800102,0.00032616328,0.00061634916,0.00017482172],"domain_scores_gemma":[0.99491936,0.001784595,0.00060610526,0.0014766592,0.00087188807,0.00034148432],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029345236,0.0007725467,0.00089233747,0.0008523822,0.0010972155,0.0012844948,0.002589804,0.0015770617,0.002506418],"category_scores_gemma":[0.011663961,0.00042771627,0.00059076335,0.00084838795,0.0010979427,0.0036424722,0.002714712,0.0018377939,0.00085205544],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006661728,0.00026513755,0.0029176162,0.0002234709,0.00015022841,0.00031479466,0.0007035946,0.46112448,0.03308611,0.064778134,0.011675174,0.42409503],"study_design_scores_gemma":[0.00011052025,0.00021645645,0.00025425633,0.000016181833,0.00002615959,0.00016506069,0.000058177513,0.961385,0.0077154837,0.02488081,0.0051404014,0.000031534455],"about_ca_topic_score_codex":0.0024639012,"about_ca_topic_score_gemma":0.0031853833,"teacher_disagreement_score":0.0029345236,"about_ca_system_score_codex":0.00092672335,"about_ca_system_score_gemma":0.0013139353,"threshold_uncertainty_score":0.01551944},"labels":[],"label_agreement":null},{"id":"W4401024529","doi":"10.24963/ijcai.2024/781","title":"LEKA: LLM-Enhanced Knowledge Augmentation","year":2024,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Submodular set function; Computer science; Maximization; Mathematical optimization; Artificial intelligence; Algorithm; Mathematics","score_opus":0.022152509384422876,"score_gpt":0.3182585027294919,"score_spread":0.29610599334506904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401024529","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015973704,0.00030014003,0.9692295,0.0003434406,0.000060588936,0.00013453748,0.0004298397,0.011001892,0.0025263084],"genre_scores_gemma":[0.3372899,0.00024964014,0.6544136,0.0006617604,0.000057489007,0.0005716729,0.0020825944,0.00049166085,0.004181625],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988152,0.0003408295,0.000083567844,0.0003341818,0.00033687605,0.00008944256],"domain_scores_gemma":[0.9970319,0.0015788293,0.00018886193,0.00068401394,0.00043820578,0.000078132114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017346515,0.0011591447,0.001026392,0.0018327397,0.0005430531,0.00152063,0.0030276405,0.0014639532,0.005757615],"category_scores_gemma":[0.008715618,0.000572255,0.0011606645,0.0014788151,0.0010629664,0.0036597562,0.003645069,0.0021444436,0.0023207732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039453266,0.00047747404,0.001863779,0.00043083722,0.00012686937,0.00021678736,0.00027348148,0.18278149,0.018074548,0.008782263,0.011883585,0.7746944],"study_design_scores_gemma":[0.000039517527,0.00009881498,0.0004026661,0.000030097372,0.00002941876,0.00008808613,0.00005752876,0.9667832,0.011682016,0.01605086,0.004711821,0.000025887546],"about_ca_topic_score_codex":0.0024965282,"about_ca_topic_score_gemma":0.0048683756,"teacher_disagreement_score":0.005757615,"about_ca_system_score_codex":0.00084409124,"about_ca_system_score_gemma":0.0014342088,"threshold_uncertainty_score":0.019261062},"labels":[],"label_agreement":null},{"id":"W4401074641","doi":"10.1016/j.jcss.2024.103574","title":"Minimum separator reconfiguration","year":2024,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Japan Society for the Promotion of Science; Banff International Research Station for Mathematical Innovation and Discovery; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Control reconfiguration; Separator (oil production); Computer science; Mathematical optimization; Mathematics; Embedded system; Physics","score_opus":0.024473958951421855,"score_gpt":0.2856749715242304,"score_spread":0.26120101257280853,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401074641","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.24008608,0.0012349908,0.631239,0.0016543902,0.00050284364,0.0001755126,0.0008995471,0.003627516,0.12058014],"genre_scores_gemma":[0.9051902,0.00021209425,0.07481048,0.00015580228,0.00007141036,0.000086704946,0.0005592247,0.00034324554,0.018570669],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996983,0.00006751303,0.000014687443,0.00009409475,0.000057056986,0.000068357986],"domain_scores_gemma":[0.9995912,0.0001377444,0.000055652807,0.00010329593,0.000063974374,0.00004810969],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002626011,0.00095375476,0.00094290165,0.00087778777,0.00082851044,0.0012220412,0.0008283609,0.0011661558,0.014899775],"category_scores_gemma":[0.0012932294,0.0004020157,0.0005796156,0.0008219845,0.00040247352,0.0015539991,0.0010249849,0.00091528054,0.0020623815],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019239456,0.00031814646,0.0012181149,0.0006970316,0.00019219916,0.000810293,0.00017914984,0.45787087,0.075266786,0.054560214,0.023368202,0.3835951],"study_design_scores_gemma":[0.00015681713,0.0005118557,0.0015211694,0.00008256537,0.00009976919,0.0008563905,0.000131963,0.88427216,0.038383856,0.055149686,0.018782077,0.000051685583],"about_ca_topic_score_codex":0.00035543914,"about_ca_topic_score_gemma":0.000776461,"teacher_disagreement_score":0.014899775,"about_ca_system_score_codex":0.00057721057,"about_ca_system_score_gemma":0.00046419998,"threshold_uncertainty_score":0.049844682},"labels":[],"label_agreement":null},{"id":"W4401269927","doi":"10.1016/j.tcs.2024.114761","title":"Overcoming probabilistic faults in disoriented linear search","year":2024,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; Fields Institute for Research in Mathematical Sciences; Toronto Metropolitan University","keywords":"Probabilistic logic; Competitive analysis; Randomized algorithm; Deterministic algorithm; Mathematics; Algorithm; Path (computing); Constant (computer programming); Computer science; Leverage (statistics); Mathematical optimization; Upper and lower bounds; Artificial intelligence","score_opus":0.01692713087326652,"score_gpt":0.29772330390821694,"score_spread":0.2807961730349504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401269927","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19795132,0.0014004975,0.7879021,0.0016928243,0.000263225,0.0000746209,0.00008665162,0.0023119473,0.00831677],"genre_scores_gemma":[0.90853506,0.00025691555,0.087717704,0.00027728404,0.00008216473,0.000058317157,0.00007318637,0.00022511666,0.0027742938],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99828607,0.00064837746,0.00011040621,0.0002255257,0.0005321427,0.00019734756],"domain_scores_gemma":[0.98532397,0.010134119,0.0010331685,0.0018759066,0.0012398176,0.0003930509],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003036739,0.0005993802,0.001124984,0.0008022231,0.0006677388,0.0015405377,0.0020470445,0.0015568332,0.002731528],"category_scores_gemma":[0.026220087,0.00064203417,0.0004112102,0.0011505849,0.0019648755,0.003905209,0.0022920235,0.0020573784,0.00039188133],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000974144,0.00012734205,0.003676384,0.0002702694,0.00006441471,0.00025522872,0.00030142046,0.7384797,0.003002783,0.100004725,0.003341812,0.1495018],"study_design_scores_gemma":[0.000037846803,0.00010000778,0.00025471117,0.00001631611,0.000018526365,0.0000760761,0.00004299165,0.914182,0.0010222876,0.08337068,0.0008672763,0.000011261773],"about_ca_topic_score_codex":0.0023709023,"about_ca_topic_score_gemma":0.002698539,"teacher_disagreement_score":0.003036739,"about_ca_system_score_codex":0.0012635575,"about_ca_system_score_gemma":0.0016022079,"threshold_uncertainty_score":0.016059995},"labels":[],"label_agreement":null},{"id":"W4401974097","doi":"10.37256/cm.5320243304","title":"An Efficient Algorithm for Solving the 2-MAXSAT Problem","year":2024,"lang":"en","type":"article","venue":"Contemporary Mathematics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Maximum satisfiability problem; Mathematics; Algorithm; Mathematical optimization; Theoretical computer science; Computer science; Boolean function","score_opus":0.04618635100849945,"score_gpt":0.3021554689343263,"score_spread":0.2559691179258269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401974097","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008467036,0.0005557636,0.96572554,0.00088471326,0.00022102427,0.00037941028,0.000573915,0.0059411116,0.017251475],"genre_scores_gemma":[0.07700271,0.00037597632,0.9122088,0.00034120068,0.00009804235,0.00039919818,0.0016133889,0.00045157154,0.0075090923],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987809,0.00022337271,0.00008033438,0.00035916848,0.00033233402,0.00022388798],"domain_scores_gemma":[0.99935,0.00026350058,0.00005514777,0.0001791463,0.00011645849,0.000035689165],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007386626,0.0017379393,0.0010340898,0.0012208825,0.0012820703,0.0019346561,0.0021860255,0.0019299623,0.016689492],"category_scores_gemma":[0.002540983,0.00091979204,0.0013375909,0.0021909256,0.00061008567,0.0035891694,0.0020275183,0.0016024755,0.005686691],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005414986,0.00060937076,0.0008719747,0.00063334714,0.00012318,0.00030364326,0.00025324585,0.07880265,0.017127978,0.093045995,0.069264,0.73842317],"study_design_scores_gemma":[0.0006035383,0.00026060152,0.0007128027,0.000108898035,0.00009080644,0.00071772357,0.00017717107,0.7320111,0.014111173,0.16762552,0.083499536,0.0000812531],"about_ca_topic_score_codex":0.0018364422,"about_ca_topic_score_gemma":0.0036192257,"teacher_disagreement_score":0.016689492,"about_ca_system_score_codex":0.0012514091,"about_ca_system_score_gemma":0.0028146773,"threshold_uncertainty_score":0.05583185},"labels":[],"label_agreement":null},{"id":"W4402290566","doi":"10.1145/3695411.3695415","title":"Risk-Sensitive Online Algorithms","year":2024,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Algorithm","score_opus":0.08780638005564445,"score_gpt":0.37878093031266896,"score_spread":0.2909745502570245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402290566","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0142868105,0.0007377397,0.9796622,0.00086557126,0.00013633518,0.00022692309,0.0000775241,0.00030607096,0.003700848],"genre_scores_gemma":[0.5956903,0.001464431,0.39194754,0.0014420433,0.00067875884,0.0008434965,0.00025466763,0.00034121203,0.007337576],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9677958,0.020882243,0.00088774477,0.0036031378,0.0052353274,0.0015958283],"domain_scores_gemma":[0.89403844,0.08032481,0.0068109874,0.009676881,0.006176431,0.0029725279],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.024399683,0.0023729908,0.0034922394,0.0015710419,0.0011442368,0.0049564987,0.0048568505,0.0040139384,0.00555625],"category_scores_gemma":[0.10685936,0.0018014001,0.0015957244,0.0019393242,0.0033823121,0.007677985,0.0039945827,0.004837233,0.0015873224],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010556555,0.0008131046,0.0022331353,0.0006492711,0.00027714204,0.00016450709,0.0002519623,0.4545056,0.0031940145,0.43180043,0.008197812,0.09685727],"study_design_scores_gemma":[0.0001527807,0.00057424273,0.00027378168,0.00004814019,0.00006951797,0.00015495079,0.000031225114,0.7894605,0.0015257833,0.20474604,0.0029271566,0.000035897687],"about_ca_topic_score_codex":0.00060079404,"about_ca_topic_score_gemma":0.00043740467,"teacher_disagreement_score":0.024399683,"about_ca_system_score_codex":0.0025904125,"about_ca_system_score_gemma":0.0034307893,"threshold_uncertainty_score":0.1290394},"labels":[],"label_agreement":null},{"id":"W4402290638","doi":"10.1145/3695411.3695414","title":"Online Conversion with Group Fairness Constraints","year":2024,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Group (periodic table); Computer science; Chemistry","score_opus":0.07235907221506278,"score_gpt":0.3433352758791231,"score_spread":0.27097620366406033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402290638","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053757396,0.00036019355,0.93045354,0.0005464022,0.0001532438,0.00030677285,0.00011477956,0.0005140694,0.013793555],"genre_scores_gemma":[0.83366674,0.0002965987,0.15360281,0.00032618237,0.000203476,0.00018444285,0.00014845764,0.00016688262,0.011404455],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99602795,0.0013472188,0.00014948126,0.0008388351,0.00090007426,0.00073654304],"domain_scores_gemma":[0.9884525,0.007930071,0.0006877676,0.0017206253,0.0006575871,0.0005513919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004157614,0.00092442834,0.0020341326,0.00061870366,0.0013091635,0.0038910413,0.0036991003,0.002029989,0.009052086],"category_scores_gemma":[0.014619152,0.0005309165,0.0007447592,0.0017144401,0.0018373225,0.006597037,0.0025144361,0.0029617276,0.0009660343],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009238972,0.0011790809,0.0018503999,0.0003330186,0.00008848067,0.0006786304,0.0003139314,0.5442115,0.005430962,0.22801858,0.007590775,0.20938075],"study_design_scores_gemma":[0.00008535214,0.00015825409,0.00026873295,0.000020755253,0.000021588861,0.00032607428,0.00008882162,0.8978571,0.0031829744,0.09409391,0.003872865,0.00002357942],"about_ca_topic_score_codex":0.0017598624,"about_ca_topic_score_gemma":0.0012290499,"teacher_disagreement_score":0.009052086,"about_ca_system_score_codex":0.0017211091,"about_ca_system_score_gemma":0.0023207092,"threshold_uncertainty_score":0.030282259},"labels":[],"label_agreement":null},{"id":"W4402329836","doi":"10.2139/ssrn.4949863","title":"The Power of Knowledge in Linear Search for an Escaping Target","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Power (physics); Computer science; Political science; Physics","score_opus":0.026935230575928393,"score_gpt":0.32747909175312845,"score_spread":0.30054386117720006,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402329836","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10862901,0.0042687426,0.7995703,0.0059417286,0.00026136287,0.000040088253,0.00018469336,0.000298354,0.080805615],"genre_scores_gemma":[0.950293,0.0013976068,0.040197775,0.00033784984,0.00032130184,0.000052098076,0.000069257294,0.00009401194,0.007237183],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99813557,0.0008598686,0.00007110192,0.000278811,0.00047700052,0.00017755106],"domain_scores_gemma":[0.9741434,0.023030547,0.0006413955,0.0013419985,0.0005144021,0.00032821274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026236023,0.00054567255,0.00128983,0.0012734885,0.0012439815,0.004020364,0.0016119457,0.0024120468,0.0060980245],"category_scores_gemma":[0.028298322,0.0006348835,0.0009921319,0.0018639119,0.0060730134,0.010941827,0.0033809815,0.002949926,0.00057756633],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00029269233,0.00006242712,0.00073923275,0.0002378265,0.00006555722,0.00014738143,0.00030346875,0.17403412,0.0008410576,0.7817955,0.0018519493,0.039628737],"study_design_scores_gemma":[0.00002120901,0.000029204444,0.000095907846,0.00002312175,0.000014992141,0.0000333302,0.000030814608,0.24841103,0.0003477654,0.75017506,0.0008045455,0.000012985534],"about_ca_topic_score_codex":0.0016666712,"about_ca_topic_score_gemma":0.0010994356,"teacher_disagreement_score":0.0060980245,"about_ca_system_score_codex":0.0011771119,"about_ca_system_score_gemma":0.00086005044,"threshold_uncertainty_score":0.020399928},"labels":[],"label_agreement":null},{"id":"W4402426965","doi":"10.48550/arxiv.2408.06553","title":"Centralization vs. decentralization in multi-robot sweep coverage with ground robots and UAVs","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Office of Naval Research Global; Office of Naval Research; China Scholarship Council; European Commission; Government of Ontario; University of Ottawa","keywords":"Decentralization; Robot; Business; Computer science; Artificial intelligence; Economics; Market economy","score_opus":0.07412246750598184,"score_gpt":0.2076468936296617,"score_spread":0.13352442612367987,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402426965","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.53852856,0.00079541956,0.45698026,0.00031485793,0.000020803425,0.00008962802,0.00005148966,0.0003736332,0.00284529],"genre_scores_gemma":[0.98199505,0.00009716137,0.01738223,0.000019276878,0.000012717953,0.00003414564,0.000026747755,0.000017716284,0.00041490264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99916697,0.00037185874,0.000028094451,0.00014610984,0.00015130077,0.00013568842],"domain_scores_gemma":[0.9962529,0.0022218986,0.00067163,0.00037514014,0.00025246898,0.00022591128],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019683319,0.0004103962,0.000831691,0.00051953684,0.00040819755,0.0005405505,0.0005723856,0.00057396747,0.00044537932],"category_scores_gemma":[0.0045123966,0.0002733636,0.00034181098,0.00051636284,0.0010324882,0.0013186899,0.0011060132,0.00056390534,0.000076162956],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019730818,0.00006288662,0.0015863376,0.000044903794,0.000024286,0.000034378274,0.000058579048,0.97647923,0.0024551968,0.0033877646,0.00017465721,0.0154944025],"study_design_scores_gemma":[0.000045515237,0.00023812735,0.0017516296,0.000006646252,0.000013439814,0.000034279237,0.000072696945,0.9910188,0.0022630806,0.0042779963,0.00026913485,0.000008676907],"about_ca_topic_score_codex":0.0023058315,"about_ca_topic_score_gemma":0.0018095132,"teacher_disagreement_score":0.0023058315,"about_ca_system_score_codex":0.00057816284,"about_ca_system_score_gemma":0.0006101717,"threshold_uncertainty_score":0.010409713},"labels":[],"label_agreement":null},{"id":"W4402625841","doi":"10.1007/978-981-97-7798-3_11","title":"A Distributed Approximation Algorithm for the Total Dominating Set Problem","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Approximation algorithm; Dominating set; Set (abstract data type); Algorithm; Distributed algorithm; Theoretical computer science; Distributed computing; Programming language","score_opus":0.01999182747992082,"score_gpt":0.2666103806226894,"score_spread":0.24661855314276857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402625841","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009019837,0.00053804356,0.9830232,0.00039546148,0.00026783385,0.000123731,0.00015245148,0.0007275217,0.0057519716],"genre_scores_gemma":[0.20565626,0.00069009815,0.7804963,0.0003514196,0.00026883755,0.00049424206,0.00066721183,0.00031953436,0.011056138],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99871147,0.00034379849,0.00005659798,0.00028720824,0.00042826767,0.00017269616],"domain_scores_gemma":[0.9984787,0.0008343416,0.000066261404,0.00029677362,0.00021305485,0.00011085919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014948886,0.001366667,0.0021369755,0.00096911745,0.0010065085,0.0017735554,0.0031701983,0.0014234708,0.005333341],"category_scores_gemma":[0.0040676645,0.00057001435,0.0011009146,0.0023866133,0.00074908085,0.0023549665,0.0025174133,0.0021959823,0.0011841237],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007149336,0.0004042373,0.00037157463,0.00033077196,0.00013542605,0.00009086683,0.00016762532,0.5180855,0.0051590838,0.065970555,0.022045214,0.38652423],"study_design_scores_gemma":[0.00016567974,0.00011874816,0.000110507,0.00001710183,0.00003827187,0.00008896422,0.00003617838,0.94913155,0.001083617,0.04417308,0.005023556,0.000012794895],"about_ca_topic_score_codex":0.002116674,"about_ca_topic_score_gemma":0.0031524263,"teacher_disagreement_score":0.005333341,"about_ca_system_score_codex":0.001780038,"about_ca_system_score_gemma":0.0020917552,"threshold_uncertainty_score":0.017841756},"labels":[],"label_agreement":null},{"id":"W4403420399","doi":"10.1109/ojcoms.2024.3480987","title":"Dynamic Pricing in Multi-Tenant MANO With Resource Sharing: A Stackelberg Game Approach","year":2024,"lang":"en","type":"article","venue":"IEEE Open Journal of the Communications Society","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Stackelberg competition; Computer science; Sequential game; Microeconomics; Resource (disambiguation); Game theory; Economics; Computer network","score_opus":0.08424936554807923,"score_gpt":0.344879353859206,"score_spread":0.26062998831112677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403420399","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.039613847,0.00044287535,0.9408765,0.0009434722,0.0001490294,0.00023658163,0.00010510838,0.00015603215,0.01747661],"genre_scores_gemma":[0.8993868,0.0006224278,0.08804211,0.0003377185,0.00012251071,0.00037109663,0.000068263485,0.00006621575,0.010982833],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99735427,0.0012813285,0.000089808826,0.00041477056,0.00036231746,0.0004975602],"domain_scores_gemma":[0.9975739,0.0015021849,0.00024831892,0.00009366102,0.00025758857,0.00032437342],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003592795,0.0018204058,0.0019489893,0.00089906895,0.0014154379,0.0033400343,0.003223477,0.0029349364,0.0056132665],"category_scores_gemma":[0.004913461,0.001025669,0.001474256,0.0008108898,0.00264078,0.0039484813,0.002322883,0.0022981807,0.000582905],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019938262,0.00016004029,0.00066359853,0.00012158584,0.00013790547,0.00066018983,0.00027856303,0.70165724,0.00214525,0.27861765,0.0019410981,0.013417538],"study_design_scores_gemma":[0.000033119046,0.000058757472,0.00008278739,0.000010903174,0.000020055615,0.000057631885,0.000058999936,0.93746924,0.00019279712,0.060921963,0.0010720384,0.000021675365],"about_ca_topic_score_codex":0.004726079,"about_ca_topic_score_gemma":0.003930849,"teacher_disagreement_score":0.0056132665,"about_ca_system_score_codex":0.0026388804,"about_ca_system_score_gemma":0.0027334862,"threshold_uncertainty_score":0.019146502},"labels":[],"label_agreement":null},{"id":"W4403557064","doi":"10.1007/978-3-031-74498-3_2","title":"Invited Paper: A Survey of the Impact of Knowledge on the Competitive Ratio in Linear Search","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Competitive analysis; Operations research; Information retrieval; Mathematics","score_opus":0.04304661691225021,"score_gpt":0.3129956036367817,"score_spread":0.2699489867245315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403557064","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016650261,0.72740984,0.037442256,0.020015052,0.002767046,0.00003750789,0.00085261464,0.00024285707,0.19458264],"genre_scores_gemma":[0.32645446,0.5863375,0.02720445,0.006971401,0.017911065,0.00009045888,0.0016136655,0.0005771758,0.032839846],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973328,0.00092029024,0.00011384335,0.00041467758,0.0010085396,0.00020977974],"domain_scores_gemma":[0.9645653,0.031332538,0.0006677621,0.00077532674,0.0021111593,0.0005479815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037967544,0.00087344804,0.00165392,0.0032539556,0.00065036764,0.005469534,0.0018906757,0.001989081,0.020348508],"category_scores_gemma":[0.026171291,0.00048393235,0.0005979417,0.011225915,0.0020936222,0.008930557,0.001273474,0.002380548,0.00512626],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035053672,0.00019686416,0.0021666752,0.0028816017,0.00014662191,0.0001005925,0.00011217999,0.012731844,0.00045890125,0.26958367,0.08964027,0.62163025],"study_design_scores_gemma":[0.00011584331,0.00025758307,0.004185061,0.0014257446,0.00019586414,0.00066450017,0.00021870194,0.039359853,0.0019378886,0.6776442,0.2738776,0.00011710794],"about_ca_topic_score_codex":0.0024249118,"about_ca_topic_score_gemma":0.0017059662,"teacher_disagreement_score":0.020348508,"about_ca_system_score_codex":0.0026066564,"about_ca_system_score_gemma":0.0013052106,"threshold_uncertainty_score":0.06807256},"labels":[],"label_agreement":null},{"id":"W4404028777","doi":"10.1016/j.jii.2024.100727","title":"Proximal policy optimization with population-based variable neighborhood search algorithm for coordinating photo-etching and acid-etching processes in sustainable storage chip manufacturing","year":2024,"lang":"en","type":"article","venue":"Journal of Industrial Information Integration","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"","keywords":"Etching (microfabrication); Variable (mathematics); Chip; Materials science; Population; Nanotechnology; Computer science; Algorithm; Mathematics; Telecommunications; Layer (electronics); Medicine","score_opus":0.017794392334267727,"score_gpt":0.2688782613785026,"score_spread":0.2510838690442349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404028777","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.036087114,0.0006785532,0.958378,0.00025797402,0.00009849394,0.0001017871,0.000043101918,0.00019179196,0.004163214],"genre_scores_gemma":[0.82482004,0.00042715116,0.16808602,0.00018643169,0.000054560955,0.000515052,0.00011986623,0.00007327122,0.0057175686],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993975,0.00021917204,0.000024765308,0.00012840913,0.00012742188,0.000102606486],"domain_scores_gemma":[0.9985983,0.000972178,0.000103344995,0.00003032753,0.00022921136,0.000066696615],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018766321,0.0009825559,0.0024304283,0.00095982186,0.0008577008,0.0012007556,0.0018475376,0.002303151,0.0027247404],"category_scores_gemma":[0.0030002126,0.0008622886,0.000954699,0.0008711573,0.001127965,0.0010854106,0.0016591651,0.0013321438,0.00026269627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046314846,0.00003451573,0.00020771092,0.000033977798,0.000023406063,0.000027827347,0.000027439697,0.98951846,0.00022350939,0.0025875324,0.00031181105,0.0069575375],"study_design_scores_gemma":[0.000011426406,0.000022933868,0.0000342693,0.0000027263134,0.000005037902,0.0000036475774,0.000006295156,0.9992687,0.000059247628,0.0004921725,0.000091001006,0.0000025475997],"about_ca_topic_score_codex":0.012160165,"about_ca_topic_score_gemma":0.007451176,"teacher_disagreement_score":0.012160165,"about_ca_system_score_codex":0.0011771529,"about_ca_system_score_gemma":0.002623419,"threshold_uncertainty_score":0.024178743},"labels":[],"label_agreement":null},{"id":"W4404314575","doi":"10.48550/arxiv.2410.20900","title":"Parameterized Approximation for Capacitated $d$-Hitting Set with Hard Capacities","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"European Commission; Department of Science and Technology, Ministry of Science and Technology, India; York University; New York University Shanghai","keywords":"Parameterized complexity; Set (abstract data type); Mathematical optimization; Mathematics; Computer science; Combinatorics","score_opus":0.13864227380894031,"score_gpt":0.20796505521441244,"score_spread":0.06932278140547213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404314575","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1059117,0.0046529877,0.81358624,0.0050658886,0.0005762472,0.00095485256,0.010809388,0.00923364,0.04920907],"genre_scores_gemma":[0.60815585,0.0021533673,0.34760705,0.0022065784,0.00047951122,0.0016340776,0.013802121,0.002327668,0.021633854],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99685055,0.00063089037,0.00014776296,0.0009423703,0.00061260647,0.00081584055],"domain_scores_gemma":[0.99125576,0.005477116,0.0004640709,0.0015619637,0.0005199983,0.0007210169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00197381,0.0046066,0.004392186,0.0019256466,0.0015875546,0.004516822,0.0085991295,0.0038557719,0.024821475],"category_scores_gemma":[0.0144652175,0.0015997179,0.0030772286,0.006743843,0.0017033791,0.0075295717,0.0046144975,0.0062530586,0.0042755688],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011241,0.00045879022,0.0013236749,0.0010138897,0.00022789306,0.00028390053,0.00024226977,0.81528693,0.0017446892,0.063804016,0.04276743,0.07172233],"study_design_scores_gemma":[0.0001149112,0.000089019486,0.0002036,0.0000662274,0.00005197197,0.00014757649,0.00008035609,0.90669703,0.0008090551,0.08788228,0.0038294953,0.000028416081],"about_ca_topic_score_codex":0.011415923,"about_ca_topic_score_gemma":0.013510702,"teacher_disagreement_score":0.024821475,"about_ca_system_score_codex":0.007039069,"about_ca_system_score_gemma":0.004203645,"threshold_uncertainty_score":0.083036184},"labels":[],"label_agreement":null},{"id":"W4404520437","doi":"10.1109/tro.2024.3502497","title":"Multirobot Persistent Monitoring: Minimizing Latency and Number of Robots With Recharging Constraints","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Computer science; Latency (audio); Mobile robot; Artificial intelligence; Real-time computing; Telecommunications","score_opus":0.036423058351094544,"score_gpt":0.28368479867927987,"score_spread":0.24726174032818532,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404520437","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1544525,0.0012530823,0.83808833,0.0007803847,0.00007408145,0.00024169427,0.0003723996,0.00058051146,0.0041570417],"genre_scores_gemma":[0.87574744,0.00065835344,0.11730506,0.0001219921,0.00007577176,0.00035470843,0.00034091796,0.00017301622,0.0052226377],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989085,0.0002431403,0.000051357398,0.00039435463,0.00017217829,0.00023049672],"domain_scores_gemma":[0.9966648,0.0019900412,0.0006034466,0.00024799496,0.00019809346,0.00029564492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011401811,0.0016456963,0.001382228,0.00048501222,0.00076797995,0.0012098356,0.0028189996,0.0012789378,0.0033949423],"category_scores_gemma":[0.004805306,0.0005718646,0.00063087296,0.0009212295,0.00081115257,0.0030175175,0.0017101648,0.001065735,0.00030359157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041886736,0.0001729526,0.0014461974,0.0004316175,0.00006929894,0.00033559278,0.0001611891,0.9386875,0.0071638543,0.013701903,0.0010903641,0.036320735],"study_design_scores_gemma":[0.000058000038,0.00028461573,0.0005106648,0.000022689175,0.000035795645,0.00010985238,0.000119726894,0.9779424,0.0028682218,0.016828865,0.0012029961,0.000016123104],"about_ca_topic_score_codex":0.0031765185,"about_ca_topic_score_gemma":0.002736731,"teacher_disagreement_score":0.0033949423,"about_ca_system_score_codex":0.0009741519,"about_ca_system_score_gemma":0.0011735662,"threshold_uncertainty_score":0.011357188},"labels":[],"label_agreement":null},{"id":"W4405364028","doi":"10.11591/ijape.v14.i1.pp146-154","title":"Multi-objective hunter prey optimizer technique for distributed generation placement","year":2024,"lang":"en","type":"article","venue":"International Journal of Applied Power Engineering (IJAPE)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Computer science; Predation; Mathematical optimization; Biology; Mathematics; Ecology","score_opus":0.013713111865695016,"score_gpt":0.26961463615411785,"score_spread":0.25590152428842283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405364028","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028927298,0.00030231127,0.9666128,0.00012675191,0.000047482445,0.000076469,0.000039426697,0.0003039594,0.0035635638],"genre_scores_gemma":[0.5660603,0.00029779493,0.42598286,0.00013707537,0.00004331624,0.00033427935,0.00014374325,0.00010575235,0.006894841],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99978703,0.000080089114,0.000009714078,0.000028647759,0.00007227896,0.000022289823],"domain_scores_gemma":[0.99980074,0.000102250524,0.00003108369,0.000012093867,0.000041726245,0.000012138816],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000718514,0.0008697656,0.00078452425,0.00069946115,0.00035457846,0.00048375453,0.0006381198,0.0006707068,0.0014578328],"category_scores_gemma":[0.0007846846,0.000420263,0.0006424562,0.0005712446,0.00039632083,0.00035707853,0.00053055276,0.0006533036,0.00024612815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047665664,0.000039866813,0.00036693263,0.000043607066,0.000053039057,0.000051185412,0.000027296492,0.96881324,0.0016852852,0.0022837075,0.00057920493,0.026008952],"study_design_scores_gemma":[0.0000066947673,0.00003564111,0.00007756618,0.0000033540894,0.0000055299797,0.000010715454,0.0000048900665,0.99883085,0.00031787757,0.00045653523,0.00024815733,0.0000022003726],"about_ca_topic_score_codex":0.0030757266,"about_ca_topic_score_gemma":0.0037757652,"teacher_disagreement_score":0.0030757266,"about_ca_system_score_codex":0.00049001636,"about_ca_system_score_gemma":0.0007697036,"threshold_uncertainty_score":0.0061156154},"labels":[],"label_agreement":null},{"id":"W4405490714","doi":"10.1109/iccspa61559.2024.10794313","title":"Continuous Action Learning Automata Game Optimizer Applied to Convolutional Neural Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Royal Military College of Canada","funders":"","keywords":"Computer science; Learning automata; Action (physics); Artificial intelligence; Automaton; Convolutional neural network; Cellular automaton; Machine learning","score_opus":0.023425782140693553,"score_gpt":0.27986909336945665,"score_spread":0.25644331122876307,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405490714","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.041783273,0.0005579413,0.94416344,0.000592666,0.00016578057,0.00020051628,0.00008816059,0.00056285976,0.011885365],"genre_scores_gemma":[0.8446777,0.00032434872,0.14678967,0.0003409808,0.00006159135,0.00061494653,0.00011933831,0.00016853456,0.0069029387],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993419,0.00032391705,0.00003725744,0.000102274964,0.00012219495,0.00007233869],"domain_scores_gemma":[0.9976617,0.0017628978,0.000105982166,0.00010848657,0.00023801209,0.00012291849],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019232085,0.0012895562,0.0011751938,0.0005229149,0.00049866445,0.0013570867,0.0010405186,0.0014264474,0.003400293],"category_scores_gemma":[0.0065712095,0.000489326,0.00067399297,0.00035900553,0.0014775061,0.00089507387,0.0014672244,0.0017451172,0.0004561554],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006169391,0.000049239145,0.0005095528,0.000059938582,0.000036502966,0.00006372426,0.000045426685,0.9596071,0.00069353916,0.023190316,0.0008787191,0.014804252],"study_design_scores_gemma":[0.000005453369,0.00002358534,0.000023155773,0.000003931426,0.000002375549,0.000004526485,0.0000028628613,0.9958346,0.00012455019,0.0037516814,0.0002210352,0.0000022550178],"about_ca_topic_score_codex":0.007293091,"about_ca_topic_score_gemma":0.0061765565,"teacher_disagreement_score":0.007293091,"about_ca_system_score_codex":0.0013773993,"about_ca_system_score_gemma":0.0015715469,"threshold_uncertainty_score":0.014501333},"labels":[],"label_agreement":null},{"id":"W4405801658","doi":"10.1007/978-3-031-74580-5_7","title":"Bike Assisted Evacuation on a Line of Robots with S/R Communication Faults","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Robot; Line (geometry); Human–computer interaction; Simulation; Artificial intelligence","score_opus":0.03905140899428842,"score_gpt":0.2925748422041652,"score_spread":0.25352343320987675,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405801658","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6447249,0.00052458263,0.31816182,0.00097045844,0.00041813936,0.00011964812,0.00046454216,0.0018378256,0.032778136],"genre_scores_gemma":[0.96731824,0.00011008994,0.016399521,0.000041825137,0.000024423785,0.000031010357,0.00017372216,0.00004301816,0.015858117],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998542,0.000030113852,0.0000070891033,0.000032632084,0.000023891022,0.000052119376],"domain_scores_gemma":[0.9997209,0.00010531076,0.000033717108,0.000036566016,0.00004773225,0.000055767254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016054658,0.00074101135,0.0010908549,0.00045790023,0.0012213856,0.00072535436,0.0010508777,0.0014479961,0.004727759],"category_scores_gemma":[0.0005930473,0.00027311116,0.0005102759,0.00050855626,0.0005843702,0.0008989431,0.0011641968,0.0006449816,0.00069310726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015124878,0.000108471206,0.0014013521,0.00011461912,0.000046863308,0.0027214645,0.0001741135,0.9409648,0.01266655,0.00466853,0.003937561,0.031683203],"study_design_scores_gemma":[0.000026805961,0.00018356918,0.00044829503,0.000007588143,0.00001360816,0.00017134206,0.00012262924,0.9933501,0.0019869981,0.0024236217,0.0012511116,0.000014302239],"about_ca_topic_score_codex":0.0060424996,"about_ca_topic_score_gemma":0.004523705,"teacher_disagreement_score":0.0060424996,"about_ca_system_score_codex":0.0004388767,"about_ca_system_score_gemma":0.00044074634,"threshold_uncertainty_score":0.015815914},"labels":[],"label_agreement":null},{"id":"W4405993490","doi":"10.1145/3700838.3700858","title":"Deterministic Collision-Free Exploration of Unknown Anonymous Graphs","year":2025,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Computer science; Collision; Theoretical computer science; Computer security","score_opus":0.02466638784754523,"score_gpt":0.2855213981294213,"score_spread":0.2608550102818761,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4405993490","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3113066,0.000545326,0.67348707,0.0009804023,0.00007133841,0.00018322677,0.00042125263,0.0006798118,0.012324997],"genre_scores_gemma":[0.92519665,0.0001579565,0.06786071,0.00013588864,0.00002426286,0.00014744075,0.00024209292,0.00013354528,0.006101431],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99878734,0.00042728762,0.000040839448,0.0002049423,0.00026915662,0.00027039926],"domain_scores_gemma":[0.9912369,0.007106393,0.00045309754,0.00050722377,0.0002827268,0.00041361406],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015580923,0.00070292363,0.0014723024,0.0010036344,0.001120277,0.0014363076,0.0025753265,0.0019499321,0.0027045426],"category_scores_gemma":[0.011753969,0.0009927569,0.00094905973,0.0015887636,0.0022679649,0.002845528,0.0046889987,0.0015801227,0.000313028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036681152,0.000064740954,0.00073431915,0.00007688391,0.000037746002,0.00012834049,0.00016420071,0.95946485,0.0005935884,0.02668392,0.0010893556,0.010595237],"study_design_scores_gemma":[0.000031362608,0.000027692766,0.00009178148,0.0000070937945,0.0000070528017,0.0000245371,0.000030633284,0.9751501,0.00027132718,0.024053037,0.00029893962,0.0000063514062],"about_ca_topic_score_codex":0.006424775,"about_ca_topic_score_gemma":0.0063438434,"teacher_disagreement_score":0.006424775,"about_ca_system_score_codex":0.0014569002,"about_ca_system_score_gemma":0.0018043675,"threshold_uncertainty_score":0.0127747655},"labels":[],"label_agreement":null},{"id":"W4406023013","doi":"10.1007/s10107-024-02184-y","title":"Online bipartite matching in the probe-commit model","year":2025,"lang":"en","type":"article","venue":"Mathematical Programming","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Competitive analysis; Patience; Bipartite graph; Matching (statistics); Online algorithm; Vertex (graph theory); Combinatorics; Mathematics; Commit; Graph; Discrete mathematics; Computer science; Mathematical optimization; Upper and lower bounds; Statistics","score_opus":0.03770484380387491,"score_gpt":0.32009627445079264,"score_spread":0.28239143064691774,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406023013","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13314958,0.0012125896,0.81688815,0.009429887,0.00029444112,0.0003737768,0.0019656066,0.00097360037,0.035712346],"genre_scores_gemma":[0.8638823,0.00099528,0.07752977,0.0010794405,0.0004248107,0.0006047848,0.0010612163,0.0004515347,0.053970788],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964019,0.0018364519,0.00008893965,0.00070457935,0.00036585776,0.00060226716],"domain_scores_gemma":[0.9806331,0.014859938,0.0012813275,0.0016099366,0.00064404187,0.0009716602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045829546,0.0012779576,0.004399503,0.0013805986,0.0016933009,0.0043036295,0.006303525,0.006171576,0.021299258],"category_scores_gemma":[0.02469608,0.0016910987,0.0012864597,0.0034730565,0.0030530032,0.010065397,0.003426626,0.0052631935,0.002442757],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007388883,0.00047947982,0.00083969865,0.00030913792,0.00010106753,0.00038093215,0.00021065929,0.29119533,0.000682818,0.66427326,0.017921006,0.022867732],"study_design_scores_gemma":[0.00010992069,0.000046259425,0.0001337109,0.000019723355,0.00002282329,0.00006878129,0.00005852398,0.6518521,0.00019341457,0.34610933,0.0013628482,0.000022644079],"about_ca_topic_score_codex":0.0050349617,"about_ca_topic_score_gemma":0.005120325,"teacher_disagreement_score":0.021299258,"about_ca_system_score_codex":0.003041329,"about_ca_system_score_gemma":0.002933112,"threshold_uncertainty_score":0.07125318},"labels":[],"label_agreement":null},{"id":"W4406142010","doi":"10.1137/1.9781611978322.48","title":"Parameterized Approximation for Capacitated <i>d</i>-Hitting Set with Hard Capacities","year":2025,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"European Commission; Department of Science and Technology, Ministry of Science and Technology, India; York University; New York University Shanghai","keywords":"Parameterized complexity; Combinatorics; Set cover problem; Vertex (graph theory); Mathematics; Set (abstract data type); Integer (computer science); Vertex cover; Function (biology); Cover (algebra); Discrete mathematics; Minimum weight; Mathematical optimization; Approximation algorithm; Graph; Computer science","score_opus":0.09124989470558423,"score_gpt":0.251023487810218,"score_spread":0.15977359310463377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406142010","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.112665065,0.0031716253,0.8448052,0.0019187318,0.00022806233,0.00032733506,0.0027788398,0.0025583543,0.031546846],"genre_scores_gemma":[0.7261938,0.0014806066,0.25017133,0.00058833894,0.00020974409,0.00056915183,0.0037767948,0.00080504594,0.016205171],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987691,0.00031082777,0.00005075416,0.00030485739,0.00023062858,0.0003338192],"domain_scores_gemma":[0.9968143,0.0022607374,0.00020792197,0.00031538034,0.00013541462,0.00026614836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012182832,0.0019504543,0.002550978,0.0010511456,0.00070369645,0.003264669,0.003920927,0.002025925,0.011966283],"category_scores_gemma":[0.006735448,0.00080828957,0.001237662,0.0036940267,0.0009984481,0.004235773,0.0024104214,0.0024013584,0.0014543515],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00035588542,0.00018695183,0.0008825864,0.0003744148,0.000086857886,0.00014117545,0.0001242709,0.8801445,0.0009286536,0.04340609,0.013424118,0.059944462],"study_design_scores_gemma":[0.000027422435,0.00006735141,0.00015347928,0.000032059066,0.000014228703,0.00008013738,0.00004764212,0.95237064,0.0003634437,0.045185708,0.0016462181,0.000011689196],"about_ca_topic_score_codex":0.0056475773,"about_ca_topic_score_gemma":0.0048428467,"teacher_disagreement_score":0.011966283,"about_ca_system_score_codex":0.0040052664,"about_ca_system_score_gemma":0.0019672418,"threshold_uncertainty_score":0.040031195},"labels":[],"label_agreement":null},{"id":"W4407080566","doi":"10.1007/s10107-025-02195-3","title":"Cut-sufficient directed 2-commodity multiflow topologies","year":2025,"lang":"en","type":"article","venue":"Mathematical Programming","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Network topology; Commodity; Numerical analysis; Mathematical optimization; Mathematical economics; Topology (electrical circuits); Combinatorics; Computer science; Economics; Mathematical analysis; Market economy","score_opus":0.026063294850880613,"score_gpt":0.3037517958765076,"score_spread":0.277688501025627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407080566","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1857145,0.0006903211,0.7563536,0.0016846556,0.00013471364,0.00014554393,0.0017759246,0.00029552315,0.053205203],"genre_scores_gemma":[0.79734313,0.0012238793,0.16524483,0.0005440449,0.00014815727,0.00037603287,0.0017444569,0.00025877234,0.033116687],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993376,0.0002101435,0.00003181749,0.00012035609,0.00015880507,0.0001412378],"domain_scores_gemma":[0.9970276,0.0015688256,0.00032823224,0.00019272717,0.000385205,0.0004974418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014103693,0.0010775359,0.001270974,0.0019083784,0.0012974142,0.0029830672,0.0015506468,0.0013684793,0.015075616],"category_scores_gemma":[0.0059775864,0.0007790539,0.00091331574,0.0017920015,0.0011186672,0.0046653464,0.0027669023,0.0027884354,0.0012943551],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022372059,0.00008870013,0.0005012846,0.00024261768,0.000029506895,0.00020824495,0.00015458089,0.04675356,0.0022464262,0.929029,0.0042950073,0.016227316],"study_design_scores_gemma":[0.000041116535,0.00006990337,0.00031661705,0.000065317996,0.000020336736,0.00022305298,0.00013202742,0.109402776,0.0011543515,0.88312495,0.005428879,0.000020581365],"about_ca_topic_score_codex":0.0009617011,"about_ca_topic_score_gemma":0.0015117999,"teacher_disagreement_score":0.015075616,"about_ca_system_score_codex":0.0014032004,"about_ca_system_score_gemma":0.0008851328,"threshold_uncertainty_score":0.05043298},"labels":[],"label_agreement":null},{"id":"W4407189119","doi":"10.1007/978-3-031-82670-2_1","title":"Distributed Computing by Mobile Robots: Exploring the Computational Landscape (Extended Abstract)","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Mobile robot; Distributed computing; Robot; Human–computer interaction; Theoretical computer science; Artificial intelligence","score_opus":0.022312432559130575,"score_gpt":0.2629811802111595,"score_spread":0.24066874765202895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407189119","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025845192,0.1310558,0.6140293,0.008943475,0.002771565,0.00011587775,0.0002698233,0.0008357054,0.21613331],"genre_scores_gemma":[0.5019203,0.08827612,0.25028074,0.0018944908,0.0031010958,0.00040047793,0.00051027664,0.00066955213,0.15294702],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998826,0.000027496426,0.0000032400173,0.00003969932,0.000033654385,0.000013434636],"domain_scores_gemma":[0.99982905,0.00010943565,0.000008720724,0.000018115104,0.00001611524,0.00001859841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019119853,0.0004949395,0.0006961716,0.0003921552,0.00046907752,0.0022355213,0.00084458326,0.0007579846,0.010593734],"category_scores_gemma":[0.00065453566,0.00028052292,0.00046262832,0.0015252031,0.0012498291,0.0020922439,0.0009589585,0.0012447954,0.0016846821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000090940666,0.00009079959,0.0005178514,0.0011458392,0.00006980295,0.0002295274,0.0006346328,0.07590014,0.0056745284,0.5725688,0.063200794,0.27987638],"study_design_scores_gemma":[0.00003749997,0.00006586498,0.00066533516,0.00021987491,0.00002927821,0.00031475478,0.0002499551,0.09879071,0.001440134,0.71489364,0.18327048,0.000022395243],"about_ca_topic_score_codex":0.0010496441,"about_ca_topic_score_gemma":0.0011772341,"teacher_disagreement_score":0.010593734,"about_ca_system_score_codex":0.0005696019,"about_ca_system_score_gemma":0.00046806454,"threshold_uncertainty_score":0.03543961},"labels":[],"label_agreement":null},{"id":"W4407189250","doi":"10.1007/978-3-031-82670-2_23","title":"Multi-agent Search-Type Problems on Polygons","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Type (biology)","score_opus":0.04104181170680093,"score_gpt":0.2888128697729929,"score_spread":0.24777105806619198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407189250","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.019469567,0.0016681635,0.9070778,0.0010031213,0.00032152986,0.0001310229,0.00029534125,0.00013647047,0.06989698],"genre_scores_gemma":[0.35674974,0.0034043374,0.5611049,0.0002699616,0.00035191048,0.00049202476,0.0006247014,0.00028149615,0.076720916],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995415,0.00020412354,0.000022304694,0.00008036628,0.00010749992,0.00004424964],"domain_scores_gemma":[0.9992478,0.00053512654,0.00006983601,0.000048914757,0.000054579596,0.000043894768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006079235,0.0010184986,0.0012844274,0.00068803865,0.00078021537,0.0023901716,0.0015257188,0.0018751642,0.0066917227],"category_scores_gemma":[0.003304237,0.0006888821,0.0012642286,0.0017057868,0.0015053557,0.0022545292,0.001863323,0.0020532648,0.0007118122],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007501409,0.000046296183,0.00019412118,0.00029553619,0.000037232043,0.00016452571,0.00012980917,0.45856732,0.0011416352,0.49236006,0.006918291,0.040070225],"study_design_scores_gemma":[0.00004232245,0.000041725903,0.000108742126,0.000060674767,0.000014535221,0.000088216475,0.00008846357,0.6304861,0.0006773393,0.35210136,0.016278243,0.0000122892425],"about_ca_topic_score_codex":0.0020514892,"about_ca_topic_score_gemma":0.001696933,"teacher_disagreement_score":0.0066917227,"about_ca_system_score_codex":0.0010970043,"about_ca_system_score_gemma":0.00051855575,"threshold_uncertainty_score":0.022386074},"labels":[],"label_agreement":null},{"id":"W4407194208","doi":"10.1007/s00521-024-10546-y","title":"Optimizing a continuous action learning automata (CALA) optimizer for training artificial neural networks","year":2025,"lang":"en","type":"article","venue":"Neural Computing and Applications","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; Royal Military College of Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computational Science and Engineering; Computer science; Artificial neural network; Training (meteorology); Action (physics); Artificial intelligence; Automaton; Machine learning; Meteorology; Geography","score_opus":0.050106216401688435,"score_gpt":0.3288892452449029,"score_spread":0.27878302884321443,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407194208","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.043585725,0.0005152219,0.9462571,0.00046381057,0.00027364926,0.00012138575,0.00011809862,0.0012687636,0.007396268],"genre_scores_gemma":[0.6720541,0.00014224493,0.32254508,0.0003019921,0.0000850025,0.00040107316,0.00020402671,0.00025491547,0.004011598],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99933976,0.0002400329,0.000046100162,0.00017445488,0.000130397,0.00006923622],"domain_scores_gemma":[0.99752194,0.0016221151,0.0001141436,0.00019257647,0.00046076442,0.00008836137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016115606,0.0009573528,0.00112634,0.00057982025,0.00062202034,0.0011270822,0.0014731025,0.0027140456,0.004097465],"category_scores_gemma":[0.005694297,0.00055700284,0.0007470509,0.00054708676,0.0011551287,0.00084158714,0.001184931,0.0020859742,0.0006502873],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009384362,0.000057984667,0.00051416963,0.00007234438,0.00003744536,0.000043612126,0.000051470142,0.9455946,0.0012504352,0.006854065,0.0013733273,0.04405672],"study_design_scores_gemma":[0.000004820384,0.000013820574,0.000020642263,0.0000033304566,0.0000028311565,0.0000029037126,0.0000024069248,0.9990858,0.00015972226,0.00058877707,0.00011362019,0.0000013504947],"about_ca_topic_score_codex":0.00917709,"about_ca_topic_score_gemma":0.0097309835,"teacher_disagreement_score":0.00917709,"about_ca_system_score_codex":0.0012294397,"about_ca_system_score_gemma":0.0016700109,"threshold_uncertainty_score":0.018247366},"labels":[],"label_agreement":null},{"id":"W4407263581","doi":"10.1016/j.ic.2025.105280","title":"On the computational power of energy-constrained mobile robots","year":2025,"lang":"en","type":"article","venue":"Information and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Japan Society for the Promotion of Science; Japan Society for the Promotion of Science London","keywords":"Computer science; Energy (signal processing); Mobile robot; Power (physics); Robot; Human–computer interaction; Artificial intelligence; Physics","score_opus":0.008253946251145946,"score_gpt":0.24746364461184642,"score_spread":0.23920969836070047,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407263581","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20027342,0.010479206,0.65999675,0.010844142,0.0005684757,0.00006173744,0.00038262934,0.00025679532,0.11713684],"genre_scores_gemma":[0.95698786,0.0026457596,0.030552747,0.00035896813,0.00022300913,0.00006803269,0.00008695408,0.00011709122,0.008959631],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948955,0.0001853416,0.000019998062,0.000071920316,0.00015534493,0.0000777693],"domain_scores_gemma":[0.99407226,0.005206847,0.00015027357,0.0002895933,0.00016927597,0.000111770576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091059256,0.00059920194,0.0008752992,0.00062448275,0.00067500956,0.0015401087,0.0012697454,0.00095240545,0.0067618974],"category_scores_gemma":[0.0100988345,0.00037625874,0.00042701716,0.0011692167,0.0023291593,0.0033695914,0.0022872384,0.0012098962,0.00050761236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002474833,0.000042347758,0.00063418166,0.00019966319,0.00004491893,0.00012936175,0.00015263181,0.5307868,0.0018794878,0.42388982,0.0032061327,0.038787175],"study_design_scores_gemma":[0.000020096439,0.00002216065,0.00021392723,0.000030191184,0.000010539581,0.000029861107,0.000047276993,0.7533325,0.0005135375,0.24361391,0.002157749,0.000008303961],"about_ca_topic_score_codex":0.0019679393,"about_ca_topic_score_gemma":0.0015467368,"teacher_disagreement_score":0.0067618974,"about_ca_system_score_codex":0.00053327665,"about_ca_system_score_gemma":0.0004931307,"threshold_uncertainty_score":0.022620857},"labels":[],"label_agreement":null},{"id":"W4407366263","doi":"10.1007/978-3-031-81396-2","title":"Approximation and Online Algorithms","year":2025,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Birkbeck, University of London; Indian Institute of Technology Delhi; Syddansk Universitet; Indian Institute of Technology Bombay; Sorbonne Université; University of Twente; University of Waterloo; Eidgenössische Technische Hochschule Zürich; Nanjing University; Dalhousie University; Centre National de la Recherche Scientifique; University of Oxford; Université Grenoble Alpes; Aarhus Universitet","keywords":"Computer science; Algorithm","score_opus":0.017033240149665344,"score_gpt":0.27136077012937876,"score_spread":0.2543275299797134,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407366263","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0049635405,0.037707563,0.58335966,0.0053454004,0.0039947936,0.00012863387,0.0015244455,0.003451857,0.3595241],"genre_scores_gemma":[0.1315222,0.03309141,0.33806446,0.0026483252,0.005863965,0.00051553553,0.004849435,0.0034917644,0.4799529],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99890757,0.0002111666,0.000037983045,0.00023367102,0.00048801047,0.0001215753],"domain_scores_gemma":[0.9985461,0.000655137,0.000054301494,0.00051562296,0.00015408733,0.000074774514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008271206,0.0020833118,0.0024386924,0.0015144388,0.0008255745,0.003421465,0.00235916,0.0016600206,0.049977813],"category_scores_gemma":[0.004209759,0.00088624936,0.001175916,0.0050758235,0.0013026444,0.0048970752,0.002050926,0.0056921057,0.019932793],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019376642,0.00021084932,0.00026598392,0.00045519444,0.000068518064,0.000057559442,0.00005381235,0.026845409,0.00095942384,0.2906332,0.24765468,0.43260157],"study_design_scores_gemma":[0.00006040135,0.000054193737,0.0005333032,0.00018164552,0.0000600353,0.00028795103,0.00004176488,0.1105247,0.0013814521,0.6651707,0.22167973,0.000024128312],"about_ca_topic_score_codex":0.0018739073,"about_ca_topic_score_gemma":0.001989011,"teacher_disagreement_score":0.049977813,"about_ca_system_score_codex":0.0021321054,"about_ca_system_score_gemma":0.0011596549,"threshold_uncertainty_score":0.1671924},"labels":[],"label_agreement":null},{"id":"W4408013772","doi":"10.1016/j.orl.2025.107257","title":"Single sample prophet inequality for uniform matroids of rank 2","year":2025,"lang":"en","type":"article","venue":"Operations Research Letters","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matroid; Rank (graph theory); Mathematics; Inequality; Sample (material); Combinatorics; Mathematical analysis; Physics","score_opus":0.09306778438594705,"score_gpt":0.38871001137835837,"score_spread":0.2956422269924113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408013772","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08699347,0.002082554,0.856396,0.005773521,0.00024725444,0.00016814334,0.0012216886,0.0006220957,0.046495225],"genre_scores_gemma":[0.8397401,0.0024465437,0.12664825,0.0020723012,0.0008269059,0.00075474754,0.0010376849,0.0003893653,0.02608424],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99258524,0.0028620928,0.00030605218,0.001157387,0.0019713677,0.0011177385],"domain_scores_gemma":[0.9283742,0.05505743,0.0046569016,0.006945042,0.0029407186,0.0020257286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010393507,0.0018079095,0.0023391563,0.0017376604,0.0018053306,0.0039066914,0.0042412304,0.003151018,0.015603382],"category_scores_gemma":[0.06251522,0.0011313171,0.0018607271,0.002178671,0.004615998,0.012332081,0.004461731,0.006572224,0.0020335694],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003256534,0.00008977959,0.0011282635,0.0002843088,0.00007743766,0.00029023248,0.00022803126,0.041672584,0.001846223,0.93155384,0.004998498,0.017505134],"study_design_scores_gemma":[0.000048174614,0.00013564703,0.00044499946,0.000061447674,0.000023390689,0.0002284733,0.00004216062,0.1954127,0.00097146956,0.80030775,0.0022894891,0.000034255623],"about_ca_topic_score_codex":0.0011670764,"about_ca_topic_score_gemma":0.0012625139,"teacher_disagreement_score":0.015603382,"about_ca_system_score_codex":0.0030125924,"about_ca_system_score_gemma":0.001958849,"threshold_uncertainty_score":0.054966748},"labels":[],"label_agreement":null},{"id":"W4408128235","doi":"10.1007/978-981-96-1090-7_2","title":"An Optimal Absolute Approximation Algorithm for Computing k Restricted Shortest Paths","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Computer science; Algorithm; Approximation algorithm; Shortest path problem; Theoretical computer science; Graph","score_opus":0.01996489278085252,"score_gpt":0.27794704484643046,"score_spread":0.25798215206557795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408128235","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023596346,0.00083755446,0.961495,0.00034941177,0.00021042074,0.00016503864,0.00056152104,0.003487997,0.009296737],"genre_scores_gemma":[0.08830837,0.00031202417,0.9038512,0.00011902104,0.000066768196,0.00021383453,0.0012050024,0.00038851562,0.0055351327],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99842405,0.00028735513,0.00012494005,0.00050704315,0.00045272586,0.0002038446],"domain_scores_gemma":[0.99840873,0.00071056903,0.00009267717,0.00046931155,0.00022813534,0.00009055034],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010801685,0.0015779915,0.0021779663,0.0017993624,0.0012698959,0.0028683436,0.0043049315,0.0018270861,0.014420664],"category_scores_gemma":[0.00536738,0.00095698074,0.0016015933,0.004331887,0.0010916298,0.0050119013,0.002751359,0.002876869,0.00390689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012473873,0.00038892127,0.0007938182,0.00059458264,0.00011692784,0.00009686663,0.00028505299,0.22587115,0.008106372,0.06718172,0.020758819,0.67455834],"study_design_scores_gemma":[0.00015749966,0.00019561747,0.00042561704,0.00006723145,0.000054736087,0.00022171816,0.00016210732,0.90880054,0.0035294907,0.07656936,0.009777166,0.000038910985],"about_ca_topic_score_codex":0.0052830474,"about_ca_topic_score_gemma":0.0076567642,"teacher_disagreement_score":0.014420664,"about_ca_system_score_codex":0.0022437142,"about_ca_system_score_gemma":0.0027820584,"threshold_uncertainty_score":0.048241913},"labels":[],"label_agreement":null},{"id":"W4408215908","doi":"10.56553/popets-2025-0055","title":"Private Shared Random Minimum Spanning Forests","year":2025,"lang":"en","type":"article","venue":"Proceedings on Privacy Enhancing Technologies","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Ontario; Royal Bank of Canada","keywords":"Spanning tree; Business; Mathematics; Combinatorics","score_opus":0.01709837059611084,"score_gpt":0.2727739251701088,"score_spread":0.25567555457399793,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408215908","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15511766,0.0008844078,0.8191634,0.0021888698,0.0002222308,0.00058200187,0.0026366021,0.003982303,0.015222645],"genre_scores_gemma":[0.9074057,0.00021474734,0.08456768,0.00035607937,0.000060755083,0.00033827891,0.001322639,0.00026110272,0.005472995],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9952767,0.0018179031,0.00025767102,0.00084181374,0.0012065015,0.0005994071],"domain_scores_gemma":[0.9897119,0.003083569,0.0008043188,0.0052944063,0.0006946773,0.00041114172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003958743,0.0005987424,0.0011023318,0.00046260975,0.0012633662,0.0016473557,0.0025841824,0.0017741311,0.00596696],"category_scores_gemma":[0.014154017,0.00050694705,0.00084099313,0.000956186,0.0013092534,0.0056421226,0.004551125,0.0019639959,0.0013869222],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033231121,0.0005019801,0.0047357734,0.00083488994,0.00028201853,0.0009610303,0.0009740042,0.33116776,0.04577898,0.38356847,0.029068295,0.19880368],"study_design_scores_gemma":[0.0002286752,0.00018694422,0.0006649058,0.000056941197,0.0000690009,0.00049550383,0.00014706145,0.69803226,0.015455828,0.2728082,0.011796166,0.000058624177],"about_ca_topic_score_codex":0.000708782,"about_ca_topic_score_gemma":0.0013499806,"teacher_disagreement_score":0.00596696,"about_ca_system_score_codex":0.0014983716,"about_ca_system_score_gemma":0.0019526492,"threshold_uncertainty_score":0.020936131},"labels":[],"label_agreement":null},{"id":"W4408285114","doi":"10.1145/3711701","title":"Learning-Augmented Competitive Algorithms for Spatiotemporal Online Allocation with Deadline Constraints","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ACM on Measurement and Analysis of Computing Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Universitas Brawijaya; VMware","keywords":"Computer science; Algorithm; Artificial intelligence; Distributed computing","score_opus":0.036851129680717055,"score_gpt":0.282232683337481,"score_spread":0.24538155365676398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408285114","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015829658,0.00073958427,0.9777077,0.00053158985,0.00011650105,0.00012622321,0.00014685612,0.00048098524,0.0043208697],"genre_scores_gemma":[0.57846826,0.0007250328,0.41296783,0.00068795204,0.00033649668,0.00057210866,0.0007176158,0.00027109013,0.0052535683],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99825114,0.00063178525,0.00009646579,0.00040464362,0.0003387949,0.00027715156],"domain_scores_gemma":[0.9919992,0.0059974752,0.0005592026,0.00043480817,0.00064955925,0.00035977608],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025631934,0.0019019064,0.0028669746,0.0010728539,0.0009501654,0.0021070002,0.0036704927,0.0025696005,0.004287738],"category_scores_gemma":[0.011788948,0.000742309,0.00084266043,0.0023345193,0.001512913,0.0027668169,0.0020527567,0.0025329755,0.0008052721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001545568,0.00019698711,0.0006090199,0.00014812796,0.00005875878,0.000049553335,0.000059739043,0.918707,0.00044746726,0.024577577,0.00300286,0.051988386],"study_design_scores_gemma":[0.000019377367,0.000032061907,0.00003916206,0.0000047990166,0.000004176346,0.000009855726,0.000008117954,0.9898168,0.00010052591,0.009519941,0.00044118986,0.000004071513],"about_ca_topic_score_codex":0.009734629,"about_ca_topic_score_gemma":0.0077779414,"teacher_disagreement_score":0.009734629,"about_ca_system_score_codex":0.0019908643,"about_ca_system_score_gemma":0.0034346795,"threshold_uncertainty_score":0.019355953},"labels":[],"label_agreement":null},{"id":"W4408343545","doi":"10.1145/3723351","title":"Threshold Policies with Tight Guarantees for Online Selection with Convex Costs","year":2025,"lang":"en","type":"article","venue":"ACM Transactions on Economics and Computation","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo; University of Alberta","funders":"","keywords":"Selection (genetic algorithm); Regular polygon; Computer science; Mathematical optimization; Operations research; Business; Mathematics; Artificial intelligence","score_opus":0.016571547734413043,"score_gpt":0.26647594002704195,"score_spread":0.2499043922926289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408343545","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026208488,0.0006405896,0.9624726,0.0008555049,0.00012978473,0.00018718308,0.00020266027,0.0009814335,0.008321787],"genre_scores_gemma":[0.80696434,0.0012586314,0.18316473,0.0009542578,0.0003101054,0.0004909916,0.00039399602,0.000623929,0.00583903],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.993912,0.0017623288,0.000318528,0.0008857262,0.0018548071,0.0012666865],"domain_scores_gemma":[0.96091175,0.029787851,0.0023957198,0.0032674419,0.0019213093,0.0017158525],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005571362,0.0024046083,0.0028943124,0.001118492,0.0014838574,0.0035867149,0.003244504,0.002139295,0.0072277426],"category_scores_gemma":[0.04303243,0.0010761193,0.0013486634,0.0021491395,0.0024766382,0.0072289845,0.003195276,0.0060497494,0.0014404374],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000687412,0.00057128054,0.0013652937,0.0004141081,0.000092103466,0.00022658736,0.0002656249,0.64292467,0.0052075544,0.27416834,0.009355228,0.0647218],"study_design_scores_gemma":[0.00006558467,0.000111188434,0.00013474334,0.000025803427,0.000016028773,0.00008919914,0.00003068619,0.8958842,0.0011838557,0.10095575,0.0014828766,0.00002010888],"about_ca_topic_score_codex":0.0025259976,"about_ca_topic_score_gemma":0.0021058535,"teacher_disagreement_score":0.0072277426,"about_ca_system_score_codex":0.003421847,"about_ca_system_score_gemma":0.0045330278,"threshold_uncertainty_score":0.029464543},"labels":[],"label_agreement":null},{"id":"W4408370374","doi":"10.1007/978-981-96-2220-7_16","title":"Distributed Mission Planning for Multi-spacecraft Based on Potential Game","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in electrical engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University","funders":"","keywords":"Spacecraft; Aerospace engineering; Computer science; Potential game; Aeronautics; Astrobiology; Systems engineering; Game theory; Engineering; Physics; Mathematics","score_opus":0.018472598786174996,"score_gpt":0.26504284200933675,"score_spread":0.24657024322316176,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408370374","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024178306,0.00045931397,0.9650948,0.00021323569,0.000056219484,0.000054165514,0.00004812171,0.000089322915,0.009806504],"genre_scores_gemma":[0.89149755,0.0005167532,0.09926436,0.00007449833,0.000043654865,0.000224813,0.00008998212,0.000054426444,0.008233818],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997775,0.00007665602,0.00000853927,0.000045946854,0.000050369956,0.00004090723],"domain_scores_gemma":[0.9996903,0.00020452244,0.000024942035,0.000012706676,0.000034743272,0.000032830867],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045361574,0.000703002,0.0013131734,0.0004590973,0.00054403255,0.0009144469,0.0011990914,0.00080638746,0.0025565298],"category_scores_gemma":[0.0009900182,0.0005179358,0.0008515944,0.0006648917,0.00077475543,0.0010205387,0.001279603,0.001092523,0.00019185945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031634034,0.000017991451,0.00011973437,0.000043166,0.000019898927,0.000050232855,0.000028144103,0.9651118,0.00082296354,0.02591067,0.0005316742,0.0073120026],"study_design_scores_gemma":[0.000005261265,0.000012279128,0.000026440812,0.0000021518779,0.0000027691121,0.000008351882,0.0000047922777,0.992305,0.0000524951,0.007395868,0.00018233585,0.0000022310915],"about_ca_topic_score_codex":0.005507184,"about_ca_topic_score_gemma":0.004224298,"teacher_disagreement_score":0.005507184,"about_ca_system_score_codex":0.0010703197,"about_ca_system_score_gemma":0.0009870906,"threshold_uncertainty_score":0.010950208},"labels":[],"label_agreement":null},{"id":"W4409473625","doi":"10.1109/tase.2025.3560956","title":"Only Pick Once: Algorithms for Efficiently Picking an Exact Number of Multiple Identical Objects","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Automation Science and Engineering","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Algorithm; Computer science","score_opus":0.019212677745341508,"score_gpt":0.3065254537848646,"score_spread":0.2873127760395231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409473625","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.034266837,0.00033145538,0.95541817,0.00014780906,0.00007625418,0.00016369259,0.00014163238,0.007159303,0.0022947488],"genre_scores_gemma":[0.26360798,0.00024069645,0.72737336,0.00018575473,0.000046352263,0.00017718045,0.0004989892,0.00056199677,0.0073076105],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99930525,0.000050596067,0.000046586214,0.000215537,0.0002751455,0.000106825224],"domain_scores_gemma":[0.9988605,0.0002940678,0.00016903618,0.00039685203,0.00017738879,0.00010212553],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008399808,0.001296723,0.0013503748,0.0010848824,0.000961982,0.0008088031,0.0027313475,0.0012203656,0.005320766],"category_scores_gemma":[0.002547743,0.0006515206,0.0006375195,0.0011002492,0.00093536044,0.0028311105,0.0022361702,0.0009850374,0.0023627058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005241532,0.00022579159,0.0020627852,0.00016078698,0.000060364622,0.00014056882,0.00011433898,0.0902685,0.01919032,0.0047337874,0.006654134,0.8758645],"study_design_scores_gemma":[0.000053496824,0.0001762259,0.0010922994,0.000019599618,0.000026076246,0.00027500707,0.000083013474,0.9667294,0.016220437,0.01005029,0.005232607,0.00004151242],"about_ca_topic_score_codex":0.00563824,"about_ca_topic_score_gemma":0.009097001,"teacher_disagreement_score":0.00563824,"about_ca_system_score_codex":0.0007559043,"about_ca_system_score_gemma":0.0016194985,"threshold_uncertainty_score":0.017799735},"labels":[],"label_agreement":null},{"id":"W4410397800","doi":"10.1016/j.jcss.2025.103678","title":"Weighted group search on the disk &amp; improved lower bounds for priority evacuation","year":2025,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Group (periodic table); Computer science; Combinatorics; Mathematics; Mathematical optimization; Chemistry","score_opus":0.031114535952634755,"score_gpt":0.3065126150479861,"score_spread":0.27539807909535136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410397800","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03184381,0.0024378768,0.9469562,0.0014815978,0.00023822596,0.00010087131,0.00025614622,0.00028041037,0.016404822],"genre_scores_gemma":[0.66523296,0.0030348909,0.30949697,0.0009203333,0.0005548502,0.0005453335,0.00071703526,0.0006939041,0.018803734],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99787354,0.0008293598,0.00006998081,0.00032115306,0.00045222946,0.0004537077],"domain_scores_gemma":[0.99231684,0.005369629,0.0006229948,0.00056254986,0.000564872,0.00056313217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027300152,0.002360935,0.0019145154,0.0014046577,0.0010710394,0.002141237,0.003194048,0.0019259948,0.007790113],"category_scores_gemma":[0.018214421,0.000623042,0.0012807559,0.0020311032,0.001589203,0.0072502466,0.0034688755,0.003975597,0.0012840831],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00045680313,0.00026938872,0.0010756216,0.00052887655,0.00011003214,0.00016217725,0.00034471543,0.6814015,0.0036553696,0.24923487,0.011636006,0.05112465],"study_design_scores_gemma":[0.00002403461,0.00010104205,0.00015721309,0.00004540388,0.0000212184,0.000039062958,0.00006401277,0.9080177,0.00076470507,0.08773136,0.0030190006,0.000015325864],"about_ca_topic_score_codex":0.0023562168,"about_ca_topic_score_gemma":0.002408639,"teacher_disagreement_score":0.007790113,"about_ca_system_score_codex":0.0021127427,"about_ca_system_score_gemma":0.0013412442,"threshold_uncertainty_score":0.026060522},"labels":[],"label_agreement":null},{"id":"W4410432240","doi":"10.1287/mnsc.2023.00309","title":"Uncertain Search with Knowledge Transfer","year":2025,"lang":"en","type":"article","venue":"Management Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Knowledge transfer; Knowledge management","score_opus":0.020966666172799145,"score_gpt":0.29874203160311097,"score_spread":0.27777536543031184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410432240","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11528326,0.002790987,0.8268855,0.006254404,0.00024177316,0.0002109183,0.0008232764,0.00025476151,0.047255166],"genre_scores_gemma":[0.89752406,0.0013801008,0.07851929,0.00054603413,0.00023912112,0.00044457035,0.00035872223,0.00007898805,0.02090907],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99760807,0.0011590441,0.000089578454,0.0005393976,0.00029442375,0.00030947675],"domain_scores_gemma":[0.9914008,0.0068674083,0.00068609574,0.00038240914,0.00027479665,0.00038850415],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027460246,0.0012193084,0.0022640259,0.0011235473,0.0010807666,0.003115309,0.0025969108,0.0044078524,0.011155501],"category_scores_gemma":[0.015666604,0.00095984933,0.0017215876,0.0016988128,0.0025258102,0.0048021786,0.0025995036,0.002754768,0.00078440545],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020364368,0.00009796805,0.0009694343,0.00018964346,0.00012442909,0.0003160258,0.00017863227,0.6122896,0.00031454468,0.36881337,0.0017801936,0.014722554],"study_design_scores_gemma":[0.00007676968,0.000058992176,0.0002514407,0.000027569902,0.000033122556,0.00004945484,0.000045193792,0.68154234,0.0001256073,0.3160114,0.0017500941,0.000027975342],"about_ca_topic_score_codex":0.00870856,"about_ca_topic_score_gemma":0.0044936696,"teacher_disagreement_score":0.011155501,"about_ca_system_score_codex":0.0031016897,"about_ca_system_score_gemma":0.0017839117,"threshold_uncertainty_score":0.037318945},"labels":[],"label_agreement":null},{"id":"W4410553862","doi":"10.1007/978-3-031-91736-3_18","title":"Oblivious Robots Under Sequential Schedulers: Universal Pattern Formation","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science; Robot; Theoretical computer science; Distributed computing; Artificial intelligence","score_opus":0.024793170628626637,"score_gpt":0.25921107446130714,"score_spread":0.23441790383268052,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410553862","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.114371814,0.0003151431,0.86316246,0.00064160867,0.00013223452,0.00017091412,0.00016485662,0.0016586558,0.01938232],"genre_scores_gemma":[0.8631587,0.000334892,0.12329872,0.00016203403,0.00008359702,0.00026450938,0.00014409119,0.00029020672,0.012263343],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988959,0.00023348474,0.00006250942,0.00029720383,0.00021701513,0.00029394194],"domain_scores_gemma":[0.99646413,0.0013236376,0.00037512486,0.001286131,0.00024134296,0.00030954607],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011514637,0.00053633057,0.001227778,0.0004604549,0.0011208721,0.001401868,0.0022122336,0.00091773306,0.0035257363],"category_scores_gemma":[0.0055605173,0.0007158902,0.0007132463,0.0009853505,0.0025894407,0.0038728293,0.0040276833,0.0015418482,0.0005260665],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043174915,0.000102933605,0.0006912887,0.000216525,0.00005297704,0.00014829084,0.00034879672,0.20831648,0.007434194,0.7143194,0.004469329,0.06346802],"study_design_scores_gemma":[0.00005736398,0.00006836195,0.00019498741,0.000012082954,0.00001581785,0.00006511172,0.00005681432,0.37589705,0.0029307893,0.6189244,0.0017616376,0.000015504022],"about_ca_topic_score_codex":0.0017266744,"about_ca_topic_score_gemma":0.0020117671,"teacher_disagreement_score":0.0035257363,"about_ca_system_score_codex":0.0012162431,"about_ca_system_score_gemma":0.0023343575,"threshold_uncertainty_score":0.011794746},"labels":[],"label_agreement":null},{"id":"W4410553941","doi":"10.1007/978-3-031-91736-3_5","title":"Exploration of Convex Terrains by a Deterministic Automaton with Pebbles","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Computer science; Automaton; Deterministic automaton; Regular polygon; Terrain; Büchi automaton; Algorithm; Theoretical computer science; Geometry; Mathematics; Cartography","score_opus":0.02013115548736642,"score_gpt":0.25897559071636617,"score_spread":0.23884443522899976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410553941","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34928912,0.00026241998,0.6299937,0.00034774185,0.000092707676,0.000082549384,0.00027833862,0.0012924218,0.018361073],"genre_scores_gemma":[0.8910387,0.00014941739,0.102745526,0.000055531786,0.000016346037,0.0001157915,0.00019428949,0.00012536548,0.005559066],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997818,0.000040221228,0.000015803282,0.00006777058,0.000047459627,0.00004690702],"domain_scores_gemma":[0.99925154,0.0004542816,0.00005356575,0.00009746693,0.00005934223,0.000083721796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020703668,0.00046878678,0.0009028453,0.0005203449,0.0009560571,0.0011119038,0.0014768844,0.0010810997,0.0052986215],"category_scores_gemma":[0.0013945164,0.00059426326,0.0009404343,0.0005891257,0.0015287226,0.0012981656,0.0021711923,0.0008244967,0.00052817876],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001622611,0.000044397293,0.0010190194,0.00007127219,0.000030290852,0.00024887995,0.00016418802,0.9380454,0.006286265,0.03594923,0.0006321087,0.017346712],"study_design_scores_gemma":[0.000012251908,0.000028389719,0.00006941132,0.000006576926,0.0000049767737,0.00001800208,0.000019946072,0.9875309,0.0005459694,0.011377296,0.00037899087,0.0000072787443],"about_ca_topic_score_codex":0.0055737086,"about_ca_topic_score_gemma":0.0052422024,"teacher_disagreement_score":0.0055737086,"about_ca_system_score_codex":0.00073548453,"about_ca_system_score_gemma":0.0006760493,"threshold_uncertainty_score":0.017725646},"labels":[],"label_agreement":null},{"id":"W4410553953","doi":"10.1007/978-3-031-91736-3_16","title":"Multi-agent Disk Inspection","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Computer graphics (images); Computer vision; Engineering drawing; Engineering","score_opus":0.024340273850264316,"score_gpt":0.27294378866989777,"score_spread":0.24860351481963344,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410553953","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.047680486,0.002089754,0.88488686,0.00069701095,0.00034142422,0.00020071618,0.00013744897,0.0031263703,0.06084],"genre_scores_gemma":[0.7647219,0.0008562113,0.15179916,0.00015498506,0.000066374436,0.00012715101,0.00017116225,0.00025241871,0.081850655],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99960786,0.00008048506,0.000017801647,0.00008970445,0.00013606739,0.000068086105],"domain_scores_gemma":[0.9991841,0.00028086215,0.00009594297,0.00020357007,0.00017106294,0.00006453037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049830024,0.0006996875,0.00092763506,0.0005260304,0.0005860807,0.0012544325,0.0015460529,0.0011656615,0.007524249],"category_scores_gemma":[0.0020493933,0.0004005874,0.0004431289,0.0005864216,0.00048319437,0.0009100995,0.0011996398,0.00077021134,0.0013293023],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0004641836,0.0003287023,0.0010586686,0.00043036236,0.000072781935,0.00041061547,0.00017724147,0.57634157,0.01588853,0.04301676,0.019512,0.34229854],"study_design_scores_gemma":[0.000020225038,0.00008142268,0.00037072963,0.000024985975,0.000016914839,0.00012660954,0.000046748282,0.9731871,0.0034326538,0.013058522,0.009622444,0.000011688387],"about_ca_topic_score_codex":0.0020510813,"about_ca_topic_score_gemma":0.001869049,"teacher_disagreement_score":0.007524249,"about_ca_system_score_codex":0.0006579819,"about_ca_system_score_gemma":0.0007262525,"threshold_uncertainty_score":0.025171101},"labels":[],"label_agreement":null},{"id":"W4410789742","doi":"10.1080/03155986.2025.2510171","title":"A stochastic leader-follower model in competitive facility location","year":2025,"lang":"en","type":"article","venue":"INFOR Information Systems and Operational Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Facility location problem; Stochastic modelling; Computer science; Operations research; Engineering; Mathematics; Statistics","score_opus":0.06720263850202583,"score_gpt":0.35704757993454095,"score_spread":0.2898449414325151,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410789742","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11937881,0.0003651819,0.8641359,0.0010162117,0.00014555607,0.00015433354,0.0006497889,0.00030560725,0.01384854],"genre_scores_gemma":[0.9301042,0.00032225717,0.053660754,0.00019700106,0.00009482506,0.00022827234,0.00039485338,0.000042849442,0.014955063],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983468,0.000638961,0.000057202316,0.00038154706,0.00025430977,0.00032110015],"domain_scores_gemma":[0.99680173,0.0019510938,0.00047992254,0.0001461388,0.00030315045,0.00031791447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018896781,0.0010074989,0.0019438297,0.00063401274,0.0010420112,0.0018316748,0.0030936468,0.002827423,0.0072857244],"category_scores_gemma":[0.0042413417,0.000724814,0.0009862314,0.0011555435,0.0016457487,0.001667452,0.0012019171,0.0016704036,0.0008853058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013598935,0.00006508353,0.0005498993,0.00004881216,0.000031165597,0.00020299392,0.000071430935,0.9518746,0.00044981187,0.041831084,0.0011575366,0.0035816312],"study_design_scores_gemma":[0.000035569712,0.00003997624,0.00007831604,0.0000025871184,0.0000054944503,0.000020204696,0.000020324418,0.9922356,0.000056073382,0.0072058383,0.00029144873,0.000008483288],"about_ca_topic_score_codex":0.011405057,"about_ca_topic_score_gemma":0.008693379,"teacher_disagreement_score":0.011405057,"about_ca_system_score_codex":0.0015676746,"about_ca_system_score_gemma":0.0013295929,"threshold_uncertainty_score":0.024373114},"labels":[],"label_agreement":null},{"id":"W4411019970","doi":"10.1145/3726854.3727292","title":"Learning-Augmented Competitive Algorithms for Spatiotemporal Online Allocation with Deadline Constraints","year":2025,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Competitive analysis; Distributed computing; Artificial intelligence","score_opus":0.021685867616091585,"score_gpt":0.2997642033887987,"score_spread":0.27807833577270713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411019970","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017105872,0.0007864267,0.9758371,0.00056842086,0.0001233289,0.00013193066,0.00016126005,0.0004814074,0.0048043076],"genre_scores_gemma":[0.5865192,0.000714594,0.40458995,0.00069441844,0.0003181223,0.0005617801,0.00073192455,0.00027082386,0.005599204],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998528,0.0005326965,0.00008270077,0.00034383283,0.0002736975,0.00023906493],"domain_scores_gemma":[0.99327856,0.00504941,0.00047213418,0.00035467997,0.0005293679,0.0003158505],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023550012,0.0018730619,0.0027740572,0.0009876555,0.0009053624,0.0019626662,0.0034039274,0.0025440217,0.0045067878],"category_scores_gemma":[0.010289117,0.0007122284,0.00081428984,0.002094485,0.0013970474,0.0024576131,0.001911469,0.0023923852,0.00081229967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001506774,0.00018919233,0.00057531695,0.00014546317,0.000056830984,0.000050744457,0.00005525252,0.9243744,0.0004172925,0.022821352,0.0029862467,0.04817721],"study_design_scores_gemma":[0.000020556445,0.00003199871,0.000037081332,0.0000049649625,0.0000043242776,0.000009488634,0.000008051463,0.9904156,0.00009440404,0.00890556,0.00046421585,0.0000037808275],"about_ca_topic_score_codex":0.009544755,"about_ca_topic_score_gemma":0.007986748,"teacher_disagreement_score":0.009544755,"about_ca_system_score_codex":0.0018065734,"about_ca_system_score_gemma":0.0032104144,"threshold_uncertainty_score":0.018978417},"labels":[],"label_agreement":null},{"id":"W4411137410","doi":"10.1016/j.tcs.2025.115395","title":"Sniffing helps to meet: Deterministic rendezvous of anonymous agents in the grid","year":2025,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Università degli Studi di Milano-Bicocca; Université du Québec en Outaouais","keywords":"Sniffing; Rendezvous; Computer science; Grid; Computer security; Distributed computing; Mathematics; Psychology; Engineering","score_opus":0.021273114272894248,"score_gpt":0.31530384470650036,"score_spread":0.2940307304336061,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411137410","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.47874448,0.00021336308,0.5064393,0.00072175777,0.00008459313,0.00013702904,0.00014922956,0.0005677793,0.012942435],"genre_scores_gemma":[0.9564727,0.00007272234,0.039758272,0.000044407796,0.000013884252,0.00005521903,0.000054286,0.00003906034,0.0034894326],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99872726,0.00037538138,0.00006301416,0.00024720904,0.00023816976,0.00034907734],"domain_scores_gemma":[0.9958502,0.001952758,0.0006823499,0.00078035373,0.00029813324,0.00043620978],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011106853,0.00043164098,0.00077417423,0.00044984018,0.00186058,0.0012551042,0.001653702,0.0011404249,0.0022966966],"category_scores_gemma":[0.0067429524,0.0003705102,0.00084591424,0.0005496324,0.0022184374,0.0021658454,0.002788116,0.0008290202,0.00039699808],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009907047,0.0001125181,0.00539578,0.000119051634,0.00009000581,0.0016310399,0.001139655,0.7625768,0.0079072965,0.19508368,0.0016739354,0.023279468],"study_design_scores_gemma":[0.000088221284,0.0001138386,0.0005388687,0.000012317289,0.000020935215,0.00026609722,0.00039652354,0.8961879,0.0029680845,0.09667609,0.0026981197,0.000033025044],"about_ca_topic_score_codex":0.0061316057,"about_ca_topic_score_gemma":0.004681176,"teacher_disagreement_score":0.0061316057,"about_ca_system_score_codex":0.0009792312,"about_ca_system_score_gemma":0.0009549409,"threshold_uncertainty_score":0.012191832},"labels":[],"label_agreement":null},{"id":"W4411142825","doi":"10.1109/tro.2025.3578228","title":"SDPRLayers: Certifiable Backpropagation Through Polynomial Optimization Problems in Robotics","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Backpropagation; Artificial intelligence; Robotics; Computer science; Polynomial; Robot; Artificial neural network; Mathematics","score_opus":0.028160943682883313,"score_gpt":0.26998085358039997,"score_spread":0.24181990989751667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411142825","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0012864865,0.000333388,0.9949868,0.00034983217,0.000060151673,0.000024340188,0.000031562988,0.0007497911,0.0021776874],"genre_scores_gemma":[0.10417001,0.0012303047,0.8831359,0.0006264589,0.00019467852,0.00020002751,0.00023668763,0.0008706384,0.009335249],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990439,0.00032682926,0.00005820605,0.00016269335,0.00031992697,0.00008848369],"domain_scores_gemma":[0.9983606,0.00095940626,0.00013049292,0.00024782744,0.0002177897,0.000083940744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002930742,0.0015516845,0.0011327825,0.0007430356,0.0004925627,0.001636218,0.0025707872,0.002383025,0.0052203587],"category_scores_gemma":[0.006640669,0.0008262808,0.0009784685,0.0007929792,0.0021639285,0.0030548337,0.003422026,0.005108613,0.002004121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009257276,0.000079570316,0.00027813375,0.00031716924,0.00006541644,0.00009749214,0.00012498413,0.5984408,0.002527926,0.22418043,0.01397783,0.15981764],"study_design_scores_gemma":[0.000015610865,0.000024592362,0.000024602707,0.000023880853,0.000005354906,0.000024857463,0.000007854684,0.93021077,0.0016295084,0.061719246,0.0063039656,0.00000975127],"about_ca_topic_score_codex":0.0037354361,"about_ca_topic_score_gemma":0.0041571124,"teacher_disagreement_score":0.0052203587,"about_ca_system_score_codex":0.001346892,"about_ca_system_score_gemma":0.0025419658,"threshold_uncertainty_score":0.017463803},"labels":[],"label_agreement":null},{"id":"W4411188042","doi":"10.1007/978-3-031-93112-3_28","title":"Unsplittable Multicommodity Flows in Outerplanar Graphs","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Combinatorics; Outerplanar graph; Discrete mathematics; Mathematics; Pathwidth; Graph; Line graph","score_opus":0.01757865680214116,"score_gpt":0.259238448870317,"score_spread":0.24165979206817584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411188042","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21751478,0.0030304107,0.5750222,0.0014109537,0.00046494222,0.00019679908,0.0011044199,0.00083781,0.20041764],"genre_scores_gemma":[0.6221718,0.007267441,0.2004169,0.00035676747,0.00039122882,0.00025379882,0.0019071901,0.0007916742,0.16644323],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997954,0.000039839786,0.0000098655155,0.00004458378,0.00005543136,0.000054884556],"domain_scores_gemma":[0.9994143,0.00033604464,0.000063349726,0.00007417672,0.00006614656,0.000045984954],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003077463,0.0009161823,0.0005015781,0.000756709,0.0008567713,0.0014552535,0.0012616725,0.0006583033,0.008867423],"category_scores_gemma":[0.0017399681,0.0005748905,0.00054813037,0.0022877075,0.0006953126,0.003299854,0.0010821384,0.0018136892,0.0011718799],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00026066726,0.00014105697,0.0004158122,0.00064215326,0.000026688951,0.00034309368,0.0005990226,0.14709815,0.010412073,0.6424973,0.019363357,0.1782006],"study_design_scores_gemma":[0.000020410705,0.00005964424,0.00043259418,0.00009336921,0.000022239125,0.00016446957,0.0001438557,0.14581573,0.0036792618,0.8151097,0.03444168,0.000016937327],"about_ca_topic_score_codex":0.0020905829,"about_ca_topic_score_gemma":0.0027065163,"teacher_disagreement_score":0.008867423,"about_ca_system_score_codex":0.0010241235,"about_ca_system_score_gemma":0.0005335133,"threshold_uncertainty_score":0.029664457},"labels":[],"label_agreement":null},{"id":"W4411411471","doi":"10.1145/3744970.3727292","title":"Learning-Augmented Competitive Algorithms for Spatiotemporal Online Allocation with Deadline Constraints","year":2025,"lang":"en","type":"article","venue":"ACM SIGMETRICS Performance Evaluation Review","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Universitas Brawijaya","keywords":"Computer science; Online algorithm; Workload; Scheduling (production processes); Competitive analysis; Robustness (evolution); Metric (unit); Mathematical optimization; Algorithm; Upper and lower bounds","score_opus":0.07449504690266098,"score_gpt":0.37452110492905766,"score_spread":0.3000260580263967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411411471","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014790653,0.0010264461,0.9775639,0.00065489503,0.00014270697,0.00014456938,0.00016582645,0.00054159074,0.0049693906],"genre_scores_gemma":[0.52633035,0.0010064909,0.46417326,0.0007558277,0.00041480648,0.00060991856,0.0007937094,0.00028912904,0.0056266002],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99812955,0.000698924,0.000105116065,0.00041891332,0.0003692711,0.00027833402],"domain_scores_gemma":[0.99231297,0.0057333936,0.00053406716,0.00042339382,0.0006471334,0.00034894148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027776659,0.0019200039,0.003007883,0.001147654,0.0009840773,0.002235382,0.0038091417,0.0025344735,0.004212484],"category_scores_gemma":[0.011571886,0.0007239742,0.00086682756,0.0025911813,0.0014790525,0.002969502,0.0020645435,0.0026724443,0.0008442341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016461739,0.00023393659,0.00063433836,0.00017785658,0.00006733751,0.000048891765,0.000064792315,0.8981055,0.00042139963,0.027398098,0.0041994597,0.06848379],"study_design_scores_gemma":[0.000022268314,0.000036913694,0.00004361704,0.000006053787,0.00000500115,0.000011300799,0.000009606417,0.98800886,0.00010704582,0.011149172,0.0005958162,0.0000044416634],"about_ca_topic_score_codex":0.009854293,"about_ca_topic_score_gemma":0.007732479,"teacher_disagreement_score":0.009854293,"about_ca_system_score_codex":0.002157428,"about_ca_system_score_gemma":0.0035652712,"threshold_uncertainty_score":0.019593835},"labels":[],"label_agreement":null},{"id":"W4411488214","doi":"10.1016/j.jpdc.2025.105139","title":"Dispersion of mobile robots on directed anonymous graphs","year":2025,"lang":"en","type":"article","venue":"Journal of Parallel and Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Robot; Theoretical computer science; Artificial intelligence","score_opus":0.010369928098864294,"score_gpt":0.2679163254368854,"score_spread":0.25754639733802115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411488214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34911922,0.00017031586,0.64430684,0.00045885405,0.00003138316,0.00015693705,0.00024378109,0.0010785976,0.004434142],"genre_scores_gemma":[0.7885092,0.00016012636,0.20509033,0.0000759451,0.000021580663,0.0001304331,0.00041326467,0.00009184101,0.0055072536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939275,0.00014488473,0.00004091037,0.00017317363,0.00014276073,0.00010556675],"domain_scores_gemma":[0.99731547,0.0015452984,0.00036970113,0.0004163523,0.00021525314,0.0001378193],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047666987,0.0005225191,0.00053255836,0.0007044637,0.000874304,0.0008022494,0.001257903,0.00083954993,0.0012114858],"category_scores_gemma":[0.004716829,0.00046851582,0.00053887937,0.0007474056,0.00094653445,0.0015891258,0.0017383149,0.0007778132,0.00026712526],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036149664,0.000058639467,0.002249814,0.00013683402,0.000040796953,0.00034926698,0.00053222175,0.89166903,0.010796111,0.033877462,0.001705602,0.058222882],"study_design_scores_gemma":[0.000040934006,0.00006347031,0.00046829306,0.000012152988,0.0000121573,0.00011150853,0.00021157917,0.94228303,0.005413589,0.048899703,0.002468768,0.000014845799],"about_ca_topic_score_codex":0.0040277485,"about_ca_topic_score_gemma":0.004147413,"teacher_disagreement_score":0.0040277485,"about_ca_system_score_codex":0.0011355554,"about_ca_system_score_gemma":0.00077868346,"threshold_uncertainty_score":0.00823909},"labels":[],"label_agreement":null},{"id":"W4411547426","doi":"10.1007/s00446-025-00489-5","title":"Fast deterministic rendezvous in labeled lines","year":2025,"lang":"en","type":"article","venue":"Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Rendezvous; Computer science; Aerospace engineering; Engineering","score_opus":0.013014461166883933,"score_gpt":0.28455956800656634,"score_spread":0.2715451068396824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411547426","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11088586,0.00034701035,0.8748832,0.00046771645,0.00011699126,0.00013506935,0.00033480156,0.0031116891,0.009717724],"genre_scores_gemma":[0.6993688,0.00016583152,0.2857813,0.00016007792,0.000033713695,0.00017455718,0.0005002111,0.00061554566,0.013200088],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988256,0.00037347982,0.000046317873,0.00027268595,0.000250658,0.00023126163],"domain_scores_gemma":[0.99565566,0.0027430342,0.0002889064,0.0007303546,0.00036956256,0.00021244638],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010685847,0.0006913059,0.0012582139,0.00069827423,0.0016309167,0.0015422688,0.0017629109,0.0015012488,0.008309128],"category_scores_gemma":[0.0060680504,0.0007148723,0.0005314831,0.0013163277,0.0014950943,0.002559266,0.0023765867,0.0014428289,0.0014252382],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010810579,0.00015318194,0.0009275515,0.00018137226,0.00005447263,0.00022003235,0.0003499803,0.7709396,0.007270173,0.12180992,0.009011047,0.08800166],"study_design_scores_gemma":[0.00007243512,0.000046037603,0.00006942977,0.00001255207,0.0000061150863,0.000027037873,0.000048777274,0.96036404,0.0025607687,0.035045855,0.0017344784,0.000012450185],"about_ca_topic_score_codex":0.007361789,"about_ca_topic_score_gemma":0.00828956,"teacher_disagreement_score":0.008309128,"about_ca_system_score_codex":0.0013899032,"about_ca_system_score_gemma":0.0011825165,"threshold_uncertainty_score":0.027796805},"labels":[],"label_agreement":null},{"id":"W4412031854","doi":"10.1016/j.tcs.2025.115438","title":"Bike-assisted evacuation of robots on a line with asymmetric S/R communication","year":2025,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Line (geometry); Computer science; Human–computer interaction; Artificial intelligence; Mathematics","score_opus":0.021304030791348322,"score_gpt":0.30058114467350033,"score_spread":0.27927711388215204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412031854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.39733467,0.00030375476,0.58953834,0.0005408073,0.00006918888,0.00013963121,0.00014594829,0.0007034117,0.01122423],"genre_scores_gemma":[0.92722535,0.00012898241,0.066372596,0.00007307905,0.000017485729,0.00008640036,0.00018256587,0.00003271216,0.005880709],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99952245,0.00012600525,0.00001900043,0.000087064225,0.000076288925,0.00016930733],"domain_scores_gemma":[0.99885774,0.00052963063,0.00017384354,0.00014060888,0.00012075324,0.00017741437],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005206299,0.00084407843,0.0012379823,0.00048192294,0.00096788,0.00065124,0.0018614597,0.0015594043,0.0026264675],"category_scores_gemma":[0.0018754016,0.0002820849,0.00065812987,0.0005318234,0.0008942381,0.0012421049,0.0023893623,0.00088489975,0.00049816014],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008705377,0.00013620486,0.0011389077,0.00018434142,0.000051385217,0.00042088423,0.00024347786,0.94179887,0.011704582,0.016763322,0.0018360707,0.024851456],"study_design_scores_gemma":[0.000019558447,0.00007564045,0.00009812043,0.0000041351664,0.0000040861564,0.000055828048,0.000048081005,0.99592835,0.0012196491,0.0021982598,0.00034130766,0.000007062278],"about_ca_topic_score_codex":0.0039399574,"about_ca_topic_score_gemma":0.0036707504,"teacher_disagreement_score":0.0039399574,"about_ca_system_score_codex":0.00063518307,"about_ca_system_score_gemma":0.0008636589,"threshold_uncertainty_score":0.00878644},"labels":[],"label_agreement":null},{"id":"W4412198485","doi":"10.4171/aihpd/212","title":"Counting mobiles by integrable systems","year":2025,"lang":"en","type":"article","venue":"Annales de l’Institut Henri Poincaré D Combinatorics Physics and their Interactions","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Integrable system; Computer science; Mathematics; Mathematical physics","score_opus":0.01221853338093233,"score_gpt":0.2567638169124274,"score_spread":0.24454528353149507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412198485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.81355447,0.00082359614,0.16527225,0.000815597,0.000055067052,0.000057244622,0.000361992,0.0001847287,0.018875096],"genre_scores_gemma":[0.9754284,0.00039950127,0.01882412,0.000090551795,0.000114705326,0.00007556699,0.00032447954,0.00006890145,0.0046738824],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994653,0.00014341983,0.000030362517,0.000108301734,0.00014820509,0.00010437728],"domain_scores_gemma":[0.99787664,0.0012024802,0.000335582,0.00021416071,0.00020199803,0.00016921017],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006862166,0.000342169,0.00066090084,0.002491264,0.0007194648,0.002091999,0.0008833943,0.0011209117,0.00441306],"category_scores_gemma":[0.005615098,0.0003108866,0.0005061011,0.0010357561,0.0017797456,0.0034225674,0.0014290002,0.0008409795,0.00039742296],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000033369583,0.000028805029,0.0039531314,0.00009580355,0.000015226769,0.00017912223,0.00032629777,0.007789996,0.0032866856,0.9700298,0.0014001308,0.012861754],"study_design_scores_gemma":[0.000020207124,0.00003065117,0.001807793,0.000054050673,0.000018795958,0.0004252335,0.00021044465,0.121165946,0.002352857,0.87100166,0.002884193,0.000028265795],"about_ca_topic_score_codex":0.00056975335,"about_ca_topic_score_gemma":0.0005653134,"teacher_disagreement_score":0.00441306,"about_ca_system_score_codex":0.00086908956,"about_ca_system_score_gemma":0.00030149694,"threshold_uncertainty_score":0.014763176},"labels":[],"label_agreement":null},{"id":"W4412220241","doi":"10.4230/lipics.swat.2024.16","title":"On the Online Weighted Non-Crossing Matching Problem","year":2024,"lang":"en","type":"article","venue":"University of Southern Denmark Research Portal (University of Southern Denmark)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Concordia University; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Danmarks Frie Forskningsfond","keywords":"Matching (statistics); Computer science; Level crossing; Mathematics; Statistics; Geography; Archaeology","score_opus":0.02915519909427842,"score_gpt":0.2591531528757423,"score_spread":0.2299979537814639,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412220241","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09312005,0.0012969512,0.88282734,0.002374781,0.00022820245,0.00046671767,0.00090778695,0.0010774994,0.017700553],"genre_scores_gemma":[0.604607,0.0014643834,0.3773329,0.0010969504,0.00048164334,0.0006729075,0.0020465949,0.0005571507,0.011740452],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9942854,0.0022686312,0.00028263943,0.0015115591,0.00088905665,0.0007626339],"domain_scores_gemma":[0.9886354,0.007850014,0.0009919761,0.0014126737,0.000508956,0.0006008875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038101422,0.001879097,0.0031006462,0.0010341534,0.0013501561,0.0032730603,0.004253169,0.003223408,0.009509115],"category_scores_gemma":[0.01815307,0.0008658156,0.0012103359,0.0037438408,0.0021962675,0.008920941,0.0028686775,0.0036469295,0.0020448957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011753265,0.000807534,0.0014344212,0.00061131665,0.0001804846,0.00031658937,0.00025172174,0.6089913,0.0039563207,0.2602434,0.011287658,0.11074392],"study_design_scores_gemma":[0.00015799547,0.00018092999,0.0002963362,0.00002895056,0.000034868695,0.00018080304,0.000057551955,0.74322253,0.0011539727,0.25069994,0.0039539267,0.00003214676],"about_ca_topic_score_codex":0.0018906973,"about_ca_topic_score_gemma":0.001263457,"teacher_disagreement_score":0.009509115,"about_ca_system_score_codex":0.002066397,"about_ca_system_score_gemma":0.0020366334,"threshold_uncertainty_score":0.031811178},"labels":[],"label_agreement":null},{"id":"W4412375049","doi":"10.1109/tsipn.2025.3587399","title":"An ADMM-Based Approach to Quadratically-Regularized Distributed Optimal Transport on Graphs","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Signal and Information Processing over Networks","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Quadratic growth; Computer science; Mathematics; Regularization (linguistics); Mathematical optimization; Econometrics; Applied mathematics; Algorithm; Artificial intelligence","score_opus":0.008588321185572597,"score_gpt":0.2394253606992774,"score_spread":0.2308370395137048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412375049","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020837062,0.00005533659,0.9967326,0.00014720694,0.000024119774,0.000012477496,0.000016321657,0.00009467521,0.0008337273],"genre_scores_gemma":[0.3074977,0.00028941472,0.68377715,0.0002920785,0.00014138076,0.00019647053,0.0002564405,0.00022668118,0.0073226886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994962,0.00017638813,0.000025172358,0.00012395138,0.00013330269,0.00004491855],"domain_scores_gemma":[0.9989675,0.00052770984,0.0001140962,0.00011552163,0.00022151034,0.000053677075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013669254,0.0010129658,0.0011108138,0.0006151874,0.0005192514,0.0009935015,0.0016266451,0.0016963701,0.001882589],"category_scores_gemma":[0.0030292792,0.00058327377,0.0007996758,0.0010247007,0.0011647624,0.0014278338,0.0013218378,0.002333771,0.00042208238],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000020664706,0.000016106633,0.00007825808,0.00003290877,0.000014780476,0.000031616804,0.000023130002,0.96834666,0.0008319419,0.0155619215,0.0009990212,0.014042945],"study_design_scores_gemma":[0.0000032401044,0.0000073092187,0.000007935747,0.0000017689491,0.0000014461802,0.0000065782506,0.0000023265131,0.99582976,0.00012598626,0.0037198998,0.0002921005,0.0000016499415],"about_ca_topic_score_codex":0.0041947677,"about_ca_topic_score_gemma":0.003791423,"teacher_disagreement_score":0.0041947677,"about_ca_system_score_codex":0.0011390331,"about_ca_system_score_gemma":0.0017676945,"threshold_uncertainty_score":0.008340716},"labels":[],"label_agreement":null},{"id":"W4412398761","doi":"10.1109/icccs65393.2025.11069970","title":"Comparative Analysis of Shortest-Path Algorithms in Network Routing","year":2025,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of the Fraser Valley","funders":"","keywords":"Computer science; Shortest path problem; K shortest path routing; Routing (electronic design automation); Path (computing); Equal-cost multi-path routing; Routing algorithm; Link-state routing protocol; Algorithm; Routing protocol; Computer network; Theoretical computer science; Graph","score_opus":0.03011207326568078,"score_gpt":0.3251645753135578,"score_spread":0.29505250204787703,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412398761","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31182805,0.08140003,0.5154032,0.002355062,0.00086144666,0.0003016741,0.00082274945,0.0018031512,0.08522463],"genre_scores_gemma":[0.82655096,0.021317417,0.14501564,0.00012509881,0.00032147084,0.00013765281,0.001384453,0.00034247033,0.0048048855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99556303,0.0016055906,0.00021123754,0.00025190707,0.0021411395,0.0002271571],"domain_scores_gemma":[0.9860167,0.01054791,0.00032651649,0.0005147344,0.002442963,0.0001511267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046312497,0.0009080293,0.00089828897,0.004174764,0.00072212174,0.0013743404,0.0009527263,0.0009435077,0.0031661475],"category_scores_gemma":[0.01842631,0.00023117846,0.0005764398,0.0056512817,0.00056641473,0.0035400635,0.0006375803,0.00062608765,0.0004546898],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000641391,0.0002469198,0.0046271845,0.00076837844,0.00023983425,0.00012574285,0.00014878869,0.5423665,0.001580687,0.082773164,0.0068695946,0.3596118],"study_design_scores_gemma":[0.000042548887,0.00033798366,0.0037527909,0.000102595695,0.00010391798,0.00029962976,0.00019674575,0.942997,0.0027733785,0.03516876,0.014187882,0.00003684899],"about_ca_topic_score_codex":0.0024074672,"about_ca_topic_score_gemma":0.002135646,"teacher_disagreement_score":0.0046312497,"about_ca_system_score_codex":0.00197078,"about_ca_system_score_gemma":0.0010160296,"threshold_uncertainty_score":0.024492681},"labels":[],"label_agreement":null},{"id":"W4412508555","doi":"10.1609/socs.v18i1.35996","title":"Reevaluation of Large Neighborhood Search for MAPF: Findings and Opportunities","year":2025,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo; Simon Fraser University","funders":"","keywords":"Psychology; Sociology","score_opus":0.03636055977328928,"score_gpt":0.3097754427812473,"score_spread":0.273414883007958,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412508555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08713965,0.02119346,0.8635433,0.0034922073,0.00078140944,0.00036255072,0.00040852613,0.0031956797,0.019883253],"genre_scores_gemma":[0.49092892,0.00541151,0.49818167,0.00071511196,0.00029334566,0.00026168098,0.00074455887,0.0007416851,0.0027215853],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99673116,0.0013357968,0.000120585355,0.00048744917,0.0010961437,0.00022892925],"domain_scores_gemma":[0.98665035,0.009490016,0.00039519713,0.0015746556,0.0015003482,0.00038937232],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005087178,0.00095257786,0.0017220309,0.001140489,0.00088836346,0.002103368,0.003562089,0.0020065,0.0029287084],"category_scores_gemma":[0.029619345,0.0004572684,0.00095687853,0.0012220767,0.0013873818,0.0037720846,0.0018824922,0.002551995,0.0007246089],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00034630732,0.0004964211,0.005388392,0.0009959551,0.00020008345,0.00016553723,0.00031167988,0.46713263,0.0016557552,0.067342706,0.012283354,0.44368124],"study_design_scores_gemma":[0.00005635554,0.00019098901,0.00048237736,0.00015680675,0.000041220213,0.0001177965,0.00013689103,0.97042894,0.0010900751,0.019416995,0.007859536,0.000022063023],"about_ca_topic_score_codex":0.01117084,"about_ca_topic_score_gemma":0.010953588,"teacher_disagreement_score":0.01117084,"about_ca_system_score_codex":0.0016536099,"about_ca_system_score_gemma":0.0031808866,"threshold_uncertainty_score":0.026903927},"labels":[],"label_agreement":null},{"id":"W4412742899","doi":"10.1109/rait65068.2025.11089067","title":"Convex Hull and Incremental Insertion for a TSP Solution","year":2025,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Future Earth","funders":"","keywords":"Convex hull; Regular polygon; Hull; Computer science; Mathematical optimization; Mathematics; Materials science; Geometry; Composite material","score_opus":0.019062847512279234,"score_gpt":0.28713866223568063,"score_spread":0.2680758147234014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412742899","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017732829,0.00030657704,0.9619361,0.0003198497,0.00009629492,0.00017310042,0.00009926604,0.0009568611,0.018379051],"genre_scores_gemma":[0.23097391,0.00060448307,0.75094783,0.00017727488,0.00007367532,0.00026547245,0.0005690142,0.00037260485,0.016015733],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994005,0.00009678015,0.000019744817,0.00011345682,0.0002806094,0.000088947694],"domain_scores_gemma":[0.9994855,0.00021687087,0.000058860798,0.000081818536,0.0001200987,0.00003686205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004319732,0.00086746586,0.0007127268,0.0012096737,0.0009801615,0.0011484207,0.0016222254,0.0008960595,0.010622552],"category_scores_gemma":[0.0018394574,0.0004713399,0.0011353408,0.0014296379,0.0009365776,0.0022100064,0.001313264,0.0017490042,0.0020596716],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024139047,0.00032608295,0.000602907,0.00043869505,0.000052597716,0.00044037003,0.0004835806,0.40989098,0.012832726,0.23012154,0.013758963,0.3308101],"study_design_scores_gemma":[0.000028109056,0.00015809074,0.0001770372,0.00003102035,0.000027295073,0.00021252185,0.000098074794,0.9277216,0.005866305,0.051517908,0.014139495,0.000022640672],"about_ca_topic_score_codex":0.004068362,"about_ca_topic_score_gemma":0.0036138939,"teacher_disagreement_score":0.010622552,"about_ca_system_score_codex":0.0011189086,"about_ca_system_score_gemma":0.0014598644,"threshold_uncertainty_score":0.03553599},"labels":[],"label_agreement":null},{"id":"W4412791354","doi":"10.1016/j.jcss.2025.103696","title":"Exploring wedges of an oriented grid by an automaton with pebbles","year":2025,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Grid; Automaton; Computer science; Cellular automaton; Theoretical computer science; Mathematics; Algorithm; Geometry","score_opus":0.042991125658790104,"score_gpt":0.2750190246847915,"score_spread":0.2320278990260014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412791354","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.50033563,0.00019933571,0.48310655,0.00026626233,0.00011386568,0.00008383639,0.00019073041,0.00079677004,0.014906962],"genre_scores_gemma":[0.8906692,0.00009783383,0.10603583,0.00005880757,0.000009330238,0.000080326776,0.000153572,0.00011164431,0.0027834259],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998271,0.000047884598,0.000011752353,0.00005134162,0.00002950194,0.000032313812],"domain_scores_gemma":[0.99926215,0.00040468219,0.000052983472,0.000109105975,0.000056993922,0.000114136055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025692486,0.00038981935,0.0007736211,0.00045757776,0.00079609663,0.000910138,0.0011103082,0.00085885107,0.005910626],"category_scores_gemma":[0.0015290973,0.00056807155,0.0006720655,0.0004671105,0.0010198564,0.0013504911,0.002157697,0.0007325631,0.00055254815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005017586,0.00014542001,0.0029085486,0.00012597542,0.00004977383,0.0006406317,0.00035901775,0.8967018,0.011210626,0.057274703,0.0012879696,0.028793816],"study_design_scores_gemma":[0.000033241533,0.000065034365,0.00012417835,0.0000147458895,0.00000890403,0.000036006615,0.00007483604,0.9765797,0.00086400507,0.021418469,0.0007704727,0.000010449294],"about_ca_topic_score_codex":0.0034207627,"about_ca_topic_score_gemma":0.0033378606,"teacher_disagreement_score":0.005910626,"about_ca_system_score_codex":0.00040922497,"about_ca_system_score_gemma":0.00055496977,"threshold_uncertainty_score":0.019773066},"labels":[],"label_agreement":null},{"id":"W4412791763","doi":"10.1016/j.jcss.2025.103695","title":"Triangle evacuation of 2 agents in the wireless model &amp; the power of choosing a starting point","year":2025,"lang":"en","type":"article","venue":"Journal of Computer and System Sciences","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wireless; Computer science; Point (geometry); Power (physics); Power point; Mathematical economics; Mathematics; Telecommunications; Physics","score_opus":0.06209018673215274,"score_gpt":0.32834209363200356,"score_spread":0.26625190689985084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412791763","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11667328,0.0007436573,0.8449037,0.002079818,0.00014993215,0.00025592957,0.0005081803,0.00018228711,0.034503184],"genre_scores_gemma":[0.8023467,0.0009969955,0.16677265,0.00034158494,0.000120696,0.00035783628,0.0004935777,0.00013137962,0.028438462],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988544,0.0004734216,0.000039539278,0.00022815078,0.00015576406,0.00024878592],"domain_scores_gemma":[0.9971879,0.001920553,0.0002979515,0.00022923278,0.00011952542,0.00024494078],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012453598,0.0008719787,0.0011447639,0.00046643303,0.0010331456,0.001726805,0.0020753765,0.002228975,0.007841274],"category_scores_gemma":[0.0065202075,0.00056783337,0.0015165536,0.0009877924,0.0019518695,0.003309043,0.0030978792,0.002291615,0.00073063874],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028507411,0.000057956608,0.00045515507,0.00010251557,0.000027083579,0.0002596957,0.00017640984,0.835323,0.00076987786,0.15311238,0.0021528543,0.0072781],"study_design_scores_gemma":[0.000039623876,0.000058448753,0.00007872104,0.000013481023,0.00000972707,0.000063689105,0.00007592327,0.94997025,0.0002458514,0.047683626,0.001751403,0.000009199574],"about_ca_topic_score_codex":0.007843938,"about_ca_topic_score_gemma":0.007507056,"teacher_disagreement_score":0.007843938,"about_ca_system_score_codex":0.001488746,"about_ca_system_score_gemma":0.0010921208,"threshold_uncertainty_score":0.026231647},"labels":[],"label_agreement":null},{"id":"W4412965319","doi":"10.15803/ijnc.15.2_199","title":"Asynchronous Separation of Unconscious Colored Robots","year":2025,"lang":"en","type":"article","venue":"International Journal of Networking and Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Computer science; Colored; Asynchronous communication; Unconscious mind; Separation (statistics); Robot; Artificial intelligence; Machine learning; Computer network; Psychology","score_opus":0.010477545434982735,"score_gpt":0.3124047701585097,"score_spread":0.30192722472352695,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412965319","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.063939944,0.00010413608,0.9277775,0.00044378906,0.00009724098,0.00007141711,0.0000700905,0.00023761249,0.0072582955],"genre_scores_gemma":[0.86947477,0.00015396286,0.11905835,0.0001885644,0.00008407657,0.00013636502,0.00010224027,0.000071873714,0.010729745],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867505,0.00039109026,0.00004745427,0.00035778264,0.00026988634,0.00025870302],"domain_scores_gemma":[0.997889,0.00074651046,0.0003233539,0.0005410538,0.00023715784,0.00026289112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096649874,0.00074888277,0.00068292517,0.00027165172,0.0009145466,0.0014004096,0.002069363,0.00086881756,0.0036298023],"category_scores_gemma":[0.003009967,0.00034937297,0.00067301316,0.00048180882,0.0019329304,0.0030578761,0.002872782,0.0018670034,0.0005604166],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005578873,0.00012366069,0.00091133465,0.000106706626,0.00004481829,0.0005830651,0.00050755934,0.3632957,0.011677981,0.6043306,0.001811849,0.016048843],"study_design_scores_gemma":[0.00009038052,0.00010710203,0.00012386832,0.000006763422,0.000018350258,0.00007531042,0.000072823845,0.859959,0.0031770936,0.13265763,0.0036913182,0.000020321415],"about_ca_topic_score_codex":0.0017686657,"about_ca_topic_score_gemma":0.0016176284,"teacher_disagreement_score":0.0036298023,"about_ca_system_score_codex":0.0011143761,"about_ca_system_score_gemma":0.0012255424,"threshold_uncertainty_score":0.012142897},"labels":[],"label_agreement":null},{"id":"W4413325089","doi":"10.1016/j.econmod.2025.107260","title":"Searching for robots","year":2025,"lang":"en","type":"article","venue":"Economic Modelling","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"","keywords":"Economics; Robot; Keynesian economics; Mathematical economics; Econometrics; Computer science; Artificial intelligence","score_opus":0.03561935950339513,"score_gpt":0.29380893291628035,"score_spread":0.25818957341288523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413325089","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061642703,0.0040944368,0.76161647,0.004979017,0.00038719107,0.00011037681,0.00030692143,0.00035803413,0.16650493],"genre_scores_gemma":[0.7230833,0.0032324253,0.19729462,0.00041805205,0.00019698036,0.00017897505,0.00034064314,0.00014209669,0.07511293],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996966,0.00011478793,0.00001003509,0.00007693764,0.00007273994,0.000029032955],"domain_scores_gemma":[0.99955195,0.00027191368,0.000046604477,0.000060628132,0.000037946735,0.000031049534],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037953016,0.00047829497,0.00067083974,0.0005273829,0.00067767134,0.0015799792,0.00089142274,0.0016591318,0.01500413],"category_scores_gemma":[0.0031014553,0.00035750942,0.0006255565,0.00079303014,0.0013365448,0.0020740496,0.0011603516,0.0010433367,0.0015259811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009074253,0.00005200861,0.00071827654,0.0003036886,0.000054865177,0.0001351959,0.00015820903,0.26714805,0.001741225,0.6515179,0.008277458,0.06980234],"study_design_scores_gemma":[0.000028937216,0.00006403822,0.000343511,0.000070740076,0.000022422448,0.00016892739,0.00016652163,0.48758253,0.00085359794,0.48511663,0.025563462,0.000018643103],"about_ca_topic_score_codex":0.0013887931,"about_ca_topic_score_gemma":0.0013299563,"teacher_disagreement_score":0.01500413,"about_ca_system_score_codex":0.000654808,"about_ca_system_score_gemma":0.0006209932,"threshold_uncertainty_score":0.050193787},"labels":[],"label_agreement":null},{"id":"W4413374224","doi":"10.1007/978-3-031-99872-0_2","title":"Cache Management for Mixture-of-Experts LLMs","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Institute for International Peace and Security","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Cache; Parallel computing","score_opus":0.019212463666271575,"score_gpt":0.2709219489793063,"score_spread":0.2517094853130348,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413374224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12917174,0.0031896357,0.8276345,0.0013603176,0.00053545897,0.00023324328,0.0010029831,0.021092916,0.015779179],"genre_scores_gemma":[0.8249893,0.00051807234,0.15408926,0.00042399202,0.00025937546,0.00017318697,0.0011463577,0.00089877576,0.017501615],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99876225,0.00027765016,0.000109327644,0.00019187051,0.0003191424,0.000339912],"domain_scores_gemma":[0.99506855,0.001732713,0.00019954894,0.0016270014,0.0009783758,0.00039387896],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017666279,0.0007103064,0.0014833029,0.0011094877,0.0014154771,0.0023215064,0.0030836498,0.0013686807,0.01331764],"category_scores_gemma":[0.009305343,0.0004886229,0.0006883059,0.0013523033,0.00055463717,0.0034392232,0.0029341704,0.0013659032,0.0026172814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003130644,0.00069921033,0.005778182,0.0005740736,0.0002732326,0.0010170287,0.0007710302,0.26001024,0.0155529,0.051590048,0.0819409,0.5786625],"study_design_scores_gemma":[0.00008643557,0.0001702367,0.00036992543,0.00005111706,0.000068416404,0.0002598388,0.0001577924,0.956741,0.005286621,0.025970627,0.010804013,0.000034021665],"about_ca_topic_score_codex":0.0048819575,"about_ca_topic_score_gemma":0.01072808,"teacher_disagreement_score":0.01331764,"about_ca_system_score_codex":0.0015418291,"about_ca_system_score_gemma":0.0022396382,"threshold_uncertainty_score":0.04455197},"labels":[],"label_agreement":null},{"id":"W4413857336","doi":"10.1007/978-3-032-03639-1_21","title":"Near-Linear MIR Algorithms for Stochastically-Ordered Priors","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Prior probability; Algorithm; Artificial intelligence; Bayesian probability","score_opus":0.02605732205500774,"score_gpt":0.29284712628223464,"score_spread":0.2667898042272269,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413857336","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015507807,0.0002479,0.99483055,0.0001573218,0.000053843527,0.000031078107,0.00006435837,0.0007836148,0.002280532],"genre_scores_gemma":[0.058972944,0.00038117578,0.9276478,0.0004459442,0.00019945846,0.00038035144,0.0006691834,0.0009638776,0.0103393365],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969137,0.0014805775,0.00014509486,0.00046804093,0.0007184311,0.00027414665],"domain_scores_gemma":[0.98919684,0.008125696,0.00036558748,0.0011183297,0.0008700013,0.00032352612],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048153754,0.0018259212,0.0026016792,0.0016866407,0.0013823181,0.003063398,0.0039958064,0.003316575,0.017912412],"category_scores_gemma":[0.020607833,0.0020905223,0.0020985473,0.0022293567,0.0021888085,0.0057322467,0.0066925692,0.005488262,0.0071033165],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0007305891,0.00029223604,0.00068200886,0.00046558533,0.00017776915,0.00016294513,0.0002814446,0.37162971,0.0035049987,0.2783772,0.020885035,0.32281044],"study_design_scores_gemma":[0.000041492665,0.000045591994,0.00006314116,0.000033782268,0.000017133234,0.00005144999,0.000029180379,0.90165395,0.0009025145,0.094154015,0.0029874707,0.000020276],"about_ca_topic_score_codex":0.0022828488,"about_ca_topic_score_gemma":0.004022639,"teacher_disagreement_score":0.017912412,"about_ca_system_score_codex":0.0016698168,"about_ca_system_score_gemma":0.002523728,"threshold_uncertainty_score":0.059922993},"labels":[],"label_agreement":null},{"id":"W4414646315","doi":"10.1007/978-3-032-06706-7_14","title":"Online Algorithm for Fractional Matchings with Edge Arrivals in Graphs of Maximum Degree Three","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; University of Waterloo","funders":"","keywords":"Competitive analysis; Bipartite graph; Vertex (graph theory); Hopcroft–Karp algorithm; Degree (music); Cardinality (data modeling); Online algorithm; Graph","score_opus":0.028306919491313427,"score_gpt":0.2735100315596817,"score_spread":0.24520311206836826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414646315","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07075316,0.0003847892,0.9101089,0.0008199654,0.00023689937,0.00035931804,0.00051112665,0.0036608488,0.013164893],"genre_scores_gemma":[0.3178569,0.00016968035,0.67089707,0.00024910804,0.00011017392,0.00036496896,0.0008684275,0.00039894498,0.009084714],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99882907,0.00021014015,0.00007276017,0.00032302362,0.00020925043,0.00035586077],"domain_scores_gemma":[0.99646497,0.0020546485,0.00025157805,0.0006953338,0.0002645855,0.00026883418],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016046704,0.0010465767,0.00213194,0.0011716131,0.0017998487,0.002712531,0.0043954425,0.0027803446,0.015929727],"category_scores_gemma":[0.0063931774,0.0007659606,0.001314113,0.002164188,0.0009957283,0.004887638,0.003027288,0.002031511,0.0022631914],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0024865824,0.0013801403,0.0014285452,0.00065785844,0.00014497808,0.00023388033,0.00048149028,0.29457366,0.009851028,0.107743524,0.023016404,0.55800194],"study_design_scores_gemma":[0.0002513591,0.00016239799,0.00019630099,0.00003525718,0.000040183982,0.0001003452,0.00011939836,0.9071576,0.0024844501,0.086363494,0.0030678762,0.000021257558],"about_ca_topic_score_codex":0.0034060131,"about_ca_topic_score_gemma":0.0040153074,"teacher_disagreement_score":0.015929727,"about_ca_system_score_codex":0.0021518858,"about_ca_system_score_gemma":0.0032564974,"threshold_uncertainty_score":0.053290248},"labels":[],"label_agreement":null},{"id":"W4414942510","doi":"10.1146/annurev-control-022624-033840","title":"On Operator Theory and Applications in Game Theory","year":2025,"lang":"en","type":"article","venue":"Annual Review of Control Robotics and Autonomous Systems","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Game theory; Focus (optics); Convergence (economics); Operator (biology); Algorithmic game theory; Symbolic convergence theory","score_opus":0.005322821630489083,"score_gpt":0.264844566113749,"score_spread":0.25952174448325993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414942510","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003482433,0.04077258,0.8630535,0.0046547977,0.001071061,0.000057860932,0.000105573105,0.00014022987,0.08666201],"genre_scores_gemma":[0.31089544,0.121920295,0.50678045,0.0063293893,0.01075911,0.0007567348,0.0003678871,0.0004656571,0.041725054],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99803156,0.0008888996,0.00012957443,0.0002425125,0.0005687449,0.00013871392],"domain_scores_gemma":[0.9968501,0.0025514767,0.00012345932,0.00014675553,0.00022389289,0.00010439368],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029445735,0.0014434267,0.0012578616,0.0024191928,0.0013776965,0.0026937143,0.0013408784,0.0020914853,0.006573242],"category_scores_gemma":[0.0042915936,0.00051998073,0.0018181899,0.0032641804,0.008064726,0.0055261585,0.0025871757,0.0059845354,0.0016986981],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000038693556,0.000009597172,0.00003892115,0.00010559091,0.000009188268,0.000032748743,0.00009545841,0.0024059864,0.00020437478,0.986185,0.0015466342,0.009362629],"study_design_scores_gemma":[0.0000027162641,0.000010998101,0.000035332305,0.000049667986,0.000002871577,0.000043282616,0.000020922422,0.0046767322,0.000076303884,0.9825058,0.012567505,0.000007755491],"about_ca_topic_score_codex":0.0015043082,"about_ca_topic_score_gemma":0.000978454,"teacher_disagreement_score":0.006573242,"about_ca_system_score_codex":0.0018181034,"about_ca_system_score_gemma":0.001131917,"threshold_uncertainty_score":0.021989644},"labels":[],"label_agreement":null},{"id":"W4415100966","doi":"10.48550/arxiv.2503.08833","title":"Randomization in Optimal Execution Games","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Nash equilibrium; Uniqueness; Simple (philosophy); Kernel (algebra); Backward induction; Best response; Regular polygon; Sample (material)","score_opus":0.036252964613442726,"score_gpt":0.29393324101778445,"score_spread":0.2576802764043417,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415100966","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25718686,0.0006274412,0.72373354,0.0014016986,0.00007482569,0.00016145849,0.00013462667,0.00027628455,0.016403278],"genre_scores_gemma":[0.96541923,0.0002967255,0.029079327,0.00013565976,0.000049994796,0.00012313279,0.00006231098,0.000048995375,0.004784568],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9982326,0.0009011431,0.000082819846,0.00027949433,0.00025143952,0.0002524484],"domain_scores_gemma":[0.994743,0.003628439,0.0008345481,0.00030245972,0.00020899647,0.00028262392],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020590895,0.00083534064,0.0010605677,0.00047242732,0.00052571535,0.0015941232,0.0011087989,0.0013330043,0.0034574675],"category_scores_gemma":[0.01201482,0.00043026233,0.00061552174,0.00054227543,0.002248229,0.003174052,0.0013003814,0.0016007996,0.00028910217],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002813031,0.00015520815,0.0010767604,0.00010801972,0.00006066781,0.00022983279,0.00009963283,0.47312018,0.0030286948,0.5105431,0.0008564403,0.010440198],"study_design_scores_gemma":[0.000054343996,0.00008559513,0.00021513893,0.00001069708,0.0000117022955,0.000035115474,0.000025837595,0.80498356,0.0006021884,0.19331592,0.0006452137,0.000014724597],"about_ca_topic_score_codex":0.0016654887,"about_ca_topic_score_gemma":0.0010429656,"teacher_disagreement_score":0.0034574675,"about_ca_system_score_codex":0.0014391718,"about_ca_system_score_gemma":0.0011566151,"threshold_uncertainty_score":0.011566341},"labels":[],"label_agreement":null},{"id":"W4416063924","doi":"10.4230/lipics.stacs.2026.44","title":"Optimal Average Disk-Inspection via Fermat's Principle","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Optimal control; Discretization; Limit (mathematics); Trajectory; Heuristic; Limiting; Unit disk; Upper and lower bounds","score_opus":0.03729664457265921,"score_gpt":0.3010501199671265,"score_spread":0.2637534753944673,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416063924","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11091672,0.00055814395,0.8697442,0.00093121454,0.000060570095,0.00005249989,0.000099126504,0.00024192389,0.017395606],"genre_scores_gemma":[0.84657747,0.0004019869,0.14587553,0.00017912351,0.000043063133,0.00012121087,0.00012903752,0.00023612578,0.0064364327],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994442,0.00013261232,0.000022777476,0.000110271074,0.00019078607,0.00009937528],"domain_scores_gemma":[0.9982632,0.0011971086,0.00017820945,0.0001713294,0.0001171317,0.000073076844],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014314068,0.00047423906,0.0007867328,0.0005472607,0.0006594939,0.00097554235,0.0012300009,0.0011791324,0.0033705363],"category_scores_gemma":[0.0070341015,0.00039427367,0.00082815334,0.0004186512,0.0016018136,0.002220845,0.0010356106,0.0014198411,0.0003345818],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011391524,0.00006108059,0.00075438595,0.00009836678,0.000017465152,0.00009207523,0.00011665102,0.50985765,0.0036230008,0.4601324,0.0022068424,0.022926208],"study_design_scores_gemma":[0.000012821038,0.000037043184,0.00017576828,0.000014703724,0.000004910451,0.000031374944,0.000019402809,0.8528441,0.0008287975,0.14518146,0.00083837885,0.000011175319],"about_ca_topic_score_codex":0.002557903,"about_ca_topic_score_gemma":0.001663381,"teacher_disagreement_score":0.0033705363,"about_ca_system_score_codex":0.0020370376,"about_ca_system_score_gemma":0.0011966377,"threshold_uncertainty_score":0.014779806},"labels":[],"label_agreement":null},{"id":"W4416288730","doi":"10.1007/978-3-032-11127-2_18","title":"On the Computational Power of Mobile Robots Under Sequential Schedulers","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Robot; Mobile robot; Computational complexity theory; Scheduling (production processes); Sequence (biology); Permutation (music); Base (topology)","score_opus":0.022083914878658746,"score_gpt":0.27467391144287007,"score_spread":0.2525899965642113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416288730","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35448745,0.0050316383,0.56271076,0.0050677033,0.00066736067,0.00014929834,0.0004922105,0.0008245034,0.07056911],"genre_scores_gemma":[0.9575483,0.0012517609,0.030635944,0.00025364963,0.0003113562,0.00010753361,0.00011983697,0.00021946483,0.009552028],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987663,0.00041723307,0.00004530199,0.00016562262,0.00029336842,0.00031223512],"domain_scores_gemma":[0.98843914,0.0097853225,0.00035853006,0.0006743294,0.0004003405,0.00034233532],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020899673,0.0010006707,0.0015439307,0.0007683768,0.0008714799,0.002085598,0.0021154496,0.00086860155,0.0104880715],"category_scores_gemma":[0.015212169,0.0006308029,0.00053355016,0.0016388999,0.002260713,0.0036999441,0.0021555359,0.0012975347,0.0005401485],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011624129,0.00010539978,0.0008635881,0.00026239222,0.00006011928,0.00013879746,0.00016893866,0.78547305,0.004181563,0.15966149,0.0049246824,0.042997576],"study_design_scores_gemma":[0.000041159437,0.00006886463,0.0003083798,0.000017342833,0.000016466938,0.000031078078,0.00005236088,0.9012283,0.00061886327,0.096786015,0.0008211835,0.000009995718],"about_ca_topic_score_codex":0.002623918,"about_ca_topic_score_gemma":0.0026243974,"teacher_disagreement_score":0.0104880715,"about_ca_system_score_codex":0.0014301909,"about_ca_system_score_gemma":0.0015579426,"threshold_uncertainty_score":0.035086095},"labels":[],"label_agreement":null},{"id":"W4416309400","doi":"10.1007/978-3-032-09120-8_11","title":"Linear Search for Capturing an Oblivious Mobile Target in the Sender/Receiver Model","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Communication source; Mobile robot; Competitive analysis; Motion (physics); Search and rescue; Search algorithm","score_opus":0.0357485961633655,"score_gpt":0.2959106557265032,"score_spread":0.2601620595631377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416309400","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015383197,0.0003294285,0.9708865,0.00069857197,0.000050837898,0.00004579071,0.00010819798,0.00029658532,0.012200874],"genre_scores_gemma":[0.76734793,0.0008682879,0.18224098,0.0005506178,0.00022177701,0.00039379715,0.00023761568,0.0003565609,0.047782406],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99909914,0.00041451762,0.000023646684,0.00012847956,0.0001545168,0.00017967324],"domain_scores_gemma":[0.9982229,0.0012609256,0.00013874554,0.00017165612,0.00012135047,0.00008435808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013036168,0.0009508845,0.0014576557,0.00053360435,0.00069374294,0.0019293976,0.001983472,0.0024090698,0.008426091],"category_scores_gemma":[0.0046319026,0.000814054,0.0007824755,0.0009792177,0.0018100732,0.003983282,0.00255494,0.0029081255,0.0021294563],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019323194,0.000051901392,0.00020690213,0.00013692296,0.000034563167,0.00010570016,0.00014624382,0.44770014,0.0018550329,0.532236,0.0035108111,0.013822519],"study_design_scores_gemma":[0.000018240366,0.000028217786,0.00003313482,0.000011595763,0.000008772981,0.000028512262,0.000024882263,0.8703869,0.0003636454,0.12840109,0.0006824239,0.0000126064],"about_ca_topic_score_codex":0.0025172266,"about_ca_topic_score_gemma":0.0022550453,"teacher_disagreement_score":0.008426091,"about_ca_system_score_codex":0.0017532554,"about_ca_system_score_gemma":0.0014654079,"threshold_uncertainty_score":0.02818811},"labels":[],"label_agreement":null},{"id":"W4416339503","doi":"10.48550/arxiv.2511.10792","title":"$\\rm{A}^{\\rm{SAR}}$: $\\varepsilon$-Optimal Graph Search for Minimum Expected-Detection-Time Paths with Path Budget Constraints for Search and Rescue (SAR)","year":2025,"lang":"","type":"preprint","venue":"ArXiv.org","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Incremental heuristic search; Beam search; Probabilistic logic; Search algorithm; Best-first search; Search and rescue; Heuristic; Path (computing); Graph; Local search (optimization)","score_opus":0.04008118726032491,"score_gpt":0.29253745974341944,"score_spread":0.25245627248309455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416339503","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022141669,0.00031541803,0.9540588,0.0009100961,0.00011899421,0.0002285579,0.00031099707,0.0013223132,0.0205931],"genre_scores_gemma":[0.30280215,0.00036160613,0.68205005,0.00050200283,0.00005823509,0.0006966004,0.00082733243,0.00091708323,0.011785058],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994531,0.00021038597,0.000021907568,0.00011373906,0.00011372431,0.00008709605],"domain_scores_gemma":[0.9986021,0.0010599061,0.00009408287,0.00007086721,0.0001153748,0.000057791447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009305842,0.001507651,0.0009218512,0.0010496586,0.0006130987,0.0011781473,0.0011102806,0.0016244944,0.009251941],"category_scores_gemma":[0.004039405,0.00067500415,0.000832104,0.0007902989,0.0012411665,0.001164985,0.0015751633,0.0017356434,0.0014877518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017483461,0.000117378964,0.0006707691,0.00015828513,0.000039797447,0.00007337316,0.00009255822,0.8422663,0.0016756158,0.05197796,0.011331915,0.09142125],"study_design_scores_gemma":[0.00002855699,0.000041372085,0.000087735934,0.000022940802,0.0000062075915,0.000019743757,0.00001667908,0.9779489,0.00063562795,0.019165896,0.0020185139,0.00000787131],"about_ca_topic_score_codex":0.008476126,"about_ca_topic_score_gemma":0.01004937,"teacher_disagreement_score":0.009251941,"about_ca_system_score_codex":0.001830461,"about_ca_system_score_gemma":0.002392012,"threshold_uncertainty_score":0.030950844},"labels":[],"label_agreement":null},{"id":"W4417507764","doi":"10.1080/00207721.2025.2602076","title":"Approximate message passing algorithm for decentralised task assignment and scheduling","year":2025,"lang":"en","type":"article","venue":"International Journal of Systems Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Kootenay Association for Science & Technology","funders":"Ministry of Science and ICT, South Korea; Gyeonggi-do Regional Research Center; National Research Foundation of Korea","keywords":"Scheduling (production processes); Message passing; Task (project management); Job shop scheduling; Fair-share scheduling; Rate-monotonic scheduling","score_opus":0.01732953082634017,"score_gpt":0.3076323307883267,"score_spread":0.29030279996198655,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417507764","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004254182,0.00008785466,0.99440527,0.000058288988,0.000021686592,0.00003138963,0.000015569285,0.00033945806,0.00078633876],"genre_scores_gemma":[0.36741462,0.00026853292,0.62756026,0.00010104434,0.00006299646,0.00037518403,0.00019753074,0.00012396999,0.0038959407],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991067,0.00030408512,0.000051385374,0.00016036328,0.00024166862,0.00013583273],"domain_scores_gemma":[0.999047,0.00038378398,0.00014215862,0.00018916496,0.00017116428,0.000066700944],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014389305,0.0008941001,0.0012671008,0.000768152,0.00081786653,0.0009049187,0.0016939451,0.0008054099,0.002467793],"category_scores_gemma":[0.002916593,0.00041755053,0.0006661031,0.0010649008,0.00071222405,0.001342142,0.0011442755,0.0013217491,0.00062930794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00014511718,0.00004688518,0.00037684457,0.000073404255,0.000041040337,0.000044671557,0.0001208232,0.89628553,0.002404454,0.020994829,0.0017323447,0.07773395],"study_design_scores_gemma":[0.000022170963,0.000032720534,0.00006105863,0.0000034543243,0.000007418372,0.00001760455,0.000009960648,0.9911656,0.0005923584,0.006748276,0.0013343288,0.0000050773633],"about_ca_topic_score_codex":0.005609571,"about_ca_topic_score_gemma":0.005125095,"teacher_disagreement_score":0.005609571,"about_ca_system_score_codex":0.0009989472,"about_ca_system_score_gemma":0.0018953065,"threshold_uncertainty_score":0.011153817},"labels":[],"label_agreement":null},{"id":"W54874128","doi":"10.1007/978-3-642-35476-2_9","title":"Tree Exploration by a Swarm of Mobile Agents","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Swarm behaviour; Overhead (engineering); Tree (set theory); Node (physics); Computer science; Range (aeronautics); Mathematical optimization; K-ary tree; Algorithm; Path (computing); Tree structure; Topology (electrical circuits); Mathematics; Combinatorics; Artificial intelligence; Computer network; Binary tree; Engineering","score_opus":0.034696201713548855,"score_gpt":0.2732626250365877,"score_spread":0.23856642332303885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W54874128","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31002462,0.0010562968,0.67457867,0.00068504707,0.00017826962,0.00008358133,0.00008524244,0.00043550762,0.012872802],"genre_scores_gemma":[0.87161964,0.0004146455,0.118336,0.000109850014,0.000073144554,0.000103657716,0.000104959254,0.00007466115,0.009163422],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998635,0.00003944741,0.0000068316717,0.000030810457,0.00003340389,0.000026080803],"domain_scores_gemma":[0.9994178,0.00033849687,0.000050720133,0.00004918998,0.0000601319,0.000083674895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003748569,0.00037323232,0.00083891896,0.0005000031,0.0006945139,0.00094274036,0.0009376201,0.0013952139,0.0023530067],"category_scores_gemma":[0.0015413131,0.00038471707,0.00061690656,0.00066745724,0.0006269938,0.001269761,0.0011226882,0.0006046993,0.00035543254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043060828,0.0001196444,0.0019923842,0.0001888036,0.00015546966,0.00051985774,0.0005332713,0.86619765,0.01991051,0.035214074,0.0030708706,0.07166693],"study_design_scores_gemma":[0.000029947014,0.000078218254,0.00015120463,0.000009046461,0.000015296662,0.00006194599,0.000042616084,0.98910356,0.0006863028,0.008745555,0.0010689521,0.000007340511],"about_ca_topic_score_codex":0.0012198357,"about_ca_topic_score_gemma":0.0011393472,"teacher_disagreement_score":0.0023530067,"about_ca_system_score_codex":0.0003017405,"about_ca_system_score_gemma":0.00034047654,"threshold_uncertainty_score":0.007871628},"labels":[],"label_agreement":null},{"id":"W599153350","doi":"10.1016/j.jpdc.2015.06.004","title":"Tradeoffs between cost and information for rendezvous and treasure hunt","year":2015,"lang":"en","type":"article","venue":"Journal of Parallel and Distributed Computing","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Rendezvous; Treasure; Computer science; Traverse; Advice (programming); Upper and lower bounds; Enhanced Data Rates for GSM Evolution; Node (physics); A priori and a posteriori; Situated; Network topology; Topology (electrical circuits); Combinatorics; Computer network; Mathematics; Telecommunications; Artificial intelligence; Physics","score_opus":0.05024629657989928,"score_gpt":0.28615009572103967,"score_spread":0.2359037991411404,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W599153350","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7097361,0.0040516625,0.2169172,0.003777986,0.00023696003,0.00014844823,0.000567237,0.0011621866,0.06340219],"genre_scores_gemma":[0.9865566,0.00030214572,0.010387985,0.000052992917,0.00004030124,0.000021285761,0.00008202617,0.00011063416,0.0024460019],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977731,0.0007340461,0.00009257967,0.00023985439,0.0006162517,0.0005441516],"domain_scores_gemma":[0.9552994,0.03809109,0.001200701,0.0028439732,0.0016002562,0.00096450705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038104213,0.00077943923,0.0017337598,0.0019763985,0.001047005,0.0033341455,0.0023888247,0.0028305356,0.012004069],"category_scores_gemma":[0.04361625,0.0007884552,0.0006367672,0.0015366634,0.0019795718,0.008048253,0.0025412005,0.0015280828,0.0010970519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.006876255,0.00042522894,0.006020481,0.00061418687,0.00019020597,0.00056805107,0.00048426056,0.599772,0.017438851,0.21600172,0.004118498,0.14749035],"study_design_scores_gemma":[0.00023105138,0.0006060215,0.003924481,0.000079824094,0.00013743246,0.0006362205,0.0005296423,0.8318446,0.008117717,0.15199201,0.001777464,0.00012359637],"about_ca_topic_score_codex":0.0022520625,"about_ca_topic_score_gemma":0.002809712,"teacher_disagreement_score":0.012004069,"about_ca_system_score_codex":0.0013852504,"about_ca_system_score_gemma":0.0012591645,"threshold_uncertainty_score":0.040157616},"labels":[],"label_agreement":null},{"id":"W646988672","doi":"10.1016/j.tcs.2015.05.034","title":"Competitive algorithms for unbounded one-way trading","year":2015,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Hebei Province; Chinese Academy of Sciences; National Natural Science Foundation of China","keywords":"Competitive analysis; Upper and lower bounds; Value (mathematics); Online algorithm; Product (mathematics); Combinatorics; Mathematics; Integer (computer science); Function (biology); Revenue; Logarithm; Sequence (biology); Algorithm; Discrete mathematics; Computer science; Economics; Statistics; Finance","score_opus":0.06660840790346818,"score_gpt":0.31207445656924127,"score_spread":0.2454660486657731,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W646988672","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.061464656,0.0031059273,0.88580406,0.002696049,0.00041800196,0.00018038785,0.00027802106,0.0008002197,0.045252685],"genre_scores_gemma":[0.74750584,0.00175692,0.22070555,0.0006767777,0.00045759606,0.00045683258,0.0004819588,0.00042630214,0.027532231],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974306,0.001169655,0.00011226225,0.00035916432,0.000567897,0.0003604616],"domain_scores_gemma":[0.98578054,0.011106138,0.00046385927,0.0011378006,0.0006883382,0.00082343473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030757457,0.0015886832,0.003384467,0.001174156,0.0019823688,0.0050733346,0.0050131828,0.0039484454,0.013199486],"category_scores_gemma":[0.020456655,0.00079222466,0.0013989687,0.0025675492,0.0031298671,0.00809854,0.004315524,0.0055836625,0.0017010203],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005392749,0.00031854075,0.00046207244,0.00030880948,0.00009406596,0.00012285948,0.00021216091,0.15044628,0.001006565,0.7751483,0.012973906,0.058367245],"study_design_scores_gemma":[0.00009984788,0.000046398738,0.00007360095,0.00002296742,0.000020546613,0.00005424298,0.000035179433,0.4708768,0.00022770188,0.52632606,0.0021988393,0.000017801853],"about_ca_topic_score_codex":0.0025679742,"about_ca_topic_score_gemma":0.0024243859,"teacher_disagreement_score":0.013199486,"about_ca_system_score_codex":0.0022099253,"about_ca_system_score_gemma":0.0021124773,"threshold_uncertainty_score":0.04415667},"labels":[],"label_agreement":null},{"id":"W647692831","doi":"10.1007/978-3-642-39274-0","title":"Implementation and Application of Automata : 18th international conference, CIAA 2013, Halifax, NS, Canada, July 16-19, 2013, proceedings","year":2013,"lang":"en","type":"book","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Nested word; Computer science; Automaton; Automata theory; Parsing; Theoretical computer science; Programming language; Quantum finite automata","score_opus":0.016989913192527822,"score_gpt":0.2736276097040486,"score_spread":0.2566376965115208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W647692831","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009298312,0.015708188,0.8399032,0.0047047567,0.0062351716,0.0004172226,0.0017593978,0.02541594,0.09655786],"genre_scores_gemma":[0.07451788,0.01436431,0.7184324,0.0010128703,0.0005175281,0.0006351787,0.005901145,0.004188497,0.18043017],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99881303,0.00026206143,0.00010459146,0.00016625629,0.00049444655,0.0001596071],"domain_scores_gemma":[0.99750656,0.0005009107,0.000034041394,0.00054742483,0.001214052,0.00019705942],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025822548,0.0012660887,0.0011099946,0.0009584922,0.0013549518,0.005402909,0.0031425268,0.0013826459,0.040290087],"category_scores_gemma":[0.0042831334,0.0011261533,0.001159739,0.0011901769,0.0013864408,0.0028445919,0.0022483561,0.0022941476,0.01157739],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00039208704,0.00026497696,0.00090458925,0.0006161434,0.00009265718,0.0001694989,0.000437301,0.014270953,0.01271538,0.055465177,0.29309306,0.6215782],"study_design_scores_gemma":[0.00009040159,0.00019440378,0.0012797551,0.0004197753,0.00009558642,0.00038380956,0.000389789,0.08767465,0.021951504,0.04598705,0.8414343,0.0000989891],"about_ca_topic_score_codex":0.05669811,"about_ca_topic_score_gemma":0.066042304,"teacher_disagreement_score":0.05669811,"about_ca_system_score_codex":0.0031452256,"about_ca_system_score_gemma":0.0071671777,"threshold_uncertainty_score":0.13478374},"labels":[],"label_agreement":null},{"id":"W6891765915","doi":"10.4230/lipics.opodis.2024.11","title":"Gathering Teams of Deterministic Finite Automata on a Line","year":2025,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"Natural Sciences and Engineering Research Council of Canada; Université du Québec en Outaouais","keywords":"Task (project management); State (computer science); Set (abstract data type); Node (physics); Deterministic algorithm; Line (geometry); Integer (computer science); Time complexity","score_opus":0.01909302301479185,"score_gpt":0.29656767002335854,"score_spread":0.2774746470085667,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6891765915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18600242,0.00020638884,0.7975765,0.00046886536,0.000050754894,0.0003298836,0.0004717808,0.0022902957,0.012603183],"genre_scores_gemma":[0.7579544,0.00021722102,0.2284366,0.00019563964,0.000052983418,0.00071126455,0.0011713766,0.0002533695,0.011007271],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9969363,0.00086459663,0.00034570278,0.0008200358,0.00046535747,0.0005679786],"domain_scores_gemma":[0.992218,0.004798498,0.0009779697,0.0008478965,0.00060583715,0.0005517644],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014732477,0.0011869367,0.0011826729,0.0007766633,0.0012467501,0.0030970722,0.002162073,0.0015313354,0.007859949],"category_scores_gemma":[0.008050103,0.0008962794,0.0023359791,0.0010554136,0.0021141788,0.003348669,0.0031446007,0.0014329487,0.0011817906],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00066976564,0.00015919346,0.0029730792,0.00028525884,0.00012895298,0.000998173,0.0011492167,0.86169034,0.0055257617,0.10439437,0.0014861095,0.020539783],"study_design_scores_gemma":[0.0000984619,0.00009470198,0.00023359188,0.000029276182,0.000038272512,0.000096874115,0.00018050238,0.9320978,0.0018559281,0.06265936,0.0025856092,0.000029621247],"about_ca_topic_score_codex":0.0054517435,"about_ca_topic_score_gemma":0.0037500511,"teacher_disagreement_score":0.007859949,"about_ca_system_score_codex":0.0020024201,"about_ca_system_score_gemma":0.0010698325,"threshold_uncertainty_score":0.026294112},"labels":[],"label_agreement":null},{"id":"W6906622769","doi":"10.18434/m32212","title":"SHREC'10 Track: Non-rigid 3D Shape Retrieval","year":2010,"lang":"en","type":"dataset","venue":"National Institute of Standards and Technology (NIST)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Benchmark (surveying); Object (grammar); Polygon mesh; Class (philosophy); ASCII; Task (project management); 3d model; Pattern recognition (psychology)","score_opus":0.014369764372044892,"score_gpt":0.3028795821873874,"score_spread":0.2885098178153425,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6906622769","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07746974,0.022921033,0.23044148,0.0037277741,0.013407102,0.010612707,0.37474594,0.17690332,0.08977094],"genre_scores_gemma":[0.026165027,0.002349577,0.11751078,0.0008037898,0.00034220034,0.0013335376,0.80111873,0.0028019138,0.047574427],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99200785,0.0009252848,0.0004067939,0.001624161,0.004389578,0.00064637506],"domain_scores_gemma":[0.992246,0.0011950036,0.00019411376,0.0028826431,0.0027952434,0.00068713067],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0067844386,0.0059826123,0.0062333085,0.0052029397,0.002219245,0.0056619346,0.011238349,0.004712629,0.035023205],"category_scores_gemma":[0.010851657,0.0010978004,0.0039134496,0.0042496524,0.0010739363,0.0063637546,0.0055533685,0.0037513697,0.03729193],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005983819,0.0007093326,0.0010370633,0.0009234834,0.00034061103,0.0001888892,0.00006635101,0.0042415042,0.008679126,0.0013140764,0.75890374,0.2229974],"study_design_scores_gemma":[0.0014261431,0.0029767216,0.013136658,0.0004901208,0.00042305447,0.0020771553,0.0006565537,0.2497093,0.0537944,0.00628129,0.66871357,0.0003151258],"about_ca_topic_score_codex":0.052941706,"about_ca_topic_score_gemma":0.06820305,"teacher_disagreement_score":0.052941706,"about_ca_system_score_codex":0.003395586,"about_ca_system_score_gemma":0.0040104855,"threshold_uncertainty_score":0.117164314},"labels":[],"label_agreement":null},{"id":"W6910493941","doi":"10.4230/lipics.disc.2022.11","title":"How to Meet at a Node of Any Connected Graph","year":2022,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Rendezvous; Strongly connected component; Graph; Node (physics); Set (abstract data type); Task (project management); Finite set; Directed graph; Integer (computer science)","score_opus":0.017399656834605638,"score_gpt":0.2415029935148019,"score_spread":0.22410333668019625,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6910493941","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20453893,0.0015464914,0.7214252,0.0087640695,0.00052753784,0.0007723263,0.0016213343,0.0014330738,0.059371073],"genre_scores_gemma":[0.57016873,0.0023273884,0.39962876,0.00069405395,0.00020111196,0.00057687965,0.002989535,0.0005747403,0.022838833],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99874026,0.000345735,0.00007919951,0.0004476768,0.00022428532,0.00016287704],"domain_scores_gemma":[0.99532986,0.003067744,0.00032624122,0.00056864525,0.00028253943,0.00042492454],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00080723315,0.0008324228,0.00068203406,0.00057750166,0.001348628,0.0021946493,0.0016467088,0.002059701,0.008274027],"category_scores_gemma":[0.0088071665,0.0004891649,0.0010378733,0.0009498961,0.0020502098,0.0057949997,0.0014861489,0.0015716284,0.0019644268],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005821618,0.00024513842,0.0031273395,0.0016004178,0.00017960298,0.0009890603,0.0018817332,0.19167106,0.014738618,0.6025008,0.030953733,0.15153041],"study_design_scores_gemma":[0.000097574346,0.00018627249,0.0011392446,0.0001387073,0.00010828166,0.00084750744,0.0014435739,0.18129635,0.0076696915,0.7536562,0.053335365,0.000081345774],"about_ca_topic_score_codex":0.0031285195,"about_ca_topic_score_gemma":0.003183405,"teacher_disagreement_score":0.008274027,"about_ca_system_score_codex":0.0010632226,"about_ca_system_score_gemma":0.0011108959,"threshold_uncertainty_score":0.027679324},"labels":[],"label_agreement":null},{"id":"W6930159861","doi":"10.5281/zenodo.12144537","title":"Unravel me becka mack pdf","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Paraphernalia; Staring; TSG101; Gloom; Filter (signal processing)","score_opus":0.03197470759588548,"score_gpt":0.2508860078358982,"score_spread":0.21891130024001274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930159861","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0007171267,0.0022271562,0.0041274857,0.004652728,0.009686886,0.0002600095,0.004064997,0.014903482,0.95936006],"genre_scores_gemma":[0.001966178,0.0011774796,0.0012512963,0.001378169,0.0012183858,0.000060835657,0.0013255675,0.0033939544,0.98822814],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999298,0.00004893681,0.000035250083,0.00009968725,0.00042545982,0.00009264867],"domain_scores_gemma":[0.9975854,0.00026381135,0.00009335853,0.00032565696,0.0010428062,0.00068897865],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00073095533,0.001569002,0.00079870486,0.0020935575,0.0016283505,0.007684381,0.0014904488,0.0019041934,0.85037464],"category_scores_gemma":[0.0046551763,0.00070730963,0.0009849464,0.0013203361,0.00077030633,0.007600638,0.0040713227,0.0027834782,0.79923064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000035932244,0.000019687086,0.000052028034,0.00013171877,0.0000019782874,0.00008929212,0.000047143345,0.00003371661,0.00044484882,0.001365334,0.9442389,0.053539388],"study_design_scores_gemma":[0.0000053875524,0.000010632761,0.00012226224,0.000056162615,0.000001654364,0.000111052344,0.000037596565,0.000030109339,0.00021625799,0.00044838616,0.9989543,0.000006099252],"about_ca_topic_score_codex":0.0016063512,"about_ca_topic_score_gemma":0.0033867306,"teacher_disagreement_score":0.14962536,"about_ca_system_score_codex":0.0010729255,"about_ca_system_score_gemma":0.0013766525,"threshold_uncertainty_score":0.21342242},"labels":[],"label_agreement":null},{"id":"W6930364889","doi":"10.5281/zenodo.12222022","title":"Iso 10000 pdf","year":2024,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Limiting; Nucleofection; Work (physics); Context (archaeology); Quality (philosophy)","score_opus":0.028556968612108175,"score_gpt":0.24845925157954302,"score_spread":0.21990228296743483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6930364889","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00029375879,0.0011004326,0.004420718,0.00087621756,0.0028891629,0.00037116214,0.010029548,0.009603798,0.97041523],"genre_scores_gemma":[0.00125953,0.0011972901,0.0020237952,0.0006873161,0.0005799799,0.00014986708,0.0080071585,0.0034281171,0.9826669],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99806684,0.00011883527,0.00013303716,0.00023285595,0.0012858204,0.0001627036],"domain_scores_gemma":[0.99391794,0.0006008496,0.00020116137,0.00076944806,0.0037815617,0.0007290106],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001399759,0.0021113406,0.0014895791,0.005534443,0.0017514152,0.010889526,0.0033369944,0.0030319444,0.9123049],"category_scores_gemma":[0.0084466655,0.0012876439,0.0013385039,0.004357985,0.0008945526,0.008233158,0.003528639,0.0027487644,0.8951928],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005767521,0.000060255938,0.00006230494,0.00038960334,0.000004799468,0.000057956855,0.00003717855,0.00009456727,0.00087564636,0.0024917414,0.8847925,0.111075774],"study_design_scores_gemma":[0.000010633051,0.000018112803,0.0001566777,0.00008247844,0.0000029519708,0.000069454596,0.000029359999,0.00004279635,0.00035651147,0.0007061593,0.9985158,0.000009123225],"about_ca_topic_score_codex":0.00312741,"about_ca_topic_score_gemma":0.0036972172,"teacher_disagreement_score":0.08769512,"about_ca_system_score_codex":0.001715832,"about_ca_system_score_gemma":0.00238677,"threshold_uncertainty_score":0.12508637},"labels":[],"label_agreement":null},{"id":"W6931461656","doi":"10.5281/zenodo.4672749","title":"Okanopteryx Archibald & Cannings & Erickson & Bybee & Mathewes 2021, new genus","year":2021,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Genus; Quadrangle; Sensu; Type species","score_opus":0.030376903784153884,"score_gpt":0.23785191356793725,"score_spread":0.20747500978378336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931461656","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23865782,0.0464691,0.008625803,0.0013464539,0.0020932343,0.0005037452,0.0037121905,0.000640123,0.69795156],"genre_scores_gemma":[0.79389846,0.022858948,0.017101936,0.0012068386,0.00075877475,0.00034063068,0.0040352987,0.00011869211,0.15968049],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9998641,0.000007689371,0.000014951838,0.00004624609,0.000050504725,0.00001649265],"domain_scores_gemma":[0.9998442,0.000025626841,0.00004431013,0.000026428626,0.000045489272,0.000013805579],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011055561,0.00053026486,0.00030833628,0.0012720247,0.0015867582,0.0006581302,0.00058988505,0.000547592,0.011162052],"category_scores_gemma":[0.0004520441,0.00024734464,0.00018547245,0.00082718884,0.00088275014,0.001537775,0.00085592107,0.00089196896,0.0019368522],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005166436,0.000061705745,0.0258883,0.000940602,0.00007065509,0.0016248774,0.0023778616,0.0008607864,0.014047612,0.008960854,0.031255044,0.9133951],"study_design_scores_gemma":[0.00004946307,0.00013627113,0.1980269,0.000915534,0.00018337356,0.005343246,0.001911675,0.0006777485,0.0015201311,0.002733745,0.7884559,0.000045993635],"about_ca_topic_score_codex":0.017010184,"about_ca_topic_score_gemma":0.052568786,"teacher_disagreement_score":0.017010184,"about_ca_system_score_codex":0.001072148,"about_ca_system_score_gemma":0.0007731911,"threshold_uncertainty_score":0.03734076},"labels":[],"label_agreement":null},{"id":"W6931818618","doi":"10.5281/zenodo.8098073","title":"jessicastockdale/genomicSIs: v1.0.0 Nature Communcations","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Resolution (logic); Period (music); High resolution; Natural (archaeology)","score_opus":0.03306462859708053,"score_gpt":0.26174013222251197,"score_spread":0.22867550362543143,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6931818618","genre_codex":"dataset","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008419901,0.00088490726,0.06562971,0.0012356623,0.0014658557,0.00012888199,0.44986966,0.4225689,0.057374403],"genre_scores_gemma":[0.009869715,0.0010803184,0.071248785,0.001681282,0.00052601355,0.0009526006,0.5343792,0.3317611,0.04850104],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984261,0.0001972533,0.00010360799,0.00031689688,0.0007578082,0.00019846282],"domain_scores_gemma":[0.996924,0.0008811613,0.00023047467,0.0011425052,0.0004089867,0.00041291284],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002734357,0.002499631,0.002781495,0.0045894654,0.0012678204,0.005739853,0.006124635,0.0029297406,0.46246412],"category_scores_gemma":[0.008448119,0.0026522547,0.0019694224,0.004936163,0.0007499819,0.0029067574,0.0043118475,0.0031844357,0.53753626],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010336387,0.0000136910785,0.00024796414,0.00043291578,0.000048245845,0.000056918787,0.000053038508,0.00054587994,0.0014198091,0.0034161713,0.97729504,0.016367083],"study_design_scores_gemma":[0.00019869751,0.000028240434,0.0007291289,0.00012591558,0.00003776509,0.00019104106,0.00002107735,0.002559991,0.004495811,0.011346,0.9801829,0.000083466824],"about_ca_topic_score_codex":0.0045738965,"about_ca_topic_score_gemma":0.0073561394,"teacher_disagreement_score":0.46246412,"about_ca_system_score_codex":0.0012547558,"about_ca_system_score_gemma":0.0020862313,"threshold_uncertainty_score":0.7667297},"labels":[],"label_agreement":null},{"id":"W6948871246","doi":"10.5281/zenodo.11857367","title":"conjonctivite nourrisson pdf","year":2024,"lang":"fr","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Limiting; Infectious agent; Chlamydia; Medical screening","score_opus":0.04326887277714394,"score_gpt":0.2560438463703504,"score_spread":0.21277497359320643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6948871246","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00045753198,0.00048015793,0.0009947931,0.0009469422,0.0032739742,0.00013174885,0.0017124984,0.004912107,0.9870904],"genre_scores_gemma":[0.0014098936,0.00028874355,0.0003981599,0.0004416306,0.00040270638,0.00003633132,0.0009163693,0.0018085557,0.99429756],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989066,0.000078515804,0.000039740382,0.00012305802,0.0007237403,0.00012828854],"domain_scores_gemma":[0.9960532,0.00043083445,0.000092953975,0.0006090899,0.0020793718,0.0007344508],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00076613395,0.0013953336,0.0008614689,0.002412003,0.0021769695,0.007689019,0.0017729047,0.0020322902,0.9282009],"category_scores_gemma":[0.0052793976,0.0007640936,0.00091821764,0.0020230783,0.0008002071,0.0046141297,0.0036410757,0.0023938594,0.8805393],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054431282,0.000033374043,0.0000608253,0.00011250836,0.000002793583,0.00007223934,0.000051734867,0.000033909506,0.00050439005,0.0014345171,0.94566166,0.051977593],"study_design_scores_gemma":[0.000008597807,0.000016070711,0.00018634148,0.00003444477,0.0000022212748,0.000101203084,0.00005177493,0.000037882233,0.00035683296,0.000437473,0.99875927,0.000007910926],"about_ca_topic_score_codex":0.0030772707,"about_ca_topic_score_gemma":0.007876047,"teacher_disagreement_score":0.0717991,"about_ca_system_score_codex":0.0019025982,"about_ca_system_score_gemma":0.0015308246,"threshold_uncertainty_score":0.1024127},"labels":[],"label_agreement":null},{"id":"W6949119403","doi":"10.5281/zenodo.12636795","title":"PBL Tops CLAMPS observations","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Impact","funders":"","keywords":"TOPS; Planetary boundary layer; Radar; Block (permutation group theory); Boundary (topology); Azimuth; Storm","score_opus":0.08163159801935926,"score_gpt":0.26063496799918445,"score_spread":0.1790033699798252,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6949119403","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3231794,0.00045724388,0.012668684,0.0005508872,0.0005148327,0.0009972419,0.5191296,0.010124769,0.13237737],"genre_scores_gemma":[0.5430401,0.00021685107,0.016540946,0.00049739925,0.00025222378,0.00051482854,0.41807777,0.0007149237,0.020144882],"study_design_codex":"not_applicable","study_design_gemma":"observational","domain_scores_codex":[0.99937314,0.000030961608,0.000030445568,0.00014360782,0.0003224065,0.000099416466],"domain_scores_gemma":[0.99891937,0.00006083056,0.000116538155,0.00025525107,0.00048407944,0.00016392063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00047534204,0.00038311424,0.00044984513,0.0010899677,0.0006217124,0.0013197159,0.0011346515,0.0005631394,0.01612588],"category_scores_gemma":[0.0012297882,0.0002715836,0.0004734757,0.0017127523,0.0001681234,0.0008921415,0.00112572,0.0009370253,0.0067822607],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015530436,0.00060863176,0.29965013,0.0006808329,0.0002418443,0.0007468938,0.00089079875,0.014620403,0.04194825,0.0023082835,0.46871775,0.16803306],"study_design_scores_gemma":[0.000539108,0.00021631962,0.5429044,0.00021280143,0.00014858613,0.00020499509,0.0010824194,0.03372461,0.026634922,0.001014461,0.3931991,0.00011833672],"about_ca_topic_score_codex":0.047345016,"about_ca_topic_score_gemma":0.048845373,"teacher_disagreement_score":0.047345016,"about_ca_system_score_codex":0.00088039436,"about_ca_system_score_gemma":0.0013997982,"threshold_uncertainty_score":0.09413886},"labels":[],"label_agreement":null},{"id":"W6989303635","doi":"","title":"An AO* based exact algorithm for the Canadian traveler problem","year":2016,"lang":"en","type":"article","venue":"Figshare","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Tree traversal; Markov process; Vertex (graph theory); Time complexity; Markov decision process; Node (physics); Graph; Graph traversal; Markov chain","score_opus":0.051152866382500155,"score_gpt":0.27769085016560907,"score_spread":0.2265379837831089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6989303635","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04220221,0.00039612217,0.92116505,0.0011940858,0.00014352903,0.00046099199,0.0010054031,0.0038775352,0.029555088],"genre_scores_gemma":[0.27812165,0.00020648785,0.7100825,0.00037001734,0.000040856587,0.0003573978,0.0014977087,0.00036490313,0.008958529],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939084,0.000077923825,0.000025267058,0.00015997273,0.00016422306,0.00018177697],"domain_scores_gemma":[0.99921286,0.00039923325,0.00006636384,0.000106834595,0.00014731986,0.000067308385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007274457,0.00090682367,0.00078123354,0.00092815753,0.00096118264,0.0010630742,0.0019956012,0.0010481122,0.0102144815],"category_scores_gemma":[0.0027106442,0.0004654324,0.0006908792,0.0016634484,0.00068444136,0.0012853985,0.0015028865,0.0012500226,0.0010328261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00025322352,0.00019378141,0.0012067303,0.00014349532,0.00003892378,0.00008168743,0.000089881556,0.6603364,0.0012869051,0.04527735,0.019129867,0.2719618],"study_design_scores_gemma":[0.00006814676,0.00002570173,0.00015621085,0.000008771016,0.000007782927,0.000021381189,0.00003241671,0.97971636,0.00035851315,0.016155085,0.0034416982,0.000007850585],"about_ca_topic_score_codex":0.13769548,"about_ca_topic_score_gemma":0.18002875,"teacher_disagreement_score":0.13769548,"about_ca_system_score_codex":0.0029512558,"about_ca_system_score_gemma":0.009657461,"threshold_uncertainty_score":0.27378803},"labels":[],"label_agreement":null},{"id":"W6989670241","doi":"","title":"The Canadian Traveller Problem on unit-weighted and arbitrarily weighted outerplanar graphs","year":2025,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Agence Nationale de la Recherche","keywords":"Competitive analysis; Cardinality (data modeling); Treewidth; Graph; Upper and lower bounds; Enhanced Data Rates for GSM Evolution; Pathwidth; Outerplanar graph","score_opus":0.01459357000948829,"score_gpt":0.2288761969656249,"score_spread":0.2142826269561366,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6989670241","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.54152066,0.0012150244,0.3653232,0.0041875048,0.0001458333,0.0010579046,0.0036914095,0.0020890106,0.08076941],"genre_scores_gemma":[0.795826,0.0014500608,0.16432753,0.000520628,0.00006870138,0.00032205568,0.0044169393,0.0004884438,0.032579593],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988418,0.000211433,0.000034947865,0.00027003212,0.00019693255,0.00044479177],"domain_scores_gemma":[0.9979006,0.0010833031,0.00023334665,0.00017012098,0.00017996208,0.00043261744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071554777,0.0017046737,0.0012933674,0.0009039338,0.0021083953,0.0023642315,0.004149628,0.002125393,0.012077413],"category_scores_gemma":[0.0044829673,0.0006487027,0.0010448662,0.002632624,0.0016015094,0.00526627,0.002048121,0.0019737235,0.0009676269],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00094543543,0.00044145095,0.0021827861,0.00087383384,0.00017465962,0.0005098736,0.00067353237,0.68180704,0.0075335326,0.19479515,0.027100286,0.08296241],"study_design_scores_gemma":[0.00022830462,0.00022258038,0.0011211471,0.000057540045,0.00010567451,0.00031928197,0.00075186277,0.8580511,0.0062988526,0.11159564,0.02117543,0.00007268834],"about_ca_topic_score_codex":0.16299601,"about_ca_topic_score_gemma":0.17087033,"teacher_disagreement_score":0.16299601,"about_ca_system_score_codex":0.0054761157,"about_ca_system_score_gemma":0.006120135,"threshold_uncertainty_score":0.32409447},"labels":[],"label_agreement":null},{"id":"W7023259415","doi":"","title":"Caribana '68","year":2010,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"","score_opus":0.00892101707503403,"score_gpt":0.1546943905601826,"score_spread":0.14577337348514857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7023259415","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0013791159,0.00042195548,0.0004963576,0.000899537,0.00085857016,0.000021685613,0.0006975887,0.00038107327,0.9948441],"genre_scores_gemma":[0.0057832478,0.00038284273,0.0005776374,0.00022473969,0.00006079165,0.000010314754,0.0006667593,0.00022398097,0.9920697],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9999168,0.00000747484,0.0000012712312,0.000014387866,0.000033405606,0.000026652455],"domain_scores_gemma":[0.9999069,0.000008790208,0.000002240933,0.000010295197,0.000040916275,0.00003091363],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00013635322,0.00049776613,0.00021633727,0.00092383265,0.0027333081,0.002583949,0.00046720373,0.00084166654,0.40624595],"category_scores_gemma":[0.0003702168,0.0001762954,0.0002242645,0.0010684823,0.0005002946,0.0007891945,0.0012060129,0.0010314044,0.12404081],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046711,0.000019054378,0.00023478079,0.00007872628,0.0000024084084,0.00032912608,0.0008187019,0.0000798378,0.0006782382,0.015557057,0.92076105,0.061394233],"study_design_scores_gemma":[0.0000019221982,0.0000029801242,0.00032968225,0.00002763654,8.977804e-7,0.00006545872,0.00039684869,0.000030309528,0.000081063554,0.0003330373,0.9987282,0.000001978515],"about_ca_topic_score_codex":0.082957156,"about_ca_topic_score_gemma":0.3227248,"teacher_disagreement_score":0.91704285,"about_ca_system_score_codex":0.0013742599,"about_ca_system_score_gemma":0.0013103492,"threshold_uncertainty_score":0.8469181},"labels":[],"label_agreement":null},{"id":"W7067965317","doi":"","title":"Multi-agent, multi-objective path planning in complex environments","year":2021,"lang":"en","type":"dissertation","venue":"IDEALS (University of Illinois Urbana-Champaign)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Motion planning; A priori and a posteriori; Markov decision process; Path (computing); Graph; Robot; Set (abstract data type); Any-angle path planning","score_opus":0.041088521127256986,"score_gpt":0.26121912140212344,"score_spread":0.22013060027486647,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7067965317","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.059684597,0.00025820863,0.9361265,0.00042104357,0.00003136312,0.00007532941,0.00011003912,0.0001495877,0.003143382],"genre_scores_gemma":[0.8196505,0.00053701794,0.17578633,0.00008800745,0.000032570402,0.00017585307,0.00015043333,0.00005645243,0.0035229316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961746,0.00013262189,0.000018595325,0.00012165683,0.000059136863,0.000050564788],"domain_scores_gemma":[0.9989011,0.0007543566,0.00016994016,0.000048497466,0.00006135661,0.00006478708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007053642,0.0006017066,0.00065690756,0.000385486,0.0006036058,0.0009629857,0.0009417968,0.0008989691,0.0014047935],"category_scores_gemma":[0.0020521756,0.00047747613,0.0006444464,0.00057504594,0.0014089348,0.0011192445,0.0013557439,0.000991761,0.00013654161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000013365368,0.000013564674,0.00024832998,0.000030145302,0.00001396918,0.000059003065,0.000038159927,0.9828122,0.00031468854,0.012693571,0.00016530704,0.003597563],"study_design_scores_gemma":[0.0000062466115,0.000012805925,0.00007176438,0.0000032030846,0.0000037593848,0.000007307752,0.000015477213,0.99103546,0.00011010342,0.00846013,0.00027075072,0.00000289567],"about_ca_topic_score_codex":0.009765566,"about_ca_topic_score_gemma":0.008275882,"teacher_disagreement_score":0.009765566,"about_ca_system_score_codex":0.0010945002,"about_ca_system_score_gemma":0.0012007338,"threshold_uncertainty_score":0.019417465},"labels":[],"label_agreement":null},{"id":"W7096413328","doi":"","title":"2014 Canadian Conference on Computer and Robot Vision Asymmetric Rendezvous Search at Sea","year":2014,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Drifter; Rendezvous; Position (finance); Underwater; Trajectory; Robot; Field (mathematics)","score_opus":0.025053082926508374,"score_gpt":0.2639916726582576,"score_spread":0.23893858973174925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096413328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0133748455,0.0938505,0.4940378,0.01350466,0.011610688,0.0004356532,0.0026983218,0.008303268,0.36218417],"genre_scores_gemma":[0.19176805,0.08159175,0.2087376,0.002901174,0.0026894289,0.0005803673,0.0064320685,0.0013178247,0.5039817],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989599,0.00013642498,0.000060563452,0.00021346085,0.0004974002,0.00013211442],"domain_scores_gemma":[0.9986338,0.00025072435,0.000034372155,0.00021782417,0.0007616799,0.00010150846],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013298404,0.0010924808,0.0014959787,0.0016726308,0.0009773709,0.00376182,0.0023664448,0.002211742,0.09341558],"category_scores_gemma":[0.0030102015,0.000412439,0.0006738571,0.0027398109,0.0016034562,0.0019739997,0.001401146,0.0018203469,0.02569484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019762616,0.000084392894,0.00078090397,0.00047839835,0.00008827884,0.00017979777,0.00010681761,0.012706659,0.0040657097,0.02022327,0.30424896,0.65683913],"study_design_scores_gemma":[0.000039557446,0.00006723341,0.002360851,0.00032597536,0.000064961154,0.00034152006,0.00029322886,0.118869,0.0019407066,0.024692273,0.8509394,0.00006531424],"about_ca_topic_score_codex":0.11256735,"about_ca_topic_score_gemma":0.08193736,"teacher_disagreement_score":0.11256735,"about_ca_system_score_codex":0.0024445157,"about_ca_system_score_gemma":0.0052839573,"threshold_uncertainty_score":0.31250626},"labels":[],"label_agreement":null},{"id":"W7096631854","doi":"","title":"EFFORT ALLOCATION ALGORITHMS FOR SEARCH AND RESCUE OPERATIONS 1","year":2013,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Search algorithm; Beam search; Object (grammar); Search and rescue; Best-first search; Incremental heuristic search; Guided Local Search; Constraint satisfaction; Local search (optimization)","score_opus":0.041500704220413895,"score_gpt":0.3076132840125321,"score_spread":0.26611257979211816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096631854","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038750193,0.00061607437,0.98926955,0.00018995376,0.00005978323,0.0000721166,0.00006767638,0.0002245332,0.005625281],"genre_scores_gemma":[0.26276332,0.0013732455,0.72236025,0.00020131166,0.00016799572,0.00059111154,0.00040817846,0.00020550353,0.011929069],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991757,0.000328514,0.000037659127,0.0001270837,0.00020554099,0.00012537131],"domain_scores_gemma":[0.99913824,0.0005730275,0.00005918252,0.000048002985,0.00014626066,0.000035194236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012740508,0.0012935897,0.0012884365,0.0010740893,0.0007210599,0.0014315799,0.0017560465,0.001376081,0.0066583045],"category_scores_gemma":[0.0042436924,0.00047587205,0.0006271734,0.0018183499,0.00088007905,0.0020190515,0.0013330214,0.0014256936,0.0009584781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005071891,0.000050025,0.00023475636,0.000086181026,0.000022058228,0.000024763463,0.000060018552,0.8218169,0.00046017056,0.07563107,0.004308308,0.09725506],"study_design_scores_gemma":[0.000019550804,0.000017054042,0.00005056436,0.000013162654,0.000005685545,0.000013171369,0.000013454919,0.97258127,0.00017648122,0.024742441,0.0023621374,0.0000048723614],"about_ca_topic_score_codex":0.011257966,"about_ca_topic_score_gemma":0.007916638,"teacher_disagreement_score":0.011257966,"about_ca_system_score_codex":0.002164389,"about_ca_system_score_gemma":0.0017380351,"threshold_uncertainty_score":0.022384882},"labels":[],"label_agreement":null},{"id":"W7096864499","doi":"","title":"2010 Published by Canadian Center of Science and Education 139","year":2016,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Multinomial distribution; Bayesian probability; Center (category theory); Probability distribution; Optimal stopping; Bayes' theorem","score_opus":0.008435738435133558,"score_gpt":0.23146695873137585,"score_spread":0.22303122029624228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7096864499","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0006020804,0.0017613989,0.00095062936,0.007132869,0.0014113454,0.00008367425,0.010650413,0.00059378485,0.9768138],"genre_scores_gemma":[0.0028094507,0.0011699342,0.0007866246,0.0004583206,0.000053556367,0.000024890445,0.0023476793,0.00018074879,0.99216884],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988734,0.00004626111,0.000054984077,0.00024925638,0.0005692822,0.00020678667],"domain_scores_gemma":[0.99569196,0.00026945432,0.000094102856,0.0005453353,0.0026667055,0.00073237246],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009543948,0.0010519595,0.0013500551,0.0027337892,0.0038128744,0.0076632304,0.0019793618,0.0035010474,0.7708033],"category_scores_gemma":[0.0037290705,0.0006529746,0.0006480137,0.0054154485,0.0021349255,0.0022498544,0.0016745493,0.0017577694,0.53281873],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000031221305,0.00003300502,0.0005726617,0.00015404582,0.00000708656,0.00010343203,0.00007468161,0.00019955402,0.0003683589,0.03136703,0.86415684,0.10293208],"study_design_scores_gemma":[0.0000031098925,0.000002790685,0.00045347514,0.000048696755,0.0000015565582,0.000022122638,0.000037826856,0.0000916512,0.00005355724,0.0007233907,0.99855644,0.00000532302],"about_ca_topic_score_codex":0.56795275,"about_ca_topic_score_gemma":0.6559735,"teacher_disagreement_score":0.56795275,"about_ca_system_score_codex":0.014552568,"about_ca_system_score_gemma":0.042414635,"threshold_uncertainty_score":0.8691833},"labels":[],"label_agreement":null},{"id":"W7097241741","doi":"","title":"Tight Bounds on the Competitive Ratio on Accommodating Sequences for the Seat Reservation Problem","year":2003,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Reservation; Competitive analysis; Upper and lower bounds; Matching (statistics); Online algorithm; Reservation system","score_opus":0.07193377675832262,"score_gpt":0.2986140328225581,"score_spread":0.22668025606423547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097241741","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22283183,0.021346303,0.46735364,0.012409696,0.0018970785,0.0012185788,0.005399369,0.0029501845,0.26459327],"genre_scores_gemma":[0.77525437,0.01682256,0.15733203,0.0033436602,0.0033951816,0.0017249506,0.005936263,0.0025428808,0.033648092],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98556465,0.0043294607,0.0004606668,0.0018632201,0.0033376354,0.004444389],"domain_scores_gemma":[0.91762346,0.067814596,0.003260993,0.0033430548,0.003173209,0.004784781],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0106364265,0.007434655,0.0073043993,0.0049559134,0.0037476292,0.009085028,0.009292314,0.005241084,0.034335624],"category_scores_gemma":[0.065638795,0.0021356074,0.0032851354,0.007570801,0.003923621,0.013523712,0.0055972748,0.009353031,0.006406437],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0066288463,0.0024541123,0.0043913163,0.002708788,0.00056114065,0.0006330742,0.0008208997,0.43695873,0.009332069,0.32320425,0.05850158,0.15380529],"study_design_scores_gemma":[0.00035261802,0.0009133616,0.0013071828,0.0003139326,0.0001920001,0.00053918926,0.00028559298,0.71513903,0.0019549653,0.2687862,0.010112679,0.00010318269],"about_ca_topic_score_codex":0.0057478757,"about_ca_topic_score_gemma":0.004804358,"teacher_disagreement_score":0.034335624,"about_ca_system_score_codex":0.00672085,"about_ca_system_score_gemma":0.00624183,"threshold_uncertainty_score":0.11486405},"labels":[],"label_agreement":null},{"id":"W7097417830","doi":"","title":"Scheduling in the Dark (Improved Result)","year":2007,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Scheduling (production processes); Multiprocessor scheduling; Parallelizable manifold; Upper and lower bounds; Execution time; Multiprocessing; Job shop scheduling; Job queue","score_opus":0.026063634888488483,"score_gpt":0.29021631245666496,"score_spread":0.26415267756817645,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097417830","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18610582,0.0057471097,0.6127477,0.008878559,0.002243118,0.0003858031,0.0009919116,0.002879402,0.1800206],"genre_scores_gemma":[0.8370937,0.0012166451,0.12791139,0.0027221038,0.0008391217,0.00014400615,0.0005971419,0.00040335982,0.029072575],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99644226,0.0008094028,0.00014048842,0.00089243177,0.001010325,0.00070505764],"domain_scores_gemma":[0.99491274,0.0020144254,0.0003100017,0.0017116998,0.0006578862,0.0003931996],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032698107,0.0010285778,0.0012780002,0.0011552294,0.0016771164,0.0026764087,0.0026229038,0.0011114294,0.010389815],"category_scores_gemma":[0.008852115,0.00048735188,0.0007440399,0.0013810305,0.0015651567,0.0060022385,0.004089557,0.0027898639,0.0016126535],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0028493546,0.0010612222,0.0036649732,0.0008612294,0.00021256975,0.00072469824,0.0009334979,0.23988573,0.025253173,0.52239525,0.045853604,0.15630473],"study_design_scores_gemma":[0.00032097736,0.00044202417,0.0007614453,0.00007876458,0.00009606747,0.00044843685,0.0002197937,0.657961,0.012462307,0.28135762,0.04579747,0.000053995973],"about_ca_topic_score_codex":0.003166491,"about_ca_topic_score_gemma":0.0029584793,"teacher_disagreement_score":0.010389815,"about_ca_system_score_codex":0.0024181437,"about_ca_system_score_gemma":0.0023200943,"threshold_uncertainty_score":0.034757376},"labels":[],"label_agreement":null},{"id":"W7105505977","doi":"","title":"A Learning Perspective on Random-Order Covering Problems","year":2025,"lang":"","type":"article","venue":"ArXiv.org","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; York University; National Science Foundation","keywords":"Cover (algebra); Mathematical proof; Multiplicative function; Set cover problem; Set (abstract data type); Regret; Connection (principal bundle); Perspective (graphical); Matching (statistics)","score_opus":0.028332926318305737,"score_gpt":0.29239508428658206,"score_spread":0.2640621579682763,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7105505977","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01918417,0.0017449898,0.9538018,0.0048439177,0.00015457976,0.000087869164,0.0003037046,0.00030912488,0.01956984],"genre_scores_gemma":[0.63325363,0.004098813,0.3378956,0.0023921472,0.001621753,0.0005452168,0.0007995908,0.0006370748,0.018756147],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99648535,0.0016424102,0.000078497855,0.0007171536,0.0007299154,0.0003466399],"domain_scores_gemma":[0.98950243,0.00828675,0.00042869564,0.0009796082,0.0003932927,0.00040929287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042678313,0.0019353578,0.0024411622,0.0011334582,0.0010670542,0.0034975007,0.0031678742,0.0029083458,0.008099677],"category_scores_gemma":[0.014450215,0.0009065878,0.0020465252,0.0017213917,0.003827259,0.007732772,0.0028212147,0.008203832,0.001100157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010239382,0.00011136495,0.00046312765,0.00017583706,0.000049355487,0.000065620785,0.000111155925,0.17598596,0.00073250424,0.803769,0.0034148237,0.015018943],"study_design_scores_gemma":[0.00004100221,0.00009035661,0.00019304978,0.000031929903,0.000015674888,0.00005099835,0.000037069232,0.4548632,0.00055974635,0.5401995,0.00389933,0.000018051427],"about_ca_topic_score_codex":0.0023443187,"about_ca_topic_score_gemma":0.002069892,"teacher_disagreement_score":0.008099677,"about_ca_system_score_codex":0.0037060238,"about_ca_system_score_gemma":0.0016255102,"threshold_uncertainty_score":0.027096093},"labels":[],"label_agreement":null},{"id":"W7106672325","doi":"10.1007/978-981-95-4721-0_12","title":"On Online Self-Organizing Linear Search","year":2025,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Competitive analysis; Online algorithm; Bounded function; Quality (philosophy); Online search","score_opus":0.04907550252332892,"score_gpt":0.32425391086749494,"score_spread":0.275178408344166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7106672325","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010804035,0.0043223435,0.9176296,0.0007306246,0.00059135375,0.000051208575,0.00010110051,0.00062731677,0.065142535],"genre_scores_gemma":[0.55351216,0.00667423,0.2928885,0.0011261287,0.0014366544,0.00047104774,0.0004819356,0.00069440895,0.14271498],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971277,0.00009416928,0.00001231891,0.00004128434,0.000100933445,0.000038553415],"domain_scores_gemma":[0.9991493,0.00060690613,0.000035079018,0.0000849103,0.000093211616,0.000030396744],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052868016,0.0006783488,0.0008597604,0.000509824,0.00041998105,0.0011682543,0.0013761735,0.0010686473,0.009771946],"category_scores_gemma":[0.002124296,0.0002932856,0.00034811455,0.0014285607,0.0007840628,0.001753096,0.0013623429,0.0012549201,0.0018695234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010155392,0.0001379814,0.00028579356,0.00023390136,0.000054180116,0.00007369915,0.000110355126,0.48163766,0.0017874275,0.20004088,0.029891351,0.2856452],"study_design_scores_gemma":[0.000014550212,0.00004128613,0.00011497445,0.000033261105,0.000008717743,0.00005575571,0.000024412564,0.90036637,0.00055085623,0.088510565,0.010268961,0.000010366645],"about_ca_topic_score_codex":0.0014428385,"about_ca_topic_score_gemma":0.0014764231,"teacher_disagreement_score":0.009771946,"about_ca_system_score_codex":0.0005621848,"about_ca_system_score_gemma":0.00047185324,"threshold_uncertainty_score":0.032690406},"labels":[],"label_agreement":null},{"id":"W7110080440","doi":"10.4230/lipics.disc.2025.56","title":"Brief Announcement: Universal Dancing by Luminous Robots Under Sequential Schedulers","year":2025,"lang":"en","type":"article","venue":"Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robot; Sequence (biology); Swarm behaviour; Bounded function; AKA; Mobile robot; Swarm robotics; Class (philosophy)","score_opus":0.01870643762224727,"score_gpt":0.24158779274814296,"score_spread":0.22288135512589569,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7110080440","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.14554992,0.0009968426,0.8346327,0.0019418388,0.0004111229,0.00025839775,0.00039111,0.00094489934,0.01487311],"genre_scores_gemma":[0.7255051,0.0010102447,0.2564015,0.00029470117,0.00026200296,0.00035210888,0.0006956812,0.00030435916,0.015174315],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991411,0.0002303326,0.00004837099,0.00022992068,0.00012759017,0.00022273243],"domain_scores_gemma":[0.99742764,0.0015453284,0.000246929,0.0003144613,0.00014111084,0.00032449013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001410382,0.0008271048,0.0011310736,0.00035106274,0.0009911876,0.0014390259,0.001430876,0.0011409068,0.0075456733],"category_scores_gemma":[0.0060152765,0.00043847004,0.0011182554,0.00077834143,0.0015301076,0.002475711,0.0016293614,0.001647093,0.0005796993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00061759044,0.00021420576,0.0031174324,0.0007377189,0.00012964413,0.00047013524,0.00037596616,0.61033636,0.0061852564,0.26340178,0.013824262,0.10058971],"study_design_scores_gemma":[0.00008779951,0.00012410895,0.00041143392,0.000036362486,0.000028807264,0.00008239471,0.00011623374,0.8347337,0.0024763895,0.15643068,0.005450661,0.00002145127],"about_ca_topic_score_codex":0.004227284,"about_ca_topic_score_gemma":0.0045719,"teacher_disagreement_score":0.0075456733,"about_ca_system_score_codex":0.0013032418,"about_ca_system_score_gemma":0.0018254556,"threshold_uncertainty_score":0.025242805},"labels":[],"label_agreement":null},{"id":"W7117339766","doi":"","title":"Fairness in the k-Server Problem","year":2025,"lang":"","type":"article","venue":"ArXiv.org","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Competitive analysis; Online algorithm; Randomized algorithm; Metric (unit); Deterministic algorithm; Tree (set theory); Adversary; Key (lock)","score_opus":0.04458286777791705,"score_gpt":0.2949136726583961,"score_spread":0.25033080488047904,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117339766","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09261225,0.0005751922,0.8855414,0.0042715925,0.000303041,0.00024839168,0.00048160617,0.0004728745,0.015493666],"genre_scores_gemma":[0.8187191,0.00050784944,0.16488662,0.0007380532,0.00052226614,0.00036977854,0.0003696636,0.0003586511,0.013528028],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9940871,0.0024192382,0.0002765435,0.0013741504,0.00079374394,0.0010491363],"domain_scores_gemma":[0.98658574,0.0095230285,0.00069680763,0.0015873197,0.0007707137,0.00083638175],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065228883,0.0011595374,0.002809842,0.00062088255,0.0025461318,0.003523137,0.0037337153,0.0028867687,0.008210035],"category_scores_gemma":[0.020316498,0.00060206885,0.0013084369,0.0011838136,0.0031568334,0.008746512,0.002814,0.0035223488,0.0013238171],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009625421,0.00028392934,0.001990355,0.0002654575,0.00008519911,0.00023286101,0.0005007502,0.31620255,0.0033990724,0.63465995,0.009132432,0.032284863],"study_design_scores_gemma":[0.00009145601,0.000068967034,0.00026710262,0.000028818582,0.000018969951,0.00015012987,0.00013017314,0.5373347,0.0013179075,0.45714274,0.0034166728,0.000032293203],"about_ca_topic_score_codex":0.0025401614,"about_ca_topic_score_gemma":0.0017936126,"teacher_disagreement_score":0.008210035,"about_ca_system_score_codex":0.0026609697,"about_ca_system_score_gemma":0.003824522,"threshold_uncertainty_score":0.034496784},"labels":[],"label_agreement":null},{"id":"W7117548698","doi":"10.1145/3772290.3772317","title":"Linear Search for Capturing a Moving Target by Two Robots in the F2F Model","year":2025,"lang":"","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Robot; Mobile robot; Constant (computer programming); Line (geometry); Trajectory; Search algorithm","score_opus":0.04213346926334563,"score_gpt":0.3350641539226308,"score_spread":0.2929306846592852,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7117548698","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13238668,0.0010751849,0.85235304,0.0014284267,0.00008021169,0.00007978666,0.0002521157,0.00029559623,0.012049019],"genre_scores_gemma":[0.9002693,0.00044074358,0.08310908,0.0002828224,0.000092128095,0.00028944737,0.00027045512,0.00010312624,0.0151429],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992489,0.00027599692,0.000017148328,0.00015836222,0.00010824834,0.00019130843],"domain_scores_gemma":[0.99693227,0.0023449298,0.0003265054,0.00007957655,0.00013981086,0.00017694307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015033145,0.0015513647,0.0020436603,0.0008555244,0.0010048184,0.0013487096,0.0022239222,0.0044030445,0.004660256],"category_scores_gemma":[0.0051096166,0.0006660793,0.00092795904,0.0009011793,0.0020916816,0.0022206085,0.0016505521,0.001437626,0.00063398527],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00018032202,0.000050175197,0.0003987645,0.00010430089,0.000044798715,0.0002589969,0.000093418326,0.96263885,0.000710961,0.028338773,0.0012189569,0.005961746],"study_design_scores_gemma":[0.000029642473,0.00003649927,0.000060538838,0.0000051604757,0.0000053462113,0.000027598879,0.000016377153,0.9915063,0.00009506239,0.0079804575,0.00022849778,0.000008554864],"about_ca_topic_score_codex":0.011015546,"about_ca_topic_score_gemma":0.0046182466,"teacher_disagreement_score":0.011015546,"about_ca_system_score_codex":0.0016860218,"about_ca_system_score_gemma":0.00079560326,"threshold_uncertainty_score":0.02190286},"labels":[],"label_agreement":null},{"id":"W7118002167","doi":"10.1145/3712285.3787159","title":"10.1145/3712285.3787159","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Matching (statistics); Component (thermodynamics); Key (lock); System integration","score_opus":0.008104480321622224,"score_gpt":0.19079679960172505,"score_spread":0.18269231928010282,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7118002167","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002672418,0.007617143,0.0140156895,0.0018208716,0.002024063,0.0005063865,0.020348022,0.018002762,0.9329926],"genre_scores_gemma":[0.005386728,0.003235364,0.0027667782,0.0009077564,0.00016474216,0.00027988382,0.010103676,0.0022397037,0.9749153],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992855,0.000051163937,0.000055108623,0.00020792185,0.00024685115,0.00015344594],"domain_scores_gemma":[0.9984981,0.00036894376,0.00007945792,0.00051864,0.00029485737,0.00024002913],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0017468999,0.003540572,0.00277454,0.0028389208,0.0024894231,0.0044662827,0.003240245,0.005417724,0.9440609],"category_scores_gemma":[0.0033751335,0.0019301322,0.0013949889,0.010668408,0.0015549125,0.010091391,0.0057552727,0.003087001,0.9610677],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028630428,0.0002072881,0.0004721224,0.0006445174,0.000046442907,0.00020064552,0.00008633055,0.0009493993,0.0010038702,0.0072300653,0.6684942,0.32037878],"study_design_scores_gemma":[0.000052959454,0.000042275296,0.00084276847,0.00031244874,0.000049399667,0.00016862596,0.00007611325,0.001225699,0.0005644843,0.0021382766,0.9944912,0.000035720506],"about_ca_topic_score_codex":0.019931098,"about_ca_topic_score_gemma":0.014531706,"teacher_disagreement_score":0.05593908,"about_ca_system_score_codex":0.0026900864,"about_ca_system_score_gemma":0.0010876677,"threshold_uncertainty_score":0.079790235},"labels":[],"label_agreement":null},{"id":"W7124137218","doi":"10.65109/zbuc3779","title":"Optimal solutions for moving target search","year":2009,"lang":"","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Minimax; Polynomial; Work (physics); Time complexity; Adaptation (eye)","score_opus":0.06204276209070982,"score_gpt":0.3152180448769508,"score_spread":0.253175282786241,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7124137218","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015602907,0.00085614045,0.9657916,0.00035401565,0.00007976891,0.00007446933,0.00011396464,0.00049757725,0.016629502],"genre_scores_gemma":[0.32895556,0.0008952564,0.65802115,0.00028576792,0.00010520212,0.00040384475,0.0004924777,0.0003398817,0.010500955],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993325,0.00018542423,0.00002732137,0.00017692578,0.00019470023,0.000083144216],"domain_scores_gemma":[0.9993032,0.00041743842,0.000078561505,0.00007152029,0.00009011074,0.000039294075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081080594,0.0011526017,0.0010671085,0.0011959791,0.00057574076,0.0011206917,0.0015067502,0.0019389127,0.009450697],"category_scores_gemma":[0.0048306477,0.00045583004,0.00071542163,0.0011397082,0.0010656756,0.0017390357,0.0014130708,0.0016610981,0.0012307257],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011698225,0.00008882083,0.0002560268,0.00025601155,0.000041024276,0.00007645684,0.000103476785,0.6988256,0.0013160573,0.19279452,0.00819147,0.09793355],"study_design_scores_gemma":[0.000038807488,0.00006410494,0.00010973639,0.00004166196,0.000012174411,0.000059361668,0.000035163648,0.8535309,0.0007364041,0.14053193,0.0048260377,0.00001368388],"about_ca_topic_score_codex":0.0016638585,"about_ca_topic_score_gemma":0.0013956366,"teacher_disagreement_score":0.009450697,"about_ca_system_score_codex":0.001299269,"about_ca_system_score_gemma":0.0009661544,"threshold_uncertainty_score":0.031615734},"labels":[],"label_agreement":null},{"id":"W7132860486","doi":"","title":"Online Non-preemptive Resource Constrained Scheduling","year":2024,"lang":"","type":"dissertation","venue":"TSpace","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Competitive analysis; Online algorithm; Queue; Scheduling (production processes); Workload; Flow shop scheduling; Job scheduler; Job queue; Rate-monotonic scheduling","score_opus":0.0323710719327489,"score_gpt":0.36089934038133753,"score_spread":0.3285282684485886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132860486","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.040522,0.001274067,0.9492361,0.00031699124,0.00023781363,0.00025972346,0.00010569757,0.0007499134,0.007297679],"genre_scores_gemma":[0.7700941,0.0009407432,0.22311124,0.00027045424,0.0002398507,0.00024779714,0.0002082834,0.0001706631,0.0047168285],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9974195,0.00089821516,0.00012421064,0.00045168324,0.00077281,0.0003335208],"domain_scores_gemma":[0.9941976,0.0037217522,0.0005947706,0.00061624125,0.0005623698,0.0003073526],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003187937,0.0011718755,0.0017636544,0.0005066791,0.0008905211,0.0018582181,0.0032876937,0.0010106715,0.0023205997],"category_scores_gemma":[0.007370652,0.0005262984,0.00057094474,0.0010440203,0.0008896938,0.0018877301,0.0009332884,0.0014009825,0.000605055],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005225174,0.00063093123,0.0011476072,0.00048594695,0.00010255983,0.00018614007,0.00015738512,0.7838559,0.00965508,0.043756884,0.0052272854,0.15427172],"study_design_scores_gemma":[0.000018470284,0.00007320049,0.00010764537,0.000006371312,0.0000073008937,0.0000357366,0.000012668523,0.9923523,0.0010977284,0.0050768615,0.0012057488,0.0000059701633],"about_ca_topic_score_codex":0.0026089288,"about_ca_topic_score_gemma":0.0021499628,"teacher_disagreement_score":0.0032876937,"about_ca_system_score_codex":0.0014568259,"about_ca_system_score_gemma":0.0025426284,"threshold_uncertainty_score":0.01685965},"labels":[],"label_agreement":null},{"id":"W7132863946","doi":"","title":"Optimistic Competitive Analysis: Stochastic Models, Predictions, and Revocable Decisions","year":2025,"lang":"","type":"dissertation","venue":"TSpace","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Competitive analysis; Online algorithm; Greedy algorithm; Matching (statistics); Interval (graph theory); Focus (optics); Selection (genetic algorithm); Measure (data warehouse)","score_opus":0.04402059034877745,"score_gpt":0.342868087598482,"score_spread":0.2988474972497045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7132863946","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031021085,0.0020038418,0.9492541,0.002393654,0.00016039793,0.00016019799,0.0003401468,0.0005863483,0.014080272],"genre_scores_gemma":[0.8893268,0.0020468757,0.09821184,0.001237432,0.0005837263,0.000314252,0.0004650828,0.00030074173,0.00751329],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9922201,0.0034177732,0.00019887337,0.0010601832,0.0019706434,0.0011324032],"domain_scores_gemma":[0.96313876,0.02839558,0.0024677084,0.003123685,0.0017106867,0.0011636692],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010001405,0.0025298065,0.0029905918,0.0015507982,0.0016037959,0.0049382057,0.0059687076,0.0027639198,0.0067545255],"category_scores_gemma":[0.037505083,0.0011518236,0.0016967722,0.0025744226,0.004181658,0.007165041,0.0035140556,0.006792537,0.0010419223],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040653613,0.00017212123,0.0010281442,0.0001800778,0.00009810897,0.00015449255,0.00022840904,0.63888663,0.0006533665,0.33372903,0.005757301,0.018705817],"study_design_scores_gemma":[0.000022832879,0.00003116447,0.00009584348,0.000019226165,0.000012992299,0.00003256286,0.00003262995,0.87699676,0.00020901347,0.12186243,0.00066636543,0.000018188513],"about_ca_topic_score_codex":0.0057248836,"about_ca_topic_score_gemma":0.003798017,"teacher_disagreement_score":0.010001405,"about_ca_system_score_codex":0.004271991,"about_ca_system_score_gemma":0.0036394743,"threshold_uncertainty_score":0.052893102},"labels":[],"label_agreement":null},{"id":"W7133027849","doi":"","title":"Approximate truthful mechanisms for the knapsack problem, and negative results using a stack model for local ratio algorithms","year":2005,"lang":"","type":"dissertation","venue":"TSpace","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto; Library and Archives Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Knapsack problem; Approximation algorithm; Polynomial-time approximation scheme; Set (abstract data type); Stack (abstract data type); Set cover problem; Bandwidth (computing); Tree (set theory); Facility location problem","score_opus":0.07379328664914889,"score_gpt":0.36653791996931046,"score_spread":0.29274463332016154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133027849","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02835513,0.0037423677,0.9440984,0.005185197,0.00024444947,0.00007773676,0.00009017725,0.00028262654,0.017923988],"genre_scores_gemma":[0.7385829,0.006201935,0.2371461,0.0016157506,0.0010671716,0.00053223595,0.00026134538,0.00033351308,0.014259043],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9934081,0.0031731124,0.00030118,0.00076447654,0.0017994341,0.0005537657],"domain_scores_gemma":[0.9647772,0.027325066,0.0019027449,0.0037424576,0.0016644252,0.0005881143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.012126211,0.0017623428,0.0016536139,0.002235162,0.0017597735,0.0056356415,0.0038217525,0.0029612037,0.005355155],"category_scores_gemma":[0.04533625,0.0009602728,0.0029598835,0.002862032,0.006729899,0.01868643,0.0037152024,0.0077716988,0.0007194706],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012315446,0.00006656502,0.0002446173,0.00014287107,0.000036735462,0.000041733543,0.00015528043,0.046544734,0.00052564096,0.93653387,0.001631979,0.013952762],"study_design_scores_gemma":[0.000034397613,0.00007531789,0.00010128328,0.000057310852,0.00003808914,0.000062414176,0.000057960486,0.15525958,0.0006092787,0.8410465,0.0026328322,0.000024976705],"about_ca_topic_score_codex":0.002066535,"about_ca_topic_score_gemma":0.0011566833,"teacher_disagreement_score":0.012126211,"about_ca_system_score_codex":0.005144829,"about_ca_system_score_gemma":0.0026089374,"threshold_uncertainty_score":0.064130306},"labels":[],"label_agreement":null},{"id":"W7148952270","doi":"10.70675/95f0b6c8z16efz4491za4fbzfd1a8f4a96fb","title":"A guide book for the traveller on graphs full of blockages","year":2019,"lang":"","type":"dissertation","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Statistical analysis; Graph; Limiting","score_opus":0.025316668763055265,"score_gpt":0.3028194717871067,"score_spread":0.27750280302405145,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7148952270","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0023944976,0.03615349,0.60263497,0.009122915,0.0064742686,0.00071657234,0.007721097,0.022550011,0.31223214],"genre_scores_gemma":[0.012801966,0.029383061,0.41359448,0.004554543,0.0020354635,0.0007804964,0.009501187,0.009869902,0.5174789],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999411,0.00009516765,0.000044301327,0.00016478944,0.00023421904,0.000050487954],"domain_scores_gemma":[0.99866176,0.00064218574,0.000041140414,0.0002617166,0.00031115054,0.000081975326],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005485946,0.0029117505,0.0018411507,0.0026560428,0.0014781542,0.0028820937,0.0025046803,0.0022384003,0.14949362],"category_scores_gemma":[0.0037269173,0.001817957,0.0024809581,0.0049026944,0.0010327105,0.0076686284,0.002167621,0.00441156,0.09224136],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00007275894,0.000075654156,0.00019164932,0.00060771045,0.00004584711,0.00013012263,0.00011903023,0.0055800877,0.001831118,0.053830974,0.62121844,0.3162967],"study_design_scores_gemma":[0.000026846372,0.0000447809,0.00028920625,0.00023520016,0.000018448425,0.00044618765,0.00007548368,0.005902827,0.0007211525,0.08031727,0.91187847,0.000044247372],"about_ca_topic_score_codex":0.0065542012,"about_ca_topic_score_gemma":0.011689313,"teacher_disagreement_score":0.14949362,"about_ca_system_score_codex":0.0021407746,"about_ca_system_score_gemma":0.0016606103,"threshold_uncertainty_score":0.500106},"labels":[],"label_agreement":null},{"id":"W7154030739","doi":"10.1145/3772318.3808930","title":"10.1145/3772318.3808930","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"","keywords":"Session (web analytics); Key (lock)","score_opus":0.008183086042812435,"score_gpt":0.19128174493136305,"score_spread":0.18309865888855062,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7154030739","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026125445,0.005912321,0.013694447,0.0014452538,0.0020086337,0.00053180015,0.017021753,0.017159354,0.9396138],"genre_scores_gemma":[0.0047257333,0.002671766,0.0027744747,0.0007874254,0.00013238966,0.00027173662,0.008252427,0.0020788992,0.9783052],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992692,0.000051403338,0.000059019596,0.00020653683,0.00024430561,0.00016961477],"domain_scores_gemma":[0.9983852,0.0004014565,0.00008117029,0.0005279104,0.0003243336,0.0002800064],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0020563027,0.0039784797,0.0027118614,0.0028658407,0.002360817,0.0045645363,0.003285165,0.0051657087,0.9517934],"category_scores_gemma":[0.0032172105,0.0019685435,0.0013991386,0.0105060665,0.0017302692,0.00991792,0.005614845,0.0029079337,0.96182734],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003394281,0.00023837434,0.0004902381,0.0007232195,0.000047590493,0.00020906553,0.00009366624,0.0011252831,0.0011975897,0.0074583404,0.661831,0.32624617],"study_design_scores_gemma":[0.00006167203,0.00004374766,0.0008805798,0.000314676,0.000052042622,0.00015746416,0.00009084812,0.0014164662,0.00062308944,0.0021387478,0.99417937,0.000041249947],"about_ca_topic_score_codex":0.022647267,"about_ca_topic_score_gemma":0.01745873,"teacher_disagreement_score":0.048206627,"about_ca_system_score_codex":0.0029102238,"about_ca_system_score_gemma":0.0013179479,"threshold_uncertainty_score":0.06876093},"labels":[],"label_agreement":null},{"id":"W745574","doi":"10.1007/978-1-4939-2864-4_534","title":"Analyzing Cache Behaviour in Multicore Architectures","year":2016,"lang":"en","type":"book-chapter","venue":"Encyclopedia of Algorithms","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cache; Multi-core processor; Computer science; Parallel computing; Computer architecture; Embedded system","score_opus":0.01548729466320558,"score_gpt":0.2563340607380659,"score_spread":0.24084676607486033,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W745574","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6455922,0.017620608,0.3123993,0.0011324957,0.00021888808,0.00008785169,0.001266112,0.0030123289,0.01867017],"genre_scores_gemma":[0.8772094,0.0038427836,0.10656343,0.00015520616,0.00010055863,0.000087833425,0.0017570081,0.0008018491,0.009481886],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99939847,0.000114570976,0.000028747665,0.000094154486,0.00026824267,0.00009577593],"domain_scores_gemma":[0.9982686,0.001150513,0.00011080341,0.00020717077,0.00021269944,0.000050197712],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006662497,0.00064557575,0.0005375686,0.001084714,0.0004444488,0.0013143984,0.0012572705,0.00078649516,0.0023384264],"category_scores_gemma":[0.004892778,0.00047385498,0.00047133406,0.0022587315,0.00050734024,0.0019209782,0.0006483921,0.0009578477,0.00031307037],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019507238,0.00018261085,0.015396036,0.00046319066,0.00015716538,0.00016269977,0.00031019992,0.74272406,0.015410442,0.020282455,0.008661744,0.19605426],"study_design_scores_gemma":[0.00000544599,0.000030153862,0.00222639,0.00003127908,0.000022542585,0.00005745761,0.00007661954,0.9747593,0.0039948905,0.017045913,0.0017385471,0.0000114471895],"about_ca_topic_score_codex":0.008156831,"about_ca_topic_score_gemma":0.013506768,"teacher_disagreement_score":0.008156831,"about_ca_system_score_codex":0.0010168212,"about_ca_system_score_gemma":0.0012437955,"threshold_uncertainty_score":0.016218722},"labels":[],"label_agreement":null},{"id":"W86291329","doi":"10.5555/1838206.1838253","title":"On learning in agent-centered search","year":2010,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":24,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Heuristic; Computer science; Convergence (economics); Measure (data warehouse); Unification; Process (computing); Domain (mathematical analysis); Artificial intelligence; Function (biology); Machine learning; Mathematics; Data mining","score_opus":0.03486345185458317,"score_gpt":0.29377014463131806,"score_spread":0.2589066927767349,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W86291329","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008415875,0.0023151361,0.9811674,0.00075760036,0.00009536354,0.00008395962,0.00004803597,0.00023412034,0.006882522],"genre_scores_gemma":[0.49095535,0.004246783,0.49429318,0.00097513635,0.0005574587,0.00079979695,0.00033298033,0.0003097684,0.0075295693],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99682415,0.0018134532,0.000135035,0.00039824826,0.0006276966,0.0002015196],"domain_scores_gemma":[0.98723966,0.010642915,0.00057359214,0.0006675102,0.0006122023,0.00026408283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005193069,0.0015153267,0.0023669899,0.0012073036,0.0007865162,0.0021341962,0.0028626416,0.0023380993,0.0033634512],"category_scores_gemma":[0.019361977,0.0007744469,0.00093309424,0.0023114856,0.0033200288,0.0038971342,0.0032004244,0.0029877024,0.0006794485],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016474999,0.00010685884,0.00066977553,0.00020435963,0.00011553524,0.000046509507,0.00013165841,0.7643533,0.00034542484,0.17787012,0.0020405701,0.05395125],"study_design_scores_gemma":[0.000048726983,0.00008767913,0.00013172367,0.000036698402,0.00001832464,0.000017405318,0.000014720751,0.82780683,0.00024473737,0.16990635,0.0016739977,0.000012693955],"about_ca_topic_score_codex":0.0038066888,"about_ca_topic_score_gemma":0.0029919297,"teacher_disagreement_score":0.005193069,"about_ca_system_score_codex":0.0021906483,"about_ca_system_score_gemma":0.0019290431,"threshold_uncertainty_score":0.027463913},"labels":[],"label_agreement":null},{"id":"W905866239","doi":"","title":"An approximate dynamic programming approach for semi-cooperative multi-agent resource management","year":2012,"lang":"en","type":"article","venue":"","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Resource management (computing); Dynamic programming; Distributed computing; Algorithm","score_opus":0.03760110983344896,"score_gpt":0.3068174748436359,"score_spread":0.269216365010187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W905866239","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0034689473,0.00014580383,0.99398017,0.00013484071,0.000031156218,0.000029358464,0.000026411168,0.00006214144,0.0021211356],"genre_scores_gemma":[0.60493326,0.0005720484,0.38642716,0.0001863638,0.00012048673,0.0005543928,0.0001487489,0.00014138693,0.006916227],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922895,0.00029567938,0.000034411834,0.000103244325,0.00025063203,0.00008708573],"domain_scores_gemma":[0.9985771,0.00094802264,0.00011424604,0.00008566798,0.0002035089,0.000071305476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017635293,0.0009103643,0.0019553134,0.0007722931,0.0007132673,0.0017086888,0.0023482153,0.0017709386,0.0030933644],"category_scores_gemma":[0.004743124,0.00085429434,0.0009155104,0.0012443151,0.0010510455,0.0019208218,0.0018484761,0.001378339,0.00033387917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000021776355,0.000016834701,0.00007058237,0.000030263356,0.000017700826,0.00002313882,0.0000241901,0.97514206,0.00015416784,0.016875587,0.00036220843,0.0072615203],"study_design_scores_gemma":[0.00000213983,0.0000045875036,0.000008772591,0.0000018149611,0.0000021505973,0.0000035492913,0.0000032360765,0.995952,0.000024546227,0.0038488617,0.00014701101,0.0000013946986],"about_ca_topic_score_codex":0.008116643,"about_ca_topic_score_gemma":0.005884287,"teacher_disagreement_score":0.008116643,"about_ca_system_score_codex":0.0013605283,"about_ca_system_score_gemma":0.0015921011,"threshold_uncertainty_score":0.016138792},"labels":[],"label_agreement":null},{"id":"W964625527","doi":"10.1007/978-3-642-36065-7_1","title":"Mobility and Computations: Some Open Research Directions","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Distributed computing; Focus (optics); Class (philosophy); Mobile robot; Robotics; Mobile computing; Software; Distributed algorithm; Task (project management); Artificial intelligence; Robot; Computer network; Systems engineering; Operating system","score_opus":0.08173406732485497,"score_gpt":0.35493234680769836,"score_spread":0.27319827948284336,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W964625527","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.033599846,0.17019038,0.516708,0.09258862,0.0067985235,0.00010410726,0.00076155755,0.00046548058,0.1787834],"genre_scores_gemma":[0.49057955,0.18997642,0.19236052,0.008388809,0.024939213,0.00039414936,0.0013030259,0.00088402716,0.09117426],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99855214,0.00051279645,0.0000831446,0.00034350523,0.00030760764,0.00020091457],"domain_scores_gemma":[0.9922208,0.0054391325,0.0002661407,0.0010480523,0.0006379259,0.00038798357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024082381,0.0012706352,0.0021345112,0.0020980223,0.002542182,0.00810992,0.003098561,0.0034636178,0.01852822],"category_scores_gemma":[0.011841873,0.00096776336,0.0018011609,0.0060792044,0.0070092594,0.02750426,0.004638087,0.0052299704,0.0028830692],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023454688,0.000036815185,0.00021534781,0.00018640746,0.00001490976,0.000029932933,0.00015791043,0.0026435365,0.00007446872,0.9546749,0.012165761,0.02977664],"study_design_scores_gemma":[0.0000038299404,0.000003776335,0.00006291558,0.00007191121,0.00000505543,0.000030957013,0.0001134173,0.004628507,0.000037850696,0.9841011,0.010933741,0.000006914034],"about_ca_topic_score_codex":0.0027445506,"about_ca_topic_score_gemma":0.0019193352,"teacher_disagreement_score":0.01852822,"about_ca_system_score_codex":0.0024471902,"about_ca_system_score_gemma":0.0016229546,"threshold_uncertainty_score":0.06198311},"labels":[],"label_agreement":null},{"id":"W98190632","doi":"10.1007/s00453-003-1018-5","title":"Multicast Pull Scheduling: When Fairness Is Fine","year":2003,"lang":"en","type":"article","venue":"Algorithmica","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Computer science; Multicast; Unicast; Scheduling (production processes); Computer network; Distributed computing; Competitive analysis; Approximation algorithm; Parallel computing; Algorithm; Mathematical optimization; Upper and lower bounds; Mathematics","score_opus":0.02439670081495226,"score_gpt":0.2598636974486351,"score_spread":0.2354669966336828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W98190632","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19277132,0.0015200293,0.74198574,0.015675597,0.0014773499,0.00017318179,0.00033520913,0.000892712,0.045168824],"genre_scores_gemma":[0.9581061,0.00023523471,0.031497914,0.00075038575,0.00059636676,0.000077602956,0.000058374066,0.00020127081,0.008476768],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99621296,0.0014267559,0.00014889009,0.0006889659,0.00058672554,0.00093567773],"domain_scores_gemma":[0.9740089,0.018496023,0.001383883,0.003030714,0.0014140309,0.0016664024],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010471126,0.00070766226,0.0021270178,0.00086227333,0.0029745856,0.005290375,0.002570725,0.0033662333,0.008556717],"category_scores_gemma":[0.056853928,0.0008891379,0.0006001685,0.0010478706,0.0028679264,0.010908154,0.0037284987,0.004200865,0.00062716054],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0018620576,0.00033914484,0.005853156,0.0002506352,0.0001314472,0.00043604994,0.00080391497,0.12265402,0.0030290575,0.7558997,0.022136224,0.0866045],"study_design_scores_gemma":[0.00008801359,0.000055815453,0.0005098386,0.000029048004,0.000040605562,0.0001284813,0.00027794286,0.23468748,0.0008058666,0.7594009,0.003955331,0.000020659107],"about_ca_topic_score_codex":0.0016393876,"about_ca_topic_score_gemma":0.0018582519,"teacher_disagreement_score":0.010471126,"about_ca_system_score_codex":0.0019313378,"about_ca_system_score_gemma":0.0025687597,"threshold_uncertainty_score":0.055377245},"labels":[],"label_agreement":null}]}