{"meta":{"query_hash":"8592977682df","filters":{"topic":"Speech and dialogue systems"},"cohort_total":477,"direct_labels_cover":1,"predictions_cover":477,"exported":477,"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/8592977682df","api":"https://metacan.xera.ac/api/v1/cohort?topic=Speech+and+dialogue+systems"},"results":[{"id":"W1047586780","doi":"10.11575/prism/24624","title":"5-year-olds' Use of Disfluency and Speaker Identity in Referential Communication","year":2015,"lang":"en","type":"dissertation","venue":"PRISM (University of Calgary)","topic":"Speech and dialogue systems","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":"Social Sciences and Humanities Research Council of Canada","keywords":"Identity (music); Psychology; Linguistics; Communication; Art; Philosophy","score_opus":0.02147492732115504,"score_gpt":0.23943605124953005,"score_spread":0.217961123928375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1047586780","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":[0.99884796,0.0001690131,0.00007160677,0.00001543985,0.000012756069,0.000005861558,0.00005693141,0.000007005686,0.00081348064],"genre_scores_gemma":[0.9978684,0.00016967076,0.00018284371,0.000042118107,0.000004122294,0.000013005219,0.00011406614,0.00000247675,0.0016031001],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9996394,0.000028016102,0.00004460425,0.00009441117,0.000088692104,0.000104974206],"domain_scores_gemma":[0.99834716,0.0004422276,0.00051768,0.00012180503,0.0002496385,0.00032143117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013095089,0.0004293883,0.00028443115,0.00082745287,0.00036766683,0.0012850405,0.00029640977,0.00061449624,0.0024014623],"category_scores_gemma":[0.0022002356,0.00030459647,0.00028783485,0.0001434388,0.0005711129,0.00062720326,0.00055453513,0.0006777763,0.0005785073],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015746893,0.0013881669,0.68338406,0.00026094378,0.000103018574,0.004512918,0.035549782,0.0001651029,0.22428273,0.00095103536,0.0010899816,0.046737496],"study_design_scores_gemma":[0.000022760403,0.0008995855,0.9810284,0.00006108859,0.00007889371,0.001297239,0.005342764,0.00015155459,0.009222087,0.0001877352,0.0016765833,0.00003128869],"about_ca_topic_score_codex":0.0055926186,"about_ca_topic_score_gemma":0.0075653777,"teacher_disagreement_score":0.0055926186,"about_ca_system_score_codex":0.00026019636,"about_ca_system_score_gemma":0.0002378987,"threshold_uncertainty_score":0.011120141},"labels":[],"label_agreement":null},{"id":"W128216859","doi":"","title":"Using X+V to construct a non-proprietary speech browser for a public-domain SpeechWeb","year":2006,"lang":"en","type":"dissertation","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Speech and dialogue systems","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":"Construct (python library); Public domain; Domain (mathematical analysis); Computer science; Natural language processing; World Wide Web; Programming language; Mathematics; History","score_opus":0.03609434198741233,"score_gpt":0.25353960813018966,"score_spread":0.21744526614277734,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W128216859","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022686707,0.00008159887,0.91859573,0.00012931378,0.00007808698,0.00044017067,0.00027126676,0.046640903,0.011076205],"genre_scores_gemma":[0.09750382,0.00034008894,0.8495028,0.00021083641,0.000037109297,0.0008659717,0.0016569657,0.012597888,0.03728457],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995259,0.00009698754,0.000061489154,0.000128493,0.00013156247,0.00005555214],"domain_scores_gemma":[0.99908876,0.00038657436,0.00007089803,0.00022443055,0.00015875007,0.00007055955],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010727436,0.00063798146,0.00028586248,0.0003855781,0.00040875265,0.0016757669,0.0010278573,0.0006079554,0.007957047],"category_scores_gemma":[0.002093707,0.00065947475,0.00056401285,0.00028525537,0.0005548487,0.002261876,0.0016136349,0.0012580694,0.004840804],"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":[0.0011041445,0.00057775376,0.008488836,0.0011854336,0.00015946169,0.0022951306,0.0056898724,0.014066073,0.19804622,0.14661957,0.06657756,0.5551901],"study_design_scores_gemma":[0.0003861596,0.000476279,0.0036496061,0.00034212923,0.00014208173,0.0023965845,0.0005927654,0.13598232,0.2321526,0.019113375,0.6045994,0.00016666701],"about_ca_topic_score_codex":0.0010303187,"about_ca_topic_score_gemma":0.0010262904,"teacher_disagreement_score":0.007957047,"about_ca_system_score_codex":0.00028865377,"about_ca_system_score_gemma":0.0008990968,"threshold_uncertainty_score":0.026618958},"labels":[],"label_agreement":null},{"id":"W128748169","doi":"","title":"Koordination multimodaler Metainformationen bei Fahrerinformationssystemen am Beispiel der Menüausgabe","year":2002,"lang":"de","type":"article","venue":"Ingénierie des systèmes d information","topic":"Speech and dialogue systems","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":"Variety (cybernetics); Prime (order theory); Computer science; Mode (computer interface); Component (thermodynamics); Human–computer interaction; Multimedia; Artificial intelligence; Mathematics","score_opus":0.023672426215581452,"score_gpt":0.2277505807699949,"score_spread":0.20407815455441347,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W128748169","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":[0.8126916,0.0012177237,0.17896333,0.00024385708,0.000034906523,0.00015675378,0.00008191451,0.001843589,0.0047663646],"genre_scores_gemma":[0.95991796,0.00025466853,0.03821821,0.000033740016,0.000009812145,0.00006492787,0.00006555879,0.0001258746,0.0013091959],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.997867,0.0010083452,0.00011054851,0.00022026982,0.00062575075,0.00016818885],"domain_scores_gemma":[0.9943486,0.0042170165,0.00030866713,0.00048104714,0.0005256046,0.00011907922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027625968,0.0008916049,0.0006225951,0.0010010822,0.00075780076,0.0023890007,0.00056669285,0.0015110169,0.0028712677],"category_scores_gemma":[0.008887348,0.00043357653,0.000396203,0.00058187003,0.0012674448,0.002863257,0.0015199526,0.0007901739,0.00064685923],"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":[0.00446709,0.000568177,0.009627214,0.0012976922,0.00022453864,0.0067320075,0.013981237,0.036283813,0.5830965,0.016000027,0.0010490621,0.3266726],"study_design_scores_gemma":[0.00027633502,0.00483216,0.024976704,0.0003097448,0.00058824604,0.010088978,0.0066628763,0.2912554,0.60451806,0.034266457,0.02182347,0.0004015447],"about_ca_topic_score_codex":0.00050751877,"about_ca_topic_score_gemma":0.0006524601,"teacher_disagreement_score":0.0028712677,"about_ca_system_score_codex":0.00045235615,"about_ca_system_score_gemma":0.0002646304,"threshold_uncertainty_score":0.014610231},"labels":[],"label_agreement":null},{"id":"W13152932","doi":"10.21437/eurospeech.2003-482","title":"Should i tell all?: an experiment on conciseness in spoken dialogue","year":2003,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Toronto","funders":"","keywords":"Computer science; Selection (genetic algorithm); Utterance; Pruning; Set (abstract data type); Phone; Domain (mathematical analysis); Natural language processing; Artificial intelligence; Linguistics","score_opus":0.0728376366000513,"score_gpt":0.30783520324597674,"score_spread":0.23499756664592544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W13152932","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":[0.9895956,0.00019416254,0.005509888,0.00029629018,0.00007676505,0.00041075094,0.000254499,0.00042817905,0.003233792],"genre_scores_gemma":[0.9733725,0.00020452993,0.020363484,0.0005472633,0.00007922023,0.0013344965,0.00074227806,0.0001744792,0.0031818112],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9894755,0.00769303,0.00092491234,0.0009505605,0.0007633253,0.00019275899],"domain_scores_gemma":[0.737283,0.24770176,0.0041599474,0.0054976647,0.002480918,0.0028767847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010786924,0.0010395413,0.00097468763,0.0005503052,0.00091379404,0.0021363308,0.0014310878,0.0017331409,0.0068606944],"category_scores_gemma":[0.10300716,0.0007585168,0.00044167083,0.00037756556,0.0010721296,0.0041078418,0.0017967245,0.0024861074,0.0015123752],"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":[0.076682195,0.05387166,0.049676474,0.0078056664,0.0013375757,0.0035737944,0.16077183,0.015629783,0.2509185,0.009582169,0.018255519,0.35189486],"study_design_scores_gemma":[0.02493392,0.20463026,0.15849113,0.0014668157,0.0030031104,0.005339842,0.04486763,0.28099298,0.17156662,0.041864462,0.061000526,0.0018427273],"about_ca_topic_score_codex":0.00065434765,"about_ca_topic_score_gemma":0.00046018197,"teacher_disagreement_score":0.010786924,"about_ca_system_score_codex":0.00035068655,"about_ca_system_score_gemma":0.00044122306,"threshold_uncertainty_score":0.057047367},"labels":[],"label_agreement":null},{"id":"W133592964","doi":"10.4018/978-1-60566-246-6.ch010","title":"Natural Human-System Interaction Using Intelligent Conversational Agents","year":2009,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Speech and dialogue systems","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 Moncton","funders":"","keywords":"Computer science; Naturalness; Natural language; Natural language understanding; Chatbot; Human–computer interaction; Dialog system; Markup language; Context (archaeology); Artificial intelligence; Natural language generation; Natural language processing; World Wide Web; Dialog box; XML","score_opus":0.0479104510711022,"score_gpt":0.2893521677076872,"score_spread":0.24144171663658498,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W133592964","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":[0.021714885,0.007897366,0.73389286,0.002393335,0.0002780024,0.00026319356,0.00014451335,0.0030119687,0.23040386],"genre_scores_gemma":[0.41888556,0.0057582,0.45014036,0.0011402122,0.0002752877,0.0008048776,0.00053697155,0.0005189903,0.12193958],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922323,0.00039751598,0.00003649007,0.000121804194,0.00017517872,0.00004573817],"domain_scores_gemma":[0.99938285,0.0004335328,0.000027818152,0.00007746337,0.000038085323,0.000040280018],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085268077,0.0007456711,0.00031387308,0.0004477668,0.0009131808,0.0034829194,0.0012910229,0.0014902559,0.009021938],"category_scores_gemma":[0.0013891424,0.0003458051,0.0003752933,0.0003673142,0.0017184345,0.0029943048,0.0021566502,0.0010394279,0.0034118062],"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":[0.00012268341,0.00018855804,0.00076465955,0.0015393483,0.000084764535,0.0012148984,0.011720548,0.016324975,0.04248996,0.45990852,0.034317307,0.43132392],"study_design_scores_gemma":[0.000042246924,0.00014054163,0.0007850685,0.000373934,0.00005074192,0.0015872709,0.0012429592,0.06997274,0.011122572,0.21801601,0.69659734,0.00006858223],"about_ca_topic_score_codex":0.0006052029,"about_ca_topic_score_gemma":0.000743485,"teacher_disagreement_score":0.009021938,"about_ca_system_score_codex":0.0005757781,"about_ca_system_score_gemma":0.00057806144,"threshold_uncertainty_score":0.030181408},"labels":[],"label_agreement":null},{"id":"W144220174","doi":"10.21437/interspeech.2009-578","title":"Detecting subjectivity in multiparty speech","year":2009,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of British Columbia","funders":"","keywords":"Robustness (evolution); Computer science; Speech recognition; Subjectivity; Artificial intelligence; Natural language processing; Polarity (international relations)","score_opus":0.015045728569397145,"score_gpt":0.24564807344168715,"score_spread":0.23060234487229,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W144220174","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":[0.55838346,0.0008757272,0.4256594,0.00039519128,0.00021804249,0.00020734798,0.00091944804,0.0007866297,0.012554683],"genre_scores_gemma":[0.94655734,0.00029700485,0.049490403,0.000088199384,0.00020808345,0.00010190661,0.000606564,0.000074474185,0.0025760254],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9975375,0.0011018637,0.00013005773,0.0005891637,0.0005344522,0.00010700707],"domain_scores_gemma":[0.99243766,0.0046659317,0.0011241775,0.00088827446,0.000680035,0.0002040031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018261645,0.0004751857,0.00045753308,0.0013021531,0.00051179744,0.0012824337,0.00041885895,0.0007801132,0.0011968458],"category_scores_gemma":[0.0076709874,0.0002608847,0.0003408052,0.0006942863,0.00061876944,0.0013675262,0.0012271134,0.00065455626,0.0007262138],"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":[0.0010007778,0.00026270474,0.1024587,0.00063993275,0.00024250106,0.0013752753,0.004567106,0.010962551,0.3336201,0.01021685,0.0027234554,0.5319301],"study_design_scores_gemma":[0.00007911182,0.001211626,0.32337442,0.0002640161,0.0003129378,0.0042698863,0.003834814,0.3303028,0.2553462,0.052233472,0.02846194,0.00030886664],"about_ca_topic_score_codex":0.0003754458,"about_ca_topic_score_gemma":0.0007571089,"teacher_disagreement_score":0.0018261645,"about_ca_system_score_codex":0.00024034227,"about_ca_system_score_gemma":0.00022977384,"threshold_uncertainty_score":0.0096578},"labels":[],"label_agreement":null},{"id":"W1483183099","doi":"","title":"Techniques d'interaction multimodales pour l'acces aux mathematiques par des personnes non-voyantes","year":2009,"lang":"fr","type":"article","venue":"Espace École de technologie supérieure (École de technologie supérieure)","topic":"Speech and dialogue systems","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":"École de Technologie Supérieure","funders":"","keywords":"Humanities; Art; Computer science","score_opus":0.03546807953162701,"score_gpt":0.3072543210879277,"score_spread":0.2717862415563007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1483183099","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012241742,0.0018515105,0.9616754,0.0011370322,0.00033052498,0.00023607771,0.00016085229,0.004775881,0.01759091],"genre_scores_gemma":[0.16396457,0.0043104403,0.7938385,0.0008160004,0.00026485088,0.0009448444,0.0006378625,0.00159278,0.033630196],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99546707,0.0018050615,0.0002956238,0.0007209027,0.0014883353,0.00022297751],"domain_scores_gemma":[0.99449074,0.0030807073,0.00026290343,0.00073753623,0.001205147,0.00022284169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028349024,0.0016493395,0.0012662647,0.0012351332,0.0014280948,0.004840641,0.001987339,0.0021687967,0.027359363],"category_scores_gemma":[0.012727399,0.0008361449,0.0018069716,0.000946286,0.0016148168,0.0052319826,0.0050274073,0.0025863477,0.007153317],"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":[0.0007541642,0.00032926293,0.0021407933,0.0027686227,0.00028352614,0.0010219797,0.0140418345,0.009444488,0.10796281,0.09353886,0.020199686,0.747514],"study_design_scores_gemma":[0.00018148834,0.00095380825,0.0055208537,0.0015401255,0.00042925178,0.0032420992,0.0069141695,0.1393995,0.08993881,0.08235769,0.6690741,0.0004481324],"about_ca_topic_score_codex":0.002278862,"about_ca_topic_score_gemma":0.002585424,"teacher_disagreement_score":0.027359363,"about_ca_system_score_codex":0.0007958399,"about_ca_system_score_gemma":0.0014774885,"threshold_uncertainty_score":0.09152621},"labels":[],"label_agreement":null},{"id":"W148997979","doi":"10.4018/978-1-60566-934-2.ch010","title":"Enhanced Speech-Enabled Tools for Intelligent and Mobile E-Learning Applications","year":2010,"lang":"en","type":"book-chapter","venue":"Advances in distance education technologies series/Advances in distance education technologies (ADET) series","topic":"Speech and dialogue systems","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":"Institut National de la Recherche Scientifique; Université de Moncton","funders":"","keywords":"Computer science; Multimedia; Software portability; World Wide Web; Human–computer interaction; Context (archaeology)","score_opus":0.007882255086010655,"score_gpt":0.2689904447242292,"score_spread":0.2611081896382186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W148997979","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":[0.12819229,0.0065670414,0.7959599,0.0005270406,0.0004868921,0.0006621056,0.0013425366,0.023943184,0.04231899],"genre_scores_gemma":[0.45384464,0.004183464,0.45622957,0.00073520845,0.00023365577,0.00067746075,0.0018738409,0.0012981705,0.08092405],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99966073,0.00007569713,0.000028145407,0.000037142407,0.00016896652,0.000029370603],"domain_scores_gemma":[0.99942577,0.00032699568,0.000034378852,0.00006198903,0.00012104634,0.000029851695],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037561168,0.00050026126,0.00022029865,0.00049521535,0.00017319815,0.00087745703,0.0006451277,0.0006397107,0.013822573],"category_scores_gemma":[0.0014901905,0.00018138577,0.00028815362,0.00028306205,0.00018106987,0.0010505185,0.00073795364,0.00042441158,0.004749156],"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":[0.0005440067,0.00022016012,0.00069391745,0.0011005215,0.000044601733,0.0007716711,0.000700931,0.0026895967,0.2588413,0.009333754,0.011891284,0.7131683],"study_design_scores_gemma":[0.00027798093,0.0016085004,0.009754267,0.0005908689,0.000253469,0.0045842235,0.00058898365,0.06712265,0.35892743,0.0093106795,0.546777,0.00020397674],"about_ca_topic_score_codex":0.0002488787,"about_ca_topic_score_gemma":0.0005095257,"teacher_disagreement_score":0.013822573,"about_ca_system_score_codex":0.0001821954,"about_ca_system_score_gemma":0.00023598818,"threshold_uncertainty_score":0.046241164},"labels":[],"label_agreement":null},{"id":"W1504556233","doi":"10.1007/11424918_41","title":"A Novel Use of VXML to Construct a Speech Browser for a Public-Domain SpeechWeb","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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":"Computer science; Markup language; Software deployment; Architecture; Public domain; Domain (mathematical analysis); Interpreter; Construct (python library); World Wide Web; Speech synthesis; Speech recognition; XML; Software engineering; Programming language","score_opus":0.04282828798878529,"score_gpt":0.25430026013985463,"score_spread":0.21147197215106933,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1504556233","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":[0.007667521,0.00007742271,0.91675067,0.00020294164,0.00014140841,0.00015294547,0.00026866433,0.068720356,0.006018094],"genre_scores_gemma":[0.21165638,0.00026406336,0.72931874,0.00048597943,0.00012239451,0.00033280117,0.0018669959,0.024918891,0.031033836],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.998808,0.00023684531,0.00011474585,0.0002519518,0.0004746061,0.00011375034],"domain_scores_gemma":[0.9974794,0.0009306732,0.00011032477,0.00090508815,0.000337759,0.00023684966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015299458,0.0009135515,0.0006155886,0.00095346273,0.00077513984,0.004725435,0.0026613607,0.0017603826,0.012872542],"category_scores_gemma":[0.0054933657,0.0012194825,0.00097112264,0.00059617276,0.0013053586,0.0050473893,0.004535445,0.002838068,0.0051169107],"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":[0.00171845,0.0009415964,0.0063863564,0.0009551246,0.00033723644,0.0036030186,0.009189822,0.010629042,0.26143646,0.17738907,0.07905956,0.4483542],"study_design_scores_gemma":[0.00038105025,0.00041417207,0.0016031512,0.000238761,0.0002929336,0.0029665485,0.0007556511,0.2070265,0.335865,0.036963467,0.41317657,0.00031621673],"about_ca_topic_score_codex":0.0025143272,"about_ca_topic_score_gemma":0.0029610756,"teacher_disagreement_score":0.012872542,"about_ca_system_score_codex":0.0005765886,"about_ca_system_score_gemma":0.0009829538,"threshold_uncertainty_score":0.043062985},"labels":[],"label_agreement":null},{"id":"W1507809214","doi":"10.4995/eurocall.2012.16052","title":"In search of the optimal path: How learners at task use an online dictionary","year":2012,"lang":"en","type":"article","venue":"The EuroCALL Review","topic":"Speech and dialogue systems","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 Ottawa","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Computer science; Task (project management); Path (computing); Encoding (memory); Artificial intelligence; Human–computer interaction; Multimedia; Natural language processing; Programming language","score_opus":0.08999045148197544,"score_gpt":0.29531635425247005,"score_spread":0.20532590277049462,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1507809214","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":[0.99136096,0.0008461193,0.0036330647,0.00011895603,0.0000083594905,0.000023279632,0.00003645879,0.000026432645,0.003946412],"genre_scores_gemma":[0.9917105,0.001281565,0.0031232839,0.00003814508,0.0000044702165,0.000024491577,0.0000713111,0.000022025513,0.0037241718],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99897575,0.00047346597,0.000051948195,0.00018435704,0.00022203416,0.00009250449],"domain_scores_gemma":[0.997198,0.0016240972,0.000347205,0.00012506566,0.0005164304,0.00018927261],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015924915,0.00024453198,0.00028447292,0.00060511153,0.00036347815,0.002193329,0.0005543129,0.00074752525,0.0018688693],"category_scores_gemma":[0.010247354,0.00015592882,0.00016945518,0.0004750648,0.0006454696,0.0017410467,0.00062687555,0.0004601835,0.0009822606],"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":[0.00057597226,0.0007000803,0.36244062,0.0008662676,0.00009714046,0.0021499791,0.1722557,0.004721549,0.036418907,0.0059838626,0.0029017094,0.4108882],"study_design_scores_gemma":[0.000104564,0.003367474,0.4893303,0.0007898368,0.00029915653,0.006639173,0.31666356,0.020368591,0.046741504,0.013685807,0.101564065,0.00044595447],"about_ca_topic_score_codex":0.002440917,"about_ca_topic_score_gemma":0.0032855165,"teacher_disagreement_score":0.002440917,"about_ca_system_score_codex":0.00032998784,"about_ca_system_score_gemma":0.00064506405,"threshold_uncertainty_score":0.0084219575},"labels":[],"label_agreement":null},{"id":"W1511322390","doi":"10.1109/icsmc.1988.712924","title":"Towards a Better Aid for the Blind: A Talking Stenograph Stenex","year":2005,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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","score_opus":0.02661470097922046,"score_gpt":0.26100471243803985,"score_spread":0.23439001145881938,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1511322390","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31517974,0.007358653,0.4686963,0.033237144,0.008415169,0.0010870986,0.000999777,0.018128818,0.14689733],"genre_scores_gemma":[0.4169699,0.0038250587,0.35932377,0.0060977163,0.00089765876,0.00047337293,0.0005801319,0.0012763116,0.21055618],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9988244,0.0003785901,0.00007566951,0.0002027744,0.0003360882,0.00018230309],"domain_scores_gemma":[0.9990165,0.00018284662,0.000021188209,0.000100368416,0.0002717092,0.00040730275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018954733,0.0011858711,0.0009846945,0.00081183505,0.003883768,0.0040295776,0.0013183119,0.005201708,0.02211168],"category_scores_gemma":[0.0025960663,0.00043771917,0.00054040184,0.0002809201,0.0021496906,0.004380635,0.0049241576,0.0025495975,0.0062652933],"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":[0.0029026845,0.0014919275,0.005869066,0.0022150448,0.00013724771,0.013244305,0.02711243,0.0025665113,0.17207044,0.05459935,0.10603589,0.61175513],"study_design_scores_gemma":[0.00051845063,0.003970732,0.004254623,0.0013648573,0.0004984093,0.04525361,0.022487719,0.013597022,0.088603094,0.03229227,0.7865666,0.0005924976],"about_ca_topic_score_codex":0.0031383648,"about_ca_topic_score_gemma":0.0043198597,"teacher_disagreement_score":0.02211168,"about_ca_system_score_codex":0.00059462356,"about_ca_system_score_gemma":0.0020881868,"threshold_uncertainty_score":0.07397097},"labels":[],"label_agreement":null},{"id":"W1511589452","doi":"10.1007/3-540-39965-8_3","title":"Mixed-Initiative Translation of Web Pages","year":2000,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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; Interactivity; World Wide Web; Task (project management); Web page; Human–computer interaction; Engineering","score_opus":0.036355393811706105,"score_gpt":0.23884201340687405,"score_spread":0.20248661959516795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1511589452","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":[0.09131678,0.0027209576,0.7822646,0.0011859778,0.0018903307,0.0005891879,0.004403231,0.019738108,0.095890835],"genre_scores_gemma":[0.4949056,0.0014372022,0.43162766,0.00031110193,0.00027525562,0.0003610329,0.010087954,0.004657381,0.056336667],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985592,0.000605728,0.00010937309,0.00022574514,0.00039828513,0.00010164337],"domain_scores_gemma":[0.99643916,0.0016397001,0.00011866003,0.00070758816,0.0009963074,0.000098633674],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012096248,0.0008436864,0.00074803474,0.0010016441,0.0007071044,0.0031329677,0.0013474424,0.0010617812,0.017133575],"category_scores_gemma":[0.0065428037,0.0007537499,0.00061913574,0.0014801361,0.0005164465,0.0029094466,0.0021611494,0.0011561255,0.010656316],"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":[0.0013925077,0.0004422676,0.0009968722,0.0022875478,0.00014585348,0.0017445834,0.0040688985,0.008618465,0.07180585,0.073401004,0.052418478,0.7826776],"study_design_scores_gemma":[0.00023138615,0.0006990356,0.0020895158,0.0006205652,0.0003321453,0.002626759,0.002998141,0.18947457,0.36447683,0.081507735,0.354739,0.0002043092],"about_ca_topic_score_codex":0.0010152918,"about_ca_topic_score_gemma":0.0016706446,"teacher_disagreement_score":0.017133575,"about_ca_system_score_codex":0.0004541754,"about_ca_system_score_gemma":0.00073750236,"threshold_uncertainty_score":0.057317495},"labels":[],"label_agreement":null},{"id":"W1512230024","doi":"10.1109/icassp.1995.479398","title":"Understanding referring expressions in a person-machine spoken dialogue","year":2002,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Natural language processing; Speech recognition; Artificial intelligence; Linguistics","score_opus":0.22276036222868956,"score_gpt":0.2542107702734163,"score_spread":0.03145040804472676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1512230024","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07741066,0.0010305329,0.9104362,0.0017064037,0.00007709385,0.00012877968,0.00021894112,0.0012371867,0.007754331],"genre_scores_gemma":[0.71942896,0.0007749289,0.2750034,0.00046126443,0.00010752612,0.00017337945,0.00051117485,0.0001854123,0.003353951],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9954177,0.0030019444,0.0002370597,0.0006339155,0.0005554662,0.00015390372],"domain_scores_gemma":[0.99564713,0.0031809239,0.00045321227,0.00025245483,0.0003887694,0.000077593286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004154762,0.0007922918,0.00075231044,0.001434079,0.001399273,0.0042258753,0.001468777,0.0028705047,0.002489101],"category_scores_gemma":[0.013268699,0.0005129089,0.00085570005,0.0010584162,0.0028839412,0.0097290035,0.0031109243,0.0015589708,0.0006315416],"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":[0.000523832,0.0001216666,0.0019822677,0.00079447054,0.00012814524,0.0026019916,0.06977623,0.052220352,0.04118983,0.67510045,0.00604476,0.14951593],"study_design_scores_gemma":[0.000058875154,0.00014050346,0.0017997312,0.00018860327,0.00011437577,0.00091399235,0.011195142,0.41922975,0.012345748,0.5270484,0.026782224,0.00018279192],"about_ca_topic_score_codex":0.003826619,"about_ca_topic_score_gemma":0.0019727855,"teacher_disagreement_score":0.0042258753,"about_ca_system_score_codex":0.0013051268,"about_ca_system_score_gemma":0.00066485495,"threshold_uncertainty_score":0.021972716},"labels":[],"label_agreement":null},{"id":"W1515737728","doi":"10.1007/978-3-642-02017-9_40","title":"An Online Algorithm for Applying Reinforcement Learning to Handle Ambiguity in Spoken Dialogues","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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 Guelph","funders":"","keywords":"Computer science; Reinforcement learning; Ambiguity; Artificial intelligence; Natural language; Online learning; Reinforcement; Human–computer interaction; Natural language processing; Multimedia; Programming language","score_opus":0.03491495359236249,"score_gpt":0.2726276674597225,"score_spread":0.23771271386736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1515737728","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":[0.006393829,0.00007020298,0.99125284,0.00006537942,0.00006494559,0.000077474826,0.00001830563,0.0012455619,0.00081137876],"genre_scores_gemma":[0.26852903,0.00007846695,0.72682625,0.00016620342,0.0000630683,0.00039447396,0.00010365265,0.00019598196,0.003642807],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99922514,0.00021796893,0.000053027154,0.00022129802,0.00017983477,0.000102710466],"domain_scores_gemma":[0.9981694,0.0011577005,0.000084583306,0.00012976461,0.00035213854,0.00010634296],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018730529,0.00093323295,0.0014724146,0.00060995336,0.00069923524,0.00090479705,0.0026797329,0.0019525376,0.005665958],"category_scores_gemma":[0.004330754,0.0006183423,0.0005592803,0.0005178926,0.0009333432,0.0013831134,0.0021423795,0.001944741,0.0010715869],"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":[0.00042743582,0.0003613792,0.00064861675,0.00010303266,0.000066412336,0.000112591624,0.00015173099,0.35215402,0.0065391567,0.011388123,0.0038005472,0.62424695],"study_design_scores_gemma":[0.0000372047,0.00003135894,0.00004240587,0.000003949197,0.0000056819977,0.00001469949,0.0000063608045,0.99627364,0.0007803707,0.0025075027,0.00029178572,0.000005025049],"about_ca_topic_score_codex":0.0069141765,"about_ca_topic_score_gemma":0.0053325193,"teacher_disagreement_score":0.0069141765,"about_ca_system_score_codex":0.001003851,"about_ca_system_score_gemma":0.0016912364,"threshold_uncertainty_score":0.018954515},"labels":[],"label_agreement":null},{"id":"W1515995405","doi":"","title":"Effect of Age on Lexical Decision Speed When Sentence Context Is Acoustically Distorted","year":2010,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Speech and dialogue systems","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":"Sentence; Context (archaeology); Acoustics; Computer science; Speech recognition; Artificial intelligence; Geology; Physics","score_opus":0.009869301331223487,"score_gpt":0.23843438304178988,"score_spread":0.2285650817105664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1515995405","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":[0.999169,0.00014814547,0.0001181256,0.000024854586,0.000025584219,0.0000104798855,0.00011255296,0.000008618479,0.00038254014],"genre_scores_gemma":[0.9985662,0.00012654299,0.0002624646,0.000032533288,0.00001551747,0.00003052829,0.00013047077,0.000015254561,0.0008204785],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99955267,0.00008775107,0.00007549041,0.00012261754,0.00009235167,0.000069038055],"domain_scores_gemma":[0.99437815,0.003252657,0.00097045803,0.00035147762,0.00033758846,0.00070967287],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007864187,0.00041811392,0.0006593145,0.00031559754,0.0001635216,0.00061802205,0.00023862586,0.00042550193,0.003792603],"category_scores_gemma":[0.00697983,0.00023746496,0.00021104718,0.00019478974,0.00031737593,0.00044059136,0.0003448167,0.0005074752,0.0005068765],"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":[0.16196886,0.0052739386,0.23381825,0.0003378301,0.00031265593,0.002263418,0.002875989,0.00084235996,0.552182,0.00020579057,0.00086073176,0.039058205],"study_design_scores_gemma":[0.0009437448,0.026946817,0.88677436,0.000044182678,0.0005125004,0.0013420247,0.00072092237,0.002160421,0.07830522,0.00035886694,0.0018013378,0.00008948191],"about_ca_topic_score_codex":0.001208624,"about_ca_topic_score_gemma":0.0009480399,"teacher_disagreement_score":0.003792603,"about_ca_system_score_codex":0.00018036219,"about_ca_system_score_gemma":0.00021017407,"threshold_uncertainty_score":0.012687564},"labels":[],"label_agreement":null},{"id":"W1518061492","doi":"","title":"Gender Differences in Automatic Phonetic Accommodation","year":2010,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Speech and dialogue systems","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":"Accommodation; Speech recognition; Computer science; Psychology","score_opus":0.021356215410706127,"score_gpt":0.21992727552535224,"score_spread":0.19857106011464612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1518061492","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":[0.9533464,0.00065276754,0.0020703461,0.00019084323,0.00013502878,0.000047884252,0.00083924434,0.00009428956,0.042623233],"genre_scores_gemma":[0.9928873,0.00012695369,0.00059358805,0.00006385702,0.000014616412,0.000012383217,0.00045270097,0.00009966353,0.0057488894],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.998743,0.00029793874,0.000072130606,0.00022848329,0.00037028894,0.00028823942],"domain_scores_gemma":[0.9954602,0.001713809,0.0002930187,0.00040740904,0.001770641,0.0003549102],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013724184,0.0002814874,0.00033154024,0.00080682634,0.00083276205,0.0024017012,0.0005378369,0.0006386087,0.01328036],"category_scores_gemma":[0.011995759,0.00046861568,0.00029423134,0.0005483567,0.0006589153,0.0008168073,0.0010447028,0.0005585518,0.0030651633],"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":[0.0054802173,0.00034744086,0.21431322,0.0003225796,0.00021072871,0.0012427114,0.02059781,0.0016164051,0.54350847,0.010980129,0.005399576,0.19598077],"study_design_scores_gemma":[0.00003903723,0.00021957973,0.9769791,0.00006993115,0.000046706922,0.0007505434,0.002844037,0.0019273326,0.011023203,0.0016022543,0.0044423873,0.00005593409],"about_ca_topic_score_codex":0.054280378,"about_ca_topic_score_gemma":0.084811896,"teacher_disagreement_score":0.054280378,"about_ca_system_score_codex":0.0010421542,"about_ca_system_score_gemma":0.0016681929,"threshold_uncertainty_score":0.10792887},"labels":[],"label_agreement":null},{"id":"W1522603807","doi":"","title":"The effect of an emotional carrier phrase on word recognition","year":2011,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Speech and dialogue systems","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":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Intelligibility (philosophy); Sentence; Phrase; Speech perception; Perception; Speech recognition; Psychology; Cognition; Speech processing; Computer science; Cognitive psychology; Natural language processing","score_opus":0.021169251759508317,"score_gpt":0.21402945241329155,"score_spread":0.19286020065378323,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1522603807","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":[0.9951933,0.00026163395,0.0009026483,0.000070605034,0.00014342854,0.00005429452,0.0000588634,0.000067303845,0.003247881],"genre_scores_gemma":[0.9951997,0.00018585293,0.0016877354,0.00021190749,0.00006128206,0.00006609988,0.00015407235,0.00012473055,0.0023085838],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99902177,0.00040811868,0.00013164015,0.00014861661,0.00019348059,0.000096398486],"domain_scores_gemma":[0.981793,0.016181974,0.0005232574,0.00051827217,0.00050603994,0.00047743012],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012744009,0.00065172056,0.0006337772,0.0001846919,0.00025693834,0.0009392594,0.0004805894,0.0010095254,0.010770135],"category_scores_gemma":[0.024620416,0.0003765772,0.00024511694,0.00013534412,0.00065420853,0.0010017009,0.00080801005,0.0006288874,0.0016896309],"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":[0.03894207,0.0007972676,0.0033506318,0.00054605934,0.000071588336,0.00092331856,0.0013970302,0.00031258274,0.9158141,0.00024249453,0.00052275247,0.037080016],"study_design_scores_gemma":[0.005172863,0.110837415,0.34458724,0.00034775442,0.001610388,0.0076779267,0.0029635872,0.015544674,0.5002502,0.0033035171,0.007414874,0.00028963594],"about_ca_topic_score_codex":0.0009074308,"about_ca_topic_score_gemma":0.0005856781,"teacher_disagreement_score":0.010770135,"about_ca_system_score_codex":0.00016623506,"about_ca_system_score_gemma":0.00023610475,"threshold_uncertainty_score":0.036029696},"labels":[],"label_agreement":null},{"id":"W1523191298","doi":"","title":"Live Chat / E-Mail in SLA: Two tools, two methods, one outcome.","year":2007,"lang":"en","type":"article","venue":"EdMedia: World Conference on Educational Media and Technology","topic":"Speech and dialogue systems","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 Victoria","funders":"","keywords":"Outcome (game theory); Computer science; Opt-in email; Chat room; World Wide Web; The Internet; Mathematics","score_opus":0.08528008507850308,"score_gpt":0.36119499371004055,"score_spread":0.27591490863153745,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1523191298","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":[0.7499302,0.001513631,0.1661116,0.0023913884,0.00059412053,0.008431843,0.0039068637,0.013718464,0.05340194],"genre_scores_gemma":[0.88501495,0.00033642107,0.09572206,0.0005478926,0.00013134808,0.003742867,0.0009040707,0.00065979164,0.012940529],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9828158,0.01254529,0.00065039244,0.00088028936,0.0020823407,0.0010259121],"domain_scores_gemma":[0.97106445,0.01840344,0.0013456497,0.004247557,0.0027187408,0.0022202174],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01423607,0.0008753681,0.00061776,0.0023461026,0.0014568848,0.0029563662,0.0017237827,0.0026825569,0.014185109],"category_scores_gemma":[0.030946277,0.00047083138,0.00057732,0.0010469167,0.0016841728,0.0050662123,0.00618683,0.0017552754,0.0038854196],"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":[0.012074039,0.011782523,0.04076467,0.0024619296,0.00019509661,0.0010099384,0.024233166,0.0009469993,0.014900167,0.0062855887,0.010131185,0.8752147],"study_design_scores_gemma":[0.01369164,0.042120624,0.36067066,0.0059111877,0.002464761,0.00818309,0.10822212,0.05090236,0.2010236,0.05174419,0.15347452,0.0015912569],"about_ca_topic_score_codex":0.001006122,"about_ca_topic_score_gemma":0.0016554593,"teacher_disagreement_score":0.01423607,"about_ca_system_score_codex":0.0008452849,"about_ca_system_score_gemma":0.0020427112,"threshold_uncertainty_score":0.075288475},"labels":[],"label_agreement":null},{"id":"W1526601109","doi":"","title":"Oral language evaluation via the computer","year":2007,"lang":"en","type":"article","venue":"E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education","topic":"Speech and dialogue systems","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 the Fraser Valley","funders":"","keywords":"Computer science; Natural language processing; Linguistics; Artificial intelligence","score_opus":0.07106022501286927,"score_gpt":0.31748913834239756,"score_spread":0.2464289133295283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1526601109","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":[0.7558653,0.0010913332,0.050695755,0.00076447934,0.00092680287,0.0028991844,0.005317633,0.0032855822,0.17915386],"genre_scores_gemma":[0.9172496,0.00048855745,0.02403946,0.00029401234,0.0001777263,0.0013089691,0.0022113777,0.00061433984,0.053616118],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99727017,0.001288155,0.00025553882,0.00038077647,0.0006608411,0.00014457993],"domain_scores_gemma":[0.99280965,0.0033794947,0.00016282189,0.0005322188,0.0029060196,0.00020979006],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002551814,0.0007051061,0.0006030104,0.0017576707,0.00062591524,0.0019368154,0.0005489602,0.0008854825,0.05179388],"category_scores_gemma":[0.013311996,0.00021009071,0.0003441735,0.0005189553,0.0005171248,0.001402459,0.0015697522,0.0005553034,0.01079991],"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":[0.006804783,0.0010390981,0.019461462,0.001291888,0.00012045343,0.0014506275,0.008030383,0.0022614796,0.09339861,0.0048218565,0.027776308,0.8335431],"study_design_scores_gemma":[0.0024143052,0.011936818,0.23220842,0.0010814527,0.0009949545,0.010878039,0.030212132,0.08931697,0.28875476,0.013641806,0.31756973,0.0009906626],"about_ca_topic_score_codex":0.002010921,"about_ca_topic_score_gemma":0.0024296492,"teacher_disagreement_score":0.05179388,"about_ca_system_score_codex":0.0005303768,"about_ca_system_score_gemma":0.00087315176,"threshold_uncertainty_score":0.17326778},"labels":[],"label_agreement":null},{"id":"W1528616482","doi":"10.1016/s1363-0814(05)80014-0","title":"Chapter 11 Cybercartography: A multimodal approach","year":2005,"lang":"en","type":"book-chapter","venue":"Modern cartography","topic":"Speech and dialogue systems","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 Sciences and Engineering Research Council of Canada; Carleton University","funders":"","keywords":"Modalities; Modality (human–computer interaction); Stimulus modality; Human–computer interaction; Computer science; Multimodality; Gesture; Haptic technology; USable; Multimodal interaction; Visualization; Natural (archaeology); Artificial intelligence; Multimedia; Sensory system; Cognitive psychology; Psychology","score_opus":0.017051853647053132,"score_gpt":0.20628505313820636,"score_spread":0.18923319949115322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1528616482","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":[0.0024181872,0.034186292,0.04957934,0.0017106559,0.0023950455,0.00006440208,0.000109019675,0.00034621477,0.9091909],"genre_scores_gemma":[0.043270104,0.029431025,0.01567044,0.0007964825,0.0012560956,0.00013649679,0.00026705384,0.00034532897,0.908827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99986804,0.000032893717,0.000006249686,0.000028453622,0.000047357466,0.00001707635],"domain_scores_gemma":[0.99990046,0.00003826886,0.0000046963055,0.000013935411,0.000029489252,0.000013251308],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014992716,0.0010493926,0.00037904762,0.0009953367,0.0012553117,0.0036239177,0.00062608527,0.0013536304,0.041666437],"category_scores_gemma":[0.00040614678,0.00029403507,0.00037263485,0.0011469278,0.0013289992,0.0026557634,0.0012363784,0.0014255247,0.0073086224],"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":[0.000020725609,0.0000655549,0.00011796159,0.0005823774,0.000009845654,0.00021657787,0.0025162438,0.0016177484,0.0027335952,0.5690428,0.137024,0.28605264],"study_design_scores_gemma":[0.0000020166817,0.00001857377,0.00022000837,0.00040754883,0.000008222825,0.00028361686,0.0004532535,0.0007122801,0.0011036204,0.043065954,0.95371413,0.000010819942],"about_ca_topic_score_codex":0.0019890477,"about_ca_topic_score_gemma":0.0036506027,"teacher_disagreement_score":0.041666437,"about_ca_system_score_codex":0.0011229096,"about_ca_system_score_gemma":0.0010432076,"threshold_uncertainty_score":0.13938814},"labels":[],"label_agreement":null},{"id":"W1548457881","doi":"","title":"Communication strategies for a computerized caregiver for individuals with Alzheimerâ€™s disease","year":2012,"lang":"en","type":"article","venue":"North American Chapter of the Association for Computational Linguistics","topic":"Speech and dialogue systems","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; University of Toronto","funders":"","keywords":"Task (project management); Vocabulary; Computer science; Preprocessor; Confusion; Disease; Noise (video); Human–computer interaction; Speech recognition; Cognitive psychology; Artificial intelligence; Natural language processing; Machine learning; Psychology; Medicine; Linguistics","score_opus":0.020782509783251652,"score_gpt":0.26590442363750444,"score_spread":0.24512191385425278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1548457881","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":[0.7176696,0.0016533086,0.22306518,0.008952122,0.00039325698,0.0009139349,0.0006402456,0.0069639026,0.039748505],"genre_scores_gemma":[0.8126693,0.0005618527,0.17144142,0.0008371808,0.0000740673,0.00025885948,0.0004626174,0.00022285842,0.013471848],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995165,0.00028898168,0.00003669245,0.00007756297,0.00004512121,0.000035063975],"domain_scores_gemma":[0.99895835,0.0005282649,0.000097335986,0.00013066374,0.0001980899,0.00008733641],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010962695,0.00087422354,0.00027776312,0.0005016558,0.0012279032,0.0010527711,0.0007139011,0.0008345641,0.008433843],"category_scores_gemma":[0.005153134,0.00020367617,0.0003689011,0.0001846787,0.00044618009,0.0011778438,0.00096841366,0.00045561045,0.0030043856],"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":[0.0006247422,0.00093247753,0.045987893,0.0005418925,0.00005354832,0.0068379804,0.038491514,0.0029647008,0.04191914,0.01024564,0.049048375,0.8023522],"study_design_scores_gemma":[0.0008307477,0.0033798106,0.092969686,0.0016883232,0.0007879833,0.04103044,0.14544542,0.16219136,0.11246584,0.07832266,0.36001378,0.00087393896],"about_ca_topic_score_codex":0.0013620121,"about_ca_topic_score_gemma":0.0027175636,"teacher_disagreement_score":0.008433843,"about_ca_system_score_codex":0.0003463926,"about_ca_system_score_gemma":0.00077406986,"threshold_uncertainty_score":0.028214037},"labels":[],"label_agreement":null},{"id":"W1552035308","doi":"","title":"Familiar talker advantages in formant-based and concatenative synthetic speech","year":2012,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Speech and dialogue systems","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":"University of Calgary","funders":"","keywords":"Formant; Speech recognition; Sentence; Speech synthesis; Stress (linguistics); Computer science; Natural language processing; Linguistics","score_opus":0.010541035580956842,"score_gpt":0.22031586904445616,"score_spread":0.20977483346349932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1552035308","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":[0.82899356,0.0011379125,0.119826816,0.0005274048,0.00023345633,0.00024221413,0.00037742386,0.00081473537,0.047846477],"genre_scores_gemma":[0.9437678,0.0003173291,0.047498036,0.00019645866,0.0001148236,0.00019807315,0.000281219,0.00024181242,0.0073844516],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99845827,0.000735709,0.00015229169,0.00026386217,0.00030707958,0.00008288069],"domain_scores_gemma":[0.99398756,0.0038657896,0.00020891725,0.000937858,0.00067723467,0.00032267597],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030569474,0.00034248375,0.00031679732,0.00043313843,0.00035640463,0.000921219,0.00037056635,0.00049661193,0.010780427],"category_scores_gemma":[0.00885516,0.00023386051,0.0002463653,0.00024555484,0.0005992539,0.0015619106,0.0011633266,0.0004196401,0.0019238639],"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":[0.007188688,0.00086750224,0.019210348,0.0006985629,0.00007685551,0.0013444968,0.0054675043,0.0025012507,0.5475014,0.015637878,0.0013542685,0.39815125],"study_design_scores_gemma":[0.001078722,0.021192424,0.32517976,0.00039968692,0.00063015945,0.026977437,0.0072164093,0.02771699,0.46494684,0.03808358,0.08613289,0.00044513756],"about_ca_topic_score_codex":0.00025930654,"about_ca_topic_score_gemma":0.00070030126,"teacher_disagreement_score":0.010780427,"about_ca_system_score_codex":0.00016318532,"about_ca_system_score_gemma":0.00023279978,"threshold_uncertainty_score":0.03606409},"labels":[],"label_agreement":null},{"id":"W15525221","doi":"10.1586/14737159.4.6.783","title":"Proceedings of the 14th international conference on Intelligent user interfaces","year":2009,"lang":"en","type":"article","venue":"Intelligent User Interfaces","topic":"Speech and dialogue systems","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":"Session (web analytics); Presentation (obstetrics); Computer science; Automatic summarization; Intelligent decision support system; User interface; World Wide Web; Field (mathematics); Multimedia; Artificial intelligence","score_opus":0.0415651315332456,"score_gpt":0.2840659228320183,"score_spread":0.24250079129877272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W15525221","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":[0.032053977,0.08161614,0.57591313,0.015342702,0.0431945,0.0019201973,0.003682818,0.034376603,0.21189994],"genre_scores_gemma":[0.19113256,0.040752344,0.24010304,0.009039711,0.010709952,0.0030707316,0.020179713,0.0037127428,0.48129913],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99759763,0.0008045256,0.00027685708,0.00040692638,0.00067403394,0.00024005499],"domain_scores_gemma":[0.99711955,0.0009883775,0.00006279907,0.0004249925,0.0011165934,0.0002877484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00359826,0.0025422378,0.0019213641,0.0011858682,0.0008754151,0.0057109683,0.0025662612,0.0035820976,0.09389968],"category_scores_gemma":[0.0066223405,0.0005252961,0.0010745499,0.0007856031,0.0010814257,0.004713282,0.0025696943,0.0028337366,0.04995736],"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":[0.0008201198,0.0003649123,0.0015589403,0.0005706082,0.00018351112,0.0005258562,0.0004748993,0.0007921865,0.0072374735,0.0049291174,0.4716487,0.51089376],"study_design_scores_gemma":[0.00011902967,0.00033203495,0.002996205,0.00053606636,0.00019778687,0.0008815045,0.00057905965,0.023149008,0.0041496498,0.008241277,0.9587299,0.00008840676],"about_ca_topic_score_codex":0.0028149516,"about_ca_topic_score_gemma":0.0019305906,"teacher_disagreement_score":0.09389968,"about_ca_system_score_codex":0.0007160481,"about_ca_system_score_gemma":0.00084020937,"threshold_uncertainty_score":0.31412572},"labels":[],"label_agreement":null},{"id":"W1558656462","doi":"10.1023/a:1005237527730","title":"The Place of Dialogue Theory in Logic, Computer Science and Communication Studies","year":2000,"lang":"en","type":"article","venue":"Synthese","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":73,"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 Winnipeg","funders":"","keywords":"Argumentation theory; Philosophy of language; Epistemology; Philosophy of science; Metaphysics; Focus (optics); Field (mathematics); Relation (database); Subject (documents); Sociology; Computer science; Philosophy; Mathematics","score_opus":0.02248677623808385,"score_gpt":0.2700755916718609,"score_spread":0.24758881543377706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1558656462","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":[0.023387272,0.1965387,0.25991943,0.15139283,0.007026249,0.000083876985,0.00020707314,0.00034711513,0.36109746],"genre_scores_gemma":[0.8904984,0.026294997,0.054234587,0.00787822,0.006083086,0.00028846558,0.000089154,0.00034289603,0.014290142],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9889664,0.009180613,0.00024981634,0.0005381444,0.0007435817,0.00032144395],"domain_scores_gemma":[0.9648931,0.031211859,0.0006957363,0.001628552,0.0009175731,0.0006531732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01494392,0.00087820436,0.0017281603,0.0050107976,0.0046777977,0.014543695,0.0020968565,0.005600715,0.0068918862],"category_scores_gemma":[0.02043241,0.0007772245,0.000736537,0.0045480262,0.06034855,0.026724745,0.0045441766,0.008958472,0.00087698264],"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":[0.000012111024,0.000006019127,0.00003835527,0.00006138865,0.0000035318712,0.000012910217,0.0018498007,0.00013232285,0.00003663234,0.99430627,0.0006192952,0.0029213622],"study_design_scores_gemma":[0.000014870675,0.00001228508,0.00006341805,0.0000922217,0.000004575729,0.000029563238,0.0009793958,0.00048909214,0.000075390926,0.97873735,0.019492839,0.000009023151],"about_ca_topic_score_codex":0.0031669918,"about_ca_topic_score_gemma":0.0023948892,"teacher_disagreement_score":0.01494392,"about_ca_system_score_codex":0.006079533,"about_ca_system_score_gemma":0.0044271466,"threshold_uncertainty_score":0.079031885},"labels":[],"label_agreement":null},{"id":"W156197033","doi":"10.1007/978-0-387-68439-0_2","title":"User Interface Design for Natural Language Systems: From Research to Reality","year":2007,"lang":"en","type":"book-chapter","venue":"Signals and communication technology","topic":"Speech and dialogue systems","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":"Tellabs (Canada)","funders":"","keywords":"Natural language user interface; Computer science; Natural (archaeology); Natural language; Interface (matter); Human–computer interaction; User interface; Natural language understanding; Center (category theory); Artificial intelligence; Programming language; History","score_opus":0.12163222967763371,"score_gpt":0.378101684247503,"score_spread":0.2564694545698693,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W156197033","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006976888,0.066645734,0.8960263,0.0027595733,0.0005133792,0.00012540769,0.00013063662,0.0027582773,0.0240639],"genre_scores_gemma":[0.12712038,0.04141885,0.78943366,0.0014971667,0.0006646302,0.00046768505,0.0006026848,0.0013444856,0.037450407],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9969457,0.0013410795,0.000223747,0.00041893852,0.000953235,0.00011724057],"domain_scores_gemma":[0.99634546,0.0025672128,0.00008277688,0.00030540457,0.0005896379,0.000109599234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003934329,0.0011200033,0.0012104304,0.0008682614,0.0004803627,0.0056490796,0.0029029069,0.002424574,0.007317252],"category_scores_gemma":[0.009125681,0.0008087406,0.0006889406,0.00096405833,0.002645856,0.006337921,0.0014648569,0.0023316925,0.0022785335],"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":[0.0001241993,0.000116946816,0.00052330265,0.002858261,0.00007337947,0.00014693114,0.0039326455,0.004096045,0.016001211,0.18049368,0.036847174,0.7547862],"study_design_scores_gemma":[0.000104482635,0.00055006944,0.0013650679,0.0027157587,0.00013101396,0.002046019,0.0020819537,0.0695952,0.02156001,0.30797943,0.5916769,0.00019406849],"about_ca_topic_score_codex":0.0011123425,"about_ca_topic_score_gemma":0.0008430439,"teacher_disagreement_score":0.007317252,"about_ca_system_score_codex":0.0008538333,"about_ca_system_score_gemma":0.0010422118,"threshold_uncertainty_score":0.024478614},"labels":[],"label_agreement":null},{"id":"W1575122976","doi":"10.1007/978-3-540-74628-7_4","title":"Recent Advances in Spoken Language Understanding","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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","funders":"","keywords":"Computer science; Spoken language; Parsing; Presentation (obstetrics); Natural language processing; Interpretation (philosophy); Rule-based machine translation; Artificial intelligence; Linguistics; Programming language","score_opus":0.038917850272569415,"score_gpt":0.28210917439765437,"score_spread":0.24319132412508496,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1575122976","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":[0.008679454,0.5331864,0.3343961,0.01308936,0.0031273402,0.00012754127,0.00087283825,0.0039623757,0.102558576],"genre_scores_gemma":[0.13218859,0.45404282,0.27909845,0.0046709543,0.009130645,0.00032488932,0.004185032,0.0018012769,0.11455737],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9988716,0.00025605052,0.00012352002,0.00025343985,0.00043699556,0.000058327194],"domain_scores_gemma":[0.99162185,0.0065315375,0.0001705366,0.00049218,0.001080235,0.000103637205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021110063,0.00068293366,0.0012542605,0.0018089742,0.00046199036,0.0037376652,0.0016325396,0.0015212297,0.022833075],"category_scores_gemma":[0.008093868,0.00048299268,0.00056402007,0.0025716876,0.0015608573,0.007435052,0.001824191,0.001835507,0.006920443],"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":[0.000045879788,0.00003662516,0.00017280935,0.0015577832,0.000024196786,0.000042774045,0.0004780727,0.00090577494,0.002907333,0.026793592,0.013842671,0.95319253],"study_design_scores_gemma":[0.00003299531,0.00014800171,0.0012223832,0.0011414943,0.00015687039,0.00074092095,0.0010436954,0.020678293,0.012021822,0.12677523,0.83595234,0.000085954525],"about_ca_topic_score_codex":0.0017173364,"about_ca_topic_score_gemma":0.0017102374,"teacher_disagreement_score":0.022833075,"about_ca_system_score_codex":0.000792139,"about_ca_system_score_gemma":0.0016690119,"threshold_uncertainty_score":0.07638425},"labels":[],"label_agreement":null},{"id":"W1582403093","doi":"10.1007/978-3-642-13059-5_37","title":"A Model for Reasoning about Interaction with Users in Dynamic, Time Critical Environments for the Application of Hospital Decision Making","year":2010,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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; Ask price; Human–computer interaction; Operations research","score_opus":0.01016602136726443,"score_gpt":0.2696577078625749,"score_spread":0.2594916864953105,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1582403093","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":[0.005746611,0.00024381485,0.98596025,0.0010218724,0.000069444824,0.00019700715,0.00069448166,0.0009367451,0.0051296316],"genre_scores_gemma":[0.2239809,0.00053875,0.76576394,0.0005174965,0.000119406664,0.0009070877,0.002073068,0.00019828146,0.0059009846],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9977418,0.00083886646,0.00028679366,0.0003984395,0.00049519486,0.00023901935],"domain_scores_gemma":[0.99616915,0.0028323787,0.00021576285,0.00028645826,0.00029111587,0.0002051736],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002726691,0.0014930875,0.0014171468,0.0014023561,0.0020766754,0.00580911,0.0046874788,0.0045918473,0.009835947],"category_scores_gemma":[0.0084826285,0.0011981371,0.0031552298,0.0017389023,0.0022699363,0.00696877,0.0029244926,0.0037374455,0.0016304308],"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":[0.00028268987,0.00029134372,0.0016388781,0.00047021345,0.00020292397,0.0015075865,0.0022100466,0.26439667,0.0023133673,0.67993265,0.007946393,0.03880721],"study_design_scores_gemma":[0.00009311209,0.000046482466,0.00019856848,0.000073919924,0.00010526248,0.00020878795,0.00028577368,0.7076034,0.000791714,0.2806887,0.009857062,0.00004723563],"about_ca_topic_score_codex":0.020143837,"about_ca_topic_score_gemma":0.018233793,"teacher_disagreement_score":0.020143837,"about_ca_system_score_codex":0.0024551724,"about_ca_system_score_gemma":0.002767268,"threshold_uncertainty_score":0.04005319},"labels":[],"label_agreement":null},{"id":"W1605901150","doi":"10.21437/interspeech.2010-486","title":"The impact of ASR on abstractive vs. extractive meeting summaries","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Computer science; Task (project management); Natural language processing; Contrast (vision); Information retrieval; Artificial intelligence; Engineering","score_opus":0.011113332749807378,"score_gpt":0.2772152754820833,"score_spread":0.26610194273227594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1605901150","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":[0.8813521,0.008855579,0.072620414,0.0012726125,0.0009840095,0.0011047338,0.0024318714,0.0139236525,0.017455067],"genre_scores_gemma":[0.9128855,0.0023605404,0.069828354,0.00044873962,0.00074199884,0.0004832494,0.004453743,0.0021385765,0.006659343],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.97231007,0.017523406,0.003086194,0.0024769383,0.0040194322,0.00058391085],"domain_scores_gemma":[0.79606074,0.1744033,0.007822657,0.00758599,0.012469055,0.0016582066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016453106,0.0018958452,0.0015240236,0.0019007906,0.0008738501,0.004098341,0.0010484403,0.0014586938,0.0055231457],"category_scores_gemma":[0.11163882,0.0004481844,0.0008718947,0.0014367206,0.00085472304,0.0047655622,0.0017253312,0.0016043382,0.0030293309],"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":[0.023096869,0.0011736469,0.009203713,0.0045907847,0.0008565589,0.00067541393,0.0021970472,0.00980664,0.27507576,0.0011390905,0.0076565123,0.6645281],"study_design_scores_gemma":[0.0032967022,0.049183816,0.15698552,0.00091197033,0.005326444,0.005831786,0.0065229274,0.16514143,0.5546015,0.005393302,0.045524534,0.0012800746],"about_ca_topic_score_codex":0.0013730053,"about_ca_topic_score_gemma":0.0016529693,"teacher_disagreement_score":0.016453106,"about_ca_system_score_codex":0.000656712,"about_ca_system_score_gemma":0.0005165657,"threshold_uncertainty_score":0.087013364},"labels":[],"label_agreement":null},{"id":"W1628510926","doi":"","title":"Making distinctiveness models of memory distinct","year":2007,"lang":"en","type":"book-chapter","venue":"Psychology Press eBooks","topic":"Speech and dialogue systems","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":"Memorial University of Newfoundland","funders":"","keywords":"Optimal distinctiveness theory; Psychology; Computer science; Social psychology","score_opus":0.1784786577201935,"score_gpt":0.3494409594522464,"score_spread":0.1709623017320529,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1628510926","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2519641,0.0026076313,0.60905576,0.009710236,0.00043799906,0.00004349276,0.00033138436,0.0007055732,0.12514383],"genre_scores_gemma":[0.95746505,0.00048039714,0.033370696,0.0005156407,0.00023479275,0.000041151783,0.00016228665,0.00012268887,0.007607333],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99943095,0.00016620453,0.00003196305,0.00016463375,0.000119041964,0.00008724451],"domain_scores_gemma":[0.99686795,0.0015592192,0.00019191905,0.0009543777,0.00024785372,0.0001786412],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001347305,0.00044156177,0.0006310353,0.00093527435,0.000746751,0.0037909842,0.0018975376,0.0015588239,0.0063795126],"category_scores_gemma":[0.0056886035,0.00054481503,0.0009126799,0.00077892357,0.004704785,0.016608551,0.0018944977,0.003026121,0.00077267626],"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":[0.000054126824,0.000013143064,0.00039038048,0.00002287786,0.000016436179,0.000022248545,0.00038337035,0.0010412687,0.00076340453,0.9785619,0.00076299184,0.017967751],"study_design_scores_gemma":[0.000006199817,0.000005995388,0.00019248313,0.0000035457736,0.0000063572547,0.000017434893,0.00005014518,0.0026555667,0.00021606093,0.99623626,0.00060612,0.0000038167746],"about_ca_topic_score_codex":0.0007537898,"about_ca_topic_score_gemma":0.000600756,"teacher_disagreement_score":0.0063795126,"about_ca_system_score_codex":0.0009524,"about_ca_system_score_gemma":0.00054898945,"threshold_uncertainty_score":0.021341622},"labels":[],"label_agreement":null},{"id":"W164079528","doi":"10.21437/interspeech.2004-686","title":"Robust speech recognition in client-server scenarios","year":2004,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Computer science; Server; Robustness (evolution); Normalization (sociology); Android (operating system); Computation; Distributed computing; Dialog box; Mobile telephony; Mobile device; Mobile computing; Computer network; Human–computer interaction; Mobile radio; World Wide Web; Operating system","score_opus":0.04598870219501271,"score_gpt":0.2310925917731025,"score_spread":0.18510388957808982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W164079528","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1280283,0.00072143856,0.84683526,0.00067456014,0.000113492424,0.00023231126,0.00012712865,0.010578466,0.012689106],"genre_scores_gemma":[0.78508127,0.0003933187,0.19733015,0.00026056683,0.00014210194,0.00016636406,0.00040138824,0.0005380889,0.015686851],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9966378,0.0011299175,0.00019816197,0.0005720799,0.0011653947,0.00029665194],"domain_scores_gemma":[0.99553156,0.0021628656,0.00022228491,0.00081697037,0.0011140388,0.00015227859],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023105259,0.0008859843,0.0014656661,0.0005950814,0.0007264744,0.0020318544,0.0019916212,0.0023213075,0.006326619],"category_scores_gemma":[0.0070882686,0.0005940373,0.00040760497,0.00085016177,0.0008283838,0.0034169317,0.0013310525,0.0012215764,0.008992769],"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":[0.0026996285,0.00080121454,0.003153872,0.00046315006,0.0001903928,0.002463362,0.0009148922,0.28710943,0.19409662,0.03185943,0.012821487,0.46342653],"study_design_scores_gemma":[0.000063568375,0.00022729543,0.00091830094,0.000019303368,0.000039754585,0.00086457137,0.00024860576,0.87952805,0.10071528,0.009267725,0.00804729,0.0000602862],"about_ca_topic_score_codex":0.0025971185,"about_ca_topic_score_gemma":0.002648414,"teacher_disagreement_score":0.006326619,"about_ca_system_score_codex":0.00075697224,"about_ca_system_score_gemma":0.00068248954,"threshold_uncertainty_score":0.021164656},"labels":[],"label_agreement":null},{"id":"W1707418623","doi":"10.1007/978-3-540-73283-9_39","title":"Multimodal Technology for Municipal Inspections: An Evaluation Framework","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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; National Research Council Canada","funders":"","keywords":"Computer science; Usability; TRIPS architecture; Field (mathematics); Context (archaeology); Mobile interaction; Work (physics); Focus (optics); Mobile technology; Human–computer interaction; Contextual design; Mobile device; Systems engineering; Software engineering; World Wide Web; Artificial intelligence; Engineering","score_opus":0.04761346256582205,"score_gpt":0.32762723648550207,"score_spread":0.28001377391968,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1707418623","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":[0.5689059,0.0031829015,0.33516002,0.0012116389,0.00011136935,0.006918821,0.0033103288,0.0010075829,0.08019152],"genre_scores_gemma":[0.89462566,0.0005951758,0.09713221,0.000092738446,0.000029472034,0.0030937812,0.0011040494,0.0000714513,0.003255401],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9792324,0.0142692765,0.00074469525,0.0007095659,0.0043033594,0.00074072805],"domain_scores_gemma":[0.98215574,0.01131324,0.0012288815,0.0006504855,0.0042537376,0.0003979737],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.022769572,0.0012930853,0.00074393256,0.004197125,0.0011296258,0.0038925866,0.0014843364,0.0017527989,0.0052339733],"category_scores_gemma":[0.028850554,0.00033086736,0.0010564729,0.0027561542,0.0012814641,0.0031822296,0.0026258044,0.0007881769,0.0005928879],"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":[0.0077905795,0.0044048727,0.08154238,0.003320913,0.0010585213,0.00034642874,0.0050816243,0.080319285,0.028602708,0.081895806,0.0100150425,0.69562185],"study_design_scores_gemma":[0.0010107796,0.017030882,0.17177103,0.0018665339,0.0025310358,0.0006256663,0.014311834,0.6512745,0.057469543,0.04710785,0.03449098,0.0005092295],"about_ca_topic_score_codex":0.0071770996,"about_ca_topic_score_gemma":0.010476735,"teacher_disagreement_score":0.022769572,"about_ca_system_score_codex":0.0041212197,"about_ca_system_score_gemma":0.002440316,"threshold_uncertainty_score":0.12041843},"labels":[],"label_agreement":null},{"id":"W1711540781","doi":"10.1558/cj.v30i0.187-202","title":"Clicking for Help","year":2013,"lang":"en","type":"article","venue":"CALICO Journal","topic":"Speech and dialogue systems","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":"Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"German; TUTOR; Computer science; Context (archaeology); World Wide Web; Natural language processing; Multimedia; Linguistics; Programming language","score_opus":0.02102116292661978,"score_gpt":0.24509984513110145,"score_spread":0.22407868220448166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1711540781","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":[0.98316956,0.00045902017,0.0022768246,0.00015926744,0.000028462176,0.00006957421,0.0010565093,0.00044648407,0.012334318],"genre_scores_gemma":[0.9881017,0.00028109227,0.0019084811,0.00013125093,0.00003752399,0.000050774757,0.00088010175,0.000055233184,0.008553692],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99846846,0.00046173943,0.00013815994,0.0003079264,0.0004801477,0.00014344798],"domain_scores_gemma":[0.9877293,0.008019815,0.0016888137,0.0008997575,0.000951192,0.00071116496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081106793,0.00031288507,0.00031897606,0.0012421629,0.00036455668,0.00094063504,0.0004116238,0.00072526553,0.0125925],"category_scores_gemma":[0.013660266,0.0001477973,0.00018097616,0.00055552786,0.0002654691,0.0011568735,0.00071711413,0.00031420932,0.0034882328],"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":[0.0010922415,0.0013773493,0.62683564,0.0006571442,0.00014977135,0.0030130288,0.016353438,0.0005030114,0.02966009,0.0017153899,0.008273515,0.31036946],"study_design_scores_gemma":[0.000055853965,0.0011793489,0.90429574,0.00019455966,0.00014277018,0.0061856527,0.0074421978,0.0026813997,0.011628933,0.0012213219,0.06486993,0.000102380436],"about_ca_topic_score_codex":0.0010317385,"about_ca_topic_score_gemma":0.002103336,"teacher_disagreement_score":0.0125925,"about_ca_system_score_codex":0.0001789906,"about_ca_system_score_gemma":0.00025129842,"threshold_uncertainty_score":0.04212612},"labels":[],"label_agreement":null},{"id":"W1714170610","doi":"","title":"Grammaticality Judgement in a Word Completion Task","year":2010,"lang":"en","type":"article","venue":"North American Chapter of the Association for Computational Linguistics","topic":"Speech and dialogue systems","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":"Holland Bloorview Kids Rehabilitation Hospital","funders":"","keywords":"Computer science; Grammaticality; Natural language processing; Syntax; Word (group theory); Judgement; Task (project management); Artificial intelligence; Usability; Grammar; Linguistics; Human–computer interaction","score_opus":0.01283611387327251,"score_gpt":0.25089103499739424,"score_spread":0.23805492112412172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1714170610","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":[0.9473209,0.00025207302,0.03981339,0.00017414858,0.00011883253,0.0005500945,0.000222705,0.00065532036,0.010892656],"genre_scores_gemma":[0.9675627,0.00010810917,0.02829005,0.00026719563,0.000063355605,0.0003266263,0.0005551292,0.00034629594,0.0024806063],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9870432,0.00681073,0.0007986624,0.0022444385,0.0026495843,0.00045331876],"domain_scores_gemma":[0.85949045,0.11383482,0.007182461,0.0060888953,0.011709256,0.0016940515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01274541,0.0011053944,0.0008467242,0.0012599828,0.00081147766,0.002587668,0.0011697776,0.0018456453,0.0055257343],"category_scores_gemma":[0.15784132,0.00043124534,0.0005144214,0.00066065113,0.0013945252,0.0042836866,0.0018474488,0.0012265986,0.0017828362],"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":[0.005830944,0.0014676483,0.05185877,0.0026659854,0.00027190623,0.0013999665,0.086042464,0.0071014003,0.5108795,0.004433314,0.0073902407,0.32065785],"study_design_scores_gemma":[0.0013700888,0.017049443,0.5220127,0.0011230952,0.000618014,0.0060102,0.03473538,0.121696554,0.20546694,0.039016508,0.049063433,0.001837601],"about_ca_topic_score_codex":0.0017831936,"about_ca_topic_score_gemma":0.0012783641,"teacher_disagreement_score":0.01274541,"about_ca_system_score_codex":0.0005970861,"about_ca_system_score_gemma":0.0006667801,"threshold_uncertainty_score":0.067404985},"labels":[],"label_agreement":null},{"id":"W1724237506","doi":"","title":"An Architecture for Multimodal Semantic Fusion","year":2009,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Speech and dialogue systems","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 TÉLUQ","funders":"","keywords":"Computer science; Architecture; Natural language processing; Artificial intelligence; History","score_opus":0.012829334931130896,"score_gpt":0.23965791830203187,"score_spread":0.22682858337090098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1724237506","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":[0.0062127053,0.000292003,0.9807797,0.00027078204,0.00008205683,0.00008030205,0.000209793,0.006878914,0.005193737],"genre_scores_gemma":[0.2721651,0.00077812857,0.70840776,0.00036755943,0.000107254826,0.00026993448,0.0014674258,0.0007326997,0.01570407],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936754,0.00011968198,0.000064375636,0.00018777171,0.0001811005,0.00007955996],"domain_scores_gemma":[0.9995455,0.0000987774,0.00001990283,0.00013584846,0.00016079015,0.000039140705],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015527968,0.0007431655,0.0008791961,0.0010301356,0.00092814513,0.002659072,0.0014829879,0.0014499527,0.009958363],"category_scores_gemma":[0.0018674281,0.0005890715,0.0011286314,0.001263386,0.0010328513,0.004140204,0.0038123217,0.0014504285,0.0038824934],"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":[0.0007600708,0.0001934586,0.00097223034,0.00048956485,0.0002074564,0.00050070905,0.0017683717,0.031386532,0.06279496,0.23271663,0.02130756,0.6469025],"study_design_scores_gemma":[0.00005250763,0.00019311403,0.000678891,0.00017069564,0.00031343932,0.00043815383,0.0004806803,0.5251435,0.07303611,0.29906097,0.10034206,0.00008982778],"about_ca_topic_score_codex":0.0035208862,"about_ca_topic_score_gemma":0.004514644,"teacher_disagreement_score":0.009958363,"about_ca_system_score_codex":0.00087414443,"about_ca_system_score_gemma":0.0009990875,"threshold_uncertainty_score":0.03331405},"labels":[],"label_agreement":null},{"id":"W174748860","doi":"","title":"Foundations of Similarity and Utility.","year":2007,"lang":"en","type":"article","venue":"The Florida AI Research Society","topic":"Speech and dialogue systems","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 Calgary","funders":"","keywords":"Similarity (geometry); Computer science; Foundation (evidence); Artificial intelligence; Expected utility hypothesis; Theoretical computer science; Machine learning; Mathematical economics; Mathematics","score_opus":0.09947049290987932,"score_gpt":0.40029675623724326,"score_spread":0.30082626332736395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W174748860","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0125916675,0.0061423797,0.87175,0.007501245,0.00042580877,0.00014277722,0.00034403484,0.00015231696,0.10094975],"genre_scores_gemma":[0.7817322,0.005415122,0.19227403,0.0020125539,0.0014056162,0.00049035397,0.0005621379,0.00016192567,0.015946181],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9915547,0.0036876397,0.00065132463,0.0013641464,0.0023076276,0.00043459717],"domain_scores_gemma":[0.9878512,0.0076311775,0.0009821402,0.0016666378,0.0014510233,0.0004178596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0074635637,0.00076556724,0.001177592,0.0032606854,0.0025628582,0.0061914846,0.001975038,0.0030906776,0.009338295],"category_scores_gemma":[0.023240356,0.0005758233,0.0016955134,0.0031599486,0.0125319855,0.013589799,0.004847399,0.0035576173,0.0016865733],"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":[0.0000042805673,0.00000497642,0.00007778086,0.000026572628,0.000007672427,0.000021117447,0.00007237849,0.0004730061,0.000037471695,0.99484295,0.00034946203,0.0040823794],"study_design_scores_gemma":[0.0000035472995,0.000007902224,0.00006604763,0.000021016403,0.000004177732,0.000059072063,0.000037762013,0.0024286353,0.000058986272,0.99281913,0.004488115,0.0000055628684],"about_ca_topic_score_codex":0.002070352,"about_ca_topic_score_gemma":0.001076833,"teacher_disagreement_score":0.009338295,"about_ca_system_score_codex":0.0033186057,"about_ca_system_score_gemma":0.0016418769,"threshold_uncertainty_score":0.039471567},"labels":[],"label_agreement":null},{"id":"W177862879","doi":"","title":"A Framework for Soliciting Clarification from Users During Plan Recognition","year":2004,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; University of Waterloo","funders":"","keywords":"Variety (cybernetics); Ambiguity; Computer science; Plan (archaeology); Debugging; Set (abstract data type); Advice (programming); Order (exchange); Simplicity; Human–computer interaction; Artificial intelligence; Epistemology; Business","score_opus":0.054670027494342396,"score_gpt":0.264112500711524,"score_spread":0.20944247321718157,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W177862879","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009969887,0.00009989479,0.9935137,0.00045958222,0.000043063978,0.0003009358,0.00006372047,0.0025319715,0.0019901372],"genre_scores_gemma":[0.041024044,0.000099125544,0.9541953,0.00021337895,0.00007195434,0.0004889236,0.00021247452,0.00038014978,0.003314494],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9829937,0.008654312,0.0013786616,0.0036519454,0.002374538,0.0009467399],"domain_scores_gemma":[0.9742063,0.013540226,0.0021358957,0.0055590705,0.0030930548,0.0014654883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020164784,0.00289277,0.001458761,0.003533651,0.0033920088,0.008547591,0.006718304,0.0061698514,0.015942777],"category_scores_gemma":[0.03378133,0.0027083766,0.0028369036,0.0013668928,0.008692434,0.01132077,0.006386883,0.0055381972,0.006900599],"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":[0.0007565374,0.00039267796,0.0014404282,0.0010103865,0.000119114404,0.000862931,0.016774403,0.026974492,0.02866596,0.58464205,0.013509269,0.3248517],"study_design_scores_gemma":[0.0003211077,0.0005401254,0.0009144054,0.00071150146,0.00016122074,0.0014941542,0.0031971035,0.4042457,0.027862223,0.3712186,0.18877968,0.0005541806],"about_ca_topic_score_codex":0.006416993,"about_ca_topic_score_gemma":0.006882252,"teacher_disagreement_score":0.020164784,"about_ca_system_score_codex":0.0025733146,"about_ca_system_score_gemma":0.0041426816,"threshold_uncertainty_score":0.10664284},"labels":[],"label_agreement":null},{"id":"W1779384219","doi":"","title":"Fusion multimodale pour les systemes d'interaction","year":2013,"lang":"fr","type":"dissertation","venue":"","topic":"Speech and dialogue systems","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":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Gesture; Human–computer interaction; Human–machine system; Domain (mathematical analysis); Multimodal interaction; Interactive systems engineering; Context (archaeology); Artificial intelligence; User experience design; User interface design","score_opus":0.03632047762483868,"score_gpt":0.2806426220975819,"score_spread":0.24432214447274322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1779384219","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.004095649,0.011406363,0.9609337,0.002879576,0.0010846853,0.00034230482,0.00035063992,0.0026914102,0.016215686],"genre_scores_gemma":[0.14800355,0.021021951,0.76895237,0.0028905948,0.0036408498,0.002946158,0.00184938,0.0015087134,0.049186468],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9809153,0.008091115,0.00084954745,0.0027028678,0.0068237022,0.0006175057],"domain_scores_gemma":[0.9937304,0.003784777,0.00029451537,0.000772093,0.0012032189,0.00021504465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009966011,0.0043868828,0.0033603017,0.0025013755,0.002460012,0.013945576,0.0028996016,0.0073623713,0.014964774],"category_scores_gemma":[0.015871527,0.001425655,0.003668068,0.0024938046,0.0060539343,0.009760602,0.0033101093,0.014465992,0.0059533515],"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":[0.0007499282,0.00022572311,0.00067563634,0.0014059732,0.00030250018,0.0015420213,0.002935665,0.025030043,0.014775337,0.5910457,0.023728454,0.33758304],"study_design_scores_gemma":[0.00048987486,0.0004475876,0.0024437304,0.0010772978,0.00019157404,0.0025508988,0.0011345753,0.25722358,0.027034156,0.18152109,0.5255238,0.000361787],"about_ca_topic_score_codex":0.013053745,"about_ca_topic_score_gemma":0.004369699,"teacher_disagreement_score":0.014964774,"about_ca_system_score_codex":0.004832069,"about_ca_system_score_gemma":0.0024667413,"threshold_uncertainty_score":0.052705944},"labels":[],"label_agreement":null},{"id":"W1860567634","doi":"","title":"Interpretation and Transformation for Abstracting Conversations","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of British Columbia","funders":"","keywords":"Computer science; Conversation; Interpretation (philosophy); Focus (optics); Transformation (genetics); Face (sociological concept); Ontology; Natural language processing; Semantic interpretation; Artificial intelligence; Linguistics; Programming language","score_opus":0.010586245387709506,"score_gpt":0.2474523457169039,"score_spread":0.2368661003291944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1860567634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001656403,0.00018966517,0.9925476,0.00025498663,0.00007406451,0.0001120588,0.00029855059,0.0027706611,0.0020960614],"genre_scores_gemma":[0.06669107,0.00032828937,0.9260367,0.00018135375,0.0001687832,0.0003264522,0.001993155,0.0010994067,0.0031747832],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.993455,0.0028906413,0.0007563235,0.0016138925,0.0010050326,0.0002792091],"domain_scores_gemma":[0.99549603,0.0019211884,0.00044441302,0.0011924467,0.00074853614,0.00019737359],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040220674,0.0019859693,0.00108847,0.003486864,0.0018369271,0.00499502,0.0020163946,0.0019447457,0.008421642],"category_scores_gemma":[0.01246821,0.000929365,0.0028797213,0.0019698322,0.0027211264,0.0064031566,0.005345261,0.0032344686,0.004677352],"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":[0.00035905244,0.00013900966,0.0019693552,0.0013583711,0.00019049973,0.0009953326,0.011495892,0.019564789,0.024009414,0.36686364,0.019147439,0.55390716],"study_design_scores_gemma":[0.000049778868,0.00008497002,0.0013016678,0.00030899077,0.00019666064,0.00085028925,0.002981483,0.21662313,0.02734732,0.5981629,0.15193342,0.00015939024],"about_ca_topic_score_codex":0.0036574285,"about_ca_topic_score_gemma":0.003327116,"teacher_disagreement_score":0.008421642,"about_ca_system_score_codex":0.0016191717,"about_ca_system_score_gemma":0.0022327472,"threshold_uncertainty_score":0.028173149},"labels":[],"label_agreement":null},{"id":"W18692563","doi":"10.1007/0-306-47318-6_4","title":"A Generic Fuzzy Logic Based Handoff Algorithm","year":2001,"lang":"en","type":"book-chapter","venue":"","topic":"Speech and dialogue systems","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":"Nortel (Canada)","funders":"","keywords":"Fuzzy logic; Handover; Computer science; Algorithm; Class (philosophy); SIGNAL (programming language); Artificial intelligence; Computer network","score_opus":0.03323591019814615,"score_gpt":0.22444698045452674,"score_spread":0.1912110702563806,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W18692563","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":[0.0036152054,0.00011189812,0.9925811,0.00004711237,0.0000621226,0.000055934415,0.000033366727,0.0005786171,0.0029145489],"genre_scores_gemma":[0.11844913,0.00020685833,0.87045664,0.00012510712,0.00006290132,0.00011491286,0.00019217597,0.000082106344,0.010310153],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99972755,0.000027849437,0.000017407881,0.000087554494,0.00009781308,0.000041846084],"domain_scores_gemma":[0.9998678,0.0000332917,0.00000771898,0.000025795016,0.000054211254,0.000011134724],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045817596,0.00046483008,0.0008036462,0.00055691926,0.00063151546,0.00085265643,0.0017021333,0.0011749957,0.0065943464],"category_scores_gemma":[0.0007409084,0.00021217144,0.0005261537,0.00061470066,0.00032650362,0.0009848896,0.0008810821,0.0007844245,0.0017814857],"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":[0.00017955934,0.00010485996,0.00031074553,0.00008602674,0.000035793088,0.000071029586,0.00006581736,0.092363894,0.015549047,0.027242893,0.004168856,0.85982144],"study_design_scores_gemma":[0.00004741395,0.00008230572,0.00028404777,0.000019262177,0.000035399455,0.00018594142,0.00002741658,0.97031116,0.0071187094,0.015583859,0.0062851575,0.000019225949],"about_ca_topic_score_codex":0.0023080069,"about_ca_topic_score_gemma":0.002313062,"teacher_disagreement_score":0.0065943464,"about_ca_system_score_codex":0.00051352143,"about_ca_system_score_gemma":0.0008935993,"threshold_uncertainty_score":0.022060335},"labels":[],"label_agreement":null},{"id":"W1881348152","doi":"10.3968/j.css.1923669720141001.4257","title":"Local Coherence in Stream-of-consciousness Discourse: A Centering Approach","year":2014,"lang":"en","type":"article","venue":"Canadian social science","topic":"Speech and dialogue systems","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":"Cohesion (chemistry); Consciousness; Salience (neuroscience); Premise; Coherence (philosophical gambling strategy); Cognition; Linguistics; Psychology; Computer science; Cognitive psychology; Social psychology; Mathematics; Philosophy; Statistics","score_opus":0.013106104842657408,"score_gpt":0.2423232660691469,"score_spread":0.2292171612264895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1881348152","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":[0.5163032,0.0005852682,0.4594476,0.00037182402,0.000047313297,0.00080280716,0.0005687624,0.0009803314,0.020892924],"genre_scores_gemma":[0.926869,0.0000829217,0.07173544,0.000028949627,0.000024175406,0.00031071677,0.0002937812,0.00007094252,0.0005841018],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9939302,0.0023299826,0.0007095163,0.0010735309,0.0015924401,0.00036431034],"domain_scores_gemma":[0.97847056,0.010957131,0.0031956495,0.001985975,0.00441356,0.0009771206],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0066351513,0.00078999926,0.00081336853,0.00799635,0.0017370303,0.003543007,0.00083943433,0.0008974385,0.002313697],"category_scores_gemma":[0.02708845,0.00035760214,0.00076355133,0.0041424553,0.0029600482,0.005660582,0.0045373333,0.0008226834,0.0003226665],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0027571805,0.0005402794,0.1271064,0.0014956959,0.000537859,0.00068353716,0.04518758,0.021324826,0.062361926,0.13368124,0.0025567762,0.6017667],"study_design_scores_gemma":[0.00025762772,0.004108631,0.28754818,0.0006685912,0.0009593069,0.0009933462,0.040036816,0.3224416,0.07006485,0.25116414,0.021171024,0.0005858208],"about_ca_topic_score_codex":0.0034481941,"about_ca_topic_score_gemma":0.0025878095,"teacher_disagreement_score":0.00799635,"about_ca_system_score_codex":0.0020081678,"about_ca_system_score_gemma":0.0013256,"threshold_uncertainty_score":0.035090387},"labels":[],"label_agreement":null},{"id":"W1885693054","doi":"10.1002/j.1545-7249.2008.tb00138.x","title":"Air Traffic Communication in a Second Language: Implications of Cognitive Factors for Training and Assessment","year":2008,"lang":"en","type":"article","venue":"TESOL Quarterly","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":32,"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","funders":"","keywords":"Workload; Fluency; Language proficiency; Air traffic control; Mandarin Chinese; Task (project management); Psychology; Cognition; Speech production; Computer science; Speech recognition; Linguistics; Mathematics education; Engineering","score_opus":0.04289095487607282,"score_gpt":0.30683955760549614,"score_spread":0.26394860272942333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1885693054","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":[0.9983518,0.00008207949,0.000868307,0.00007276175,0.0000070833944,0.00003178556,0.000009600956,0.0000044079216,0.0005721464],"genre_scores_gemma":[0.998546,0.00006525569,0.0010845662,0.000032701566,0.00000950043,0.00006519262,0.000012304709,0.000001988142,0.00018243678],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987626,0.00063902844,0.000067923385,0.00013807458,0.00031029916,0.00008217985],"domain_scores_gemma":[0.9848876,0.011475124,0.0012405051,0.0005332094,0.0009321935,0.0009313258],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034638483,0.0003995769,0.0002803737,0.00033542668,0.0003932092,0.0009885456,0.0002810093,0.00031564626,0.0011131109],"category_scores_gemma":[0.023494001,0.0001142074,0.00016439412,0.0002092389,0.0006204915,0.0006624152,0.00052162335,0.0003987787,0.0001074528],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0039280653,0.0036409341,0.668583,0.00043855578,0.00014922033,0.0008189512,0.021515429,0.0022400103,0.05396984,0.0008990551,0.00034576518,0.24347118],"study_design_scores_gemma":[0.00007401288,0.0040022135,0.9817224,0.000057706744,0.000040372106,0.00033438788,0.003818569,0.0031979484,0.005194296,0.00084339734,0.0006788648,0.000035768626],"about_ca_topic_score_codex":0.003393358,"about_ca_topic_score_gemma":0.0033155254,"teacher_disagreement_score":0.0034638483,"about_ca_system_score_codex":0.0003280487,"about_ca_system_score_gemma":0.00069866405,"threshold_uncertainty_score":0.018318832},"labels":[],"label_agreement":null},{"id":"W1889788879","doi":"10.1007/978-3-642-21043-3_11","title":"Learning Dialogue POMDP Models from Data","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Computer science; Partially observable Markov decision process; Artificial intelligence; Machine learning; Markov chain; Markov model","score_opus":0.05876410289242141,"score_gpt":0.24671100153610462,"score_spread":0.1879468986436832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1889788879","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022590706,0.0006924478,0.9710397,0.00050638424,0.00006492881,0.00010817635,0.0009219052,0.002759943,0.0013158196],"genre_scores_gemma":[0.54569083,0.0011665168,0.4403554,0.00033565756,0.00015282076,0.0007196842,0.006644356,0.00039166704,0.0045430795],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99936754,0.00020420736,0.000037374124,0.00023916965,0.00009369368,0.00005800112],"domain_scores_gemma":[0.9923332,0.0068621915,0.00013070021,0.00029987475,0.00024643133,0.00012764575],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020423157,0.0015644304,0.0017057395,0.0010763874,0.0005633179,0.0018133526,0.0019389883,0.0016753833,0.0046865935],"category_scores_gemma":[0.010638017,0.0015237639,0.0016593672,0.0010889284,0.00078785967,0.0029925401,0.0022180523,0.0041423785,0.0018231092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005250155,0.00026979504,0.0029371998,0.00041010053,0.00020671723,0.0001816286,0.00035336765,0.5679106,0.0015297208,0.014607188,0.008735497,0.4023331],"study_design_scores_gemma":[0.000028919103,0.00002571071,0.00010858164,0.000022986414,0.000017694321,0.000014717394,0.00003432107,0.97745353,0.00041284223,0.021222454,0.000650361,0.00000785475],"about_ca_topic_score_codex":0.006423347,"about_ca_topic_score_gemma":0.008315366,"teacher_disagreement_score":0.006423347,"about_ca_system_score_codex":0.0012808284,"about_ca_system_score_gemma":0.0012839424,"threshold_uncertainty_score":0.015678227},"labels":[],"label_agreement":null},{"id":"W1902572459","doi":"10.5589/q13-009","title":"Misunderstandings in ATC Communication: Language, Cognition, and Experimental Methodology<b>Misunderstandings in ATC Communication: Language, Cognition, and Experimental Methodology</b>","year":2013,"lang":"en","type":"article","venue":"Canadian aeronautics and space journal","topic":"Speech and dialogue systems","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":"Cognition; Psychology; Cognitive psychology; Computer science; Neuroscience","score_opus":0.071264209314285,"score_gpt":0.31815586372992144,"score_spread":0.24689165441563643,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1902572459","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":[0.87919337,0.0015102598,0.061545804,0.0047856416,0.0008564046,0.0065300646,0.0005303306,0.00020072337,0.04484743],"genre_scores_gemma":[0.9357199,0.0004971606,0.037842117,0.0020109538,0.0002911137,0.018309709,0.00041637482,0.00014357016,0.0047691404],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.93645734,0.050864514,0.0044258106,0.0029158788,0.004522852,0.00081352936],"domain_scores_gemma":[0.6831071,0.25667873,0.020099541,0.018208755,0.018854735,0.0030511182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.044143647,0.00077942177,0.00050169165,0.0025221452,0.0037542363,0.006417948,0.0018593001,0.0022357926,0.010830119],"category_scores_gemma":[0.22361669,0.0008496337,0.0009713069,0.001989718,0.00941014,0.0056448574,0.005114006,0.003204574,0.0013531935],"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":[0.0084093055,0.030410254,0.11848264,0.0037684655,0.00041707186,0.0009833334,0.2970338,0.0033849257,0.025993915,0.18933076,0.017276824,0.30450872],"study_design_scores_gemma":[0.0044420096,0.018612755,0.41333744,0.0040993188,0.00115852,0.002345438,0.15851884,0.015695663,0.051662456,0.24489833,0.0836117,0.0016175724],"about_ca_topic_score_codex":0.004317932,"about_ca_topic_score_gemma":0.0039502257,"teacher_disagreement_score":0.044143647,"about_ca_system_score_codex":0.004590875,"about_ca_system_score_gemma":0.005079302,"threshold_uncertainty_score":0.23345673},"labels":[],"label_agreement":null},{"id":"W191497374","doi":"10.5220/0001663801070114","title":"LEARNING USER INTENTIONS IN SPOKEN DIALOGUE SYSTEMS","year":2009,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence","score_opus":0.014544887455677977,"score_gpt":0.23421729434401703,"score_spread":0.21967240688833906,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W191497374","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11306119,0.00046326334,0.88294667,0.00039069136,0.000030229963,0.00010500419,0.00010799696,0.0010898854,0.0018050721],"genre_scores_gemma":[0.84791833,0.00023258352,0.14967237,0.000117119314,0.00003142595,0.0002155426,0.00031784756,0.0000939072,0.0014008769],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99655426,0.002279227,0.00015087522,0.000500619,0.00035568135,0.00015932636],"domain_scores_gemma":[0.9875409,0.010657215,0.00045853638,0.0003484873,0.00072410016,0.00027077188],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043014684,0.0006984077,0.0008589346,0.000815718,0.00060787314,0.0017863681,0.00089077407,0.001339665,0.0011881171],"category_scores_gemma":[0.01915642,0.0009027064,0.0007481417,0.00040148868,0.0011775133,0.002589016,0.0019572536,0.0016049448,0.000439033],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001204641,0.0005921771,0.024729466,0.0007570623,0.0003093994,0.00076747796,0.0073870835,0.5607864,0.014292171,0.034419496,0.003192249,0.35156226],"study_design_scores_gemma":[0.00003351041,0.0000966844,0.0013622756,0.000026509015,0.000024959836,0.000038227117,0.00033149563,0.9705127,0.0020128924,0.024769302,0.00076057314,0.000030907115],"about_ca_topic_score_codex":0.0035957443,"about_ca_topic_score_gemma":0.0041466197,"teacher_disagreement_score":0.0043014684,"about_ca_system_score_codex":0.00078936026,"about_ca_system_score_gemma":0.00092133175,"threshold_uncertainty_score":0.02274865},"labels":[],"label_agreement":null},{"id":"W1932882396","doi":"10.1109/icniconsmcl.2006.138","title":"M-learning: Overcoming the Usability Challenges of Mobile Devices","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"National Research Council Canada","funders":"","keywords":"Usability; Mobile device; Computer science; Mobile technology; Mobile computing; Human–computer interaction; TRIPS architecture; Multimedia; Field (mathematics); Mobile Web; Mobile telephony; World Wide Web; Telecommunications; Mobile radio","score_opus":0.016765429995522788,"score_gpt":0.23796584820569344,"score_spread":0.22120041821017067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1932882396","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18575747,0.022967273,0.6665549,0.009355071,0.000924125,0.0011854498,0.00011265659,0.0057891295,0.10735379],"genre_scores_gemma":[0.5477054,0.009399611,0.41368735,0.0027789092,0.0008036839,0.00058861414,0.00012666351,0.0006319143,0.024277974],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99819106,0.0007183956,0.0001128138,0.00011406842,0.0007450513,0.00011860063],"domain_scores_gemma":[0.9978974,0.0013217947,0.00013753919,0.00019759797,0.00034163464,0.000104002065],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017516544,0.0007236831,0.00046563428,0.0008082881,0.0008519247,0.0025627608,0.0011033766,0.0018402438,0.0030661472],"category_scores_gemma":[0.00571984,0.00023579315,0.0003801662,0.0004402685,0.0007044584,0.0038301633,0.0020134673,0.0007459654,0.001469494],"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":[0.00018063851,0.00015710662,0.0024540867,0.0015644042,0.000032674132,0.00069195154,0.0024424663,0.0006922489,0.026606027,0.00939785,0.009218712,0.9465618],"study_design_scores_gemma":[0.0002229396,0.004106073,0.017389955,0.002606034,0.00020876397,0.02679956,0.009979814,0.026600925,0.07340951,0.04993573,0.7883748,0.00036586926],"about_ca_topic_score_codex":0.0004042747,"about_ca_topic_score_gemma":0.0006665,"teacher_disagreement_score":0.0030661472,"about_ca_system_score_codex":0.0002874468,"about_ca_system_score_gemma":0.00045429362,"threshold_uncertainty_score":0.010257304},"labels":[],"label_agreement":null},{"id":"W1937565817","doi":"","title":"The effect of types of acoustical distortion on lexical access","year":2008,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Speech and dialogue systems","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":"University of Toronto","funders":"","keywords":"Distortion (music); Context (archaeology); Sentence; Acoustics; Speech recognition; Facilitation; Noise (video); Mathematics; Computer science; Psychology; Artificial intelligence; Physics; Telecommunications; Bandwidth (computing); Image (mathematics); Geology","score_opus":0.015808127853859766,"score_gpt":0.24608902376074335,"score_spread":0.23028089590688358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1937565817","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":[0.9965945,0.0002269771,0.001812381,0.00002631887,0.000024627338,0.000098666744,0.00009404087,0.000027442462,0.0010950683],"genre_scores_gemma":[0.99653614,0.0001808135,0.002401962,0.00005377267,0.000019282506,0.000052675012,0.00013117118,0.000044904973,0.00057939865],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99813807,0.00042346222,0.00026728472,0.00027792685,0.0007484935,0.00014471059],"domain_scores_gemma":[0.97956425,0.014197361,0.00251054,0.0015925822,0.0012785584,0.00085678045],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010739962,0.00059485313,0.0005713497,0.00047938724,0.00025062484,0.0008469458,0.0003768097,0.00048280228,0.0028093676],"category_scores_gemma":[0.01601857,0.00037201034,0.0003616271,0.00036989947,0.00071298354,0.00055065705,0.0007257613,0.0005947596,0.00043690918],"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":[0.019339144,0.0007815685,0.06499852,0.0005830134,0.00028764477,0.0011399594,0.0012407219,0.000985681,0.872285,0.00030837418,0.0001276338,0.037922736],"study_design_scores_gemma":[0.00036315958,0.009107291,0.7117118,0.000046927682,0.00046220826,0.0051577864,0.0011361374,0.0025096238,0.26684642,0.0006661197,0.0018520253,0.00014041598],"about_ca_topic_score_codex":0.0008115507,"about_ca_topic_score_gemma":0.0008307885,"teacher_disagreement_score":0.0028093676,"about_ca_system_score_codex":0.0002952531,"about_ca_system_score_gemma":0.00028297622,"threshold_uncertainty_score":0.009398282},"labels":[],"label_agreement":null},{"id":"W1938842985","doi":"","title":"Evaluating Salience Metrics for the Context-Adequate Realization of Discourse Referents","year":2011,"lang":"en","type":"article","venue":"OPUS (Augsburg University)","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":5,"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":"Simon Fraser University; Universität Potsdam","keywords":"Salience (neuroscience); Computer science; Realization (probability); Artificial intelligence; German; Phenomenon; Context (archaeology); Natural language processing; Cognitive psychology; Machine learning; Psychology; Linguistics; Mathematics; Epistemology; Statistics","score_opus":0.15114596213352932,"score_gpt":0.3107211362102565,"score_spread":0.15957517407672717,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1938842985","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":[0.71307135,0.0010846788,0.2777067,0.00041473596,0.00005072128,0.00022640424,0.0008464463,0.00056735,0.0060315244],"genre_scores_gemma":[0.94716334,0.0000968654,0.051259004,0.000024444507,0.00003054325,0.000102034304,0.0010012088,0.00005796317,0.00026451304],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99548244,0.0018607007,0.00044894876,0.0008980551,0.0010323325,0.00027755403],"domain_scores_gemma":[0.9518104,0.03875192,0.0034483676,0.002241138,0.0026841357,0.0010639919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010455989,0.000799512,0.00074225635,0.005211793,0.00091649656,0.0025922405,0.00076574273,0.00136866,0.0013206198],"category_scores_gemma":[0.051540438,0.0003476521,0.0005795471,0.0025342565,0.0014615079,0.0047709844,0.002269366,0.0013799125,0.00033022417],"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":[0.0022695418,0.000686635,0.22214633,0.00082987774,0.0006319344,0.00048241814,0.004892298,0.16764377,0.027150506,0.059188027,0.0066736406,0.507405],"study_design_scores_gemma":[0.00006223161,0.00055187,0.0823626,0.00007484735,0.00008035195,0.00026789223,0.0013508134,0.845453,0.010330082,0.056662716,0.0026792188,0.00012425538],"about_ca_topic_score_codex":0.0026940806,"about_ca_topic_score_gemma":0.003128164,"teacher_disagreement_score":0.010455989,"about_ca_system_score_codex":0.0017105726,"about_ca_system_score_gemma":0.0008574406,"threshold_uncertainty_score":0.055297256},"labels":[],"label_agreement":null},{"id":"W19448731","doi":"10.1139/y09-009","title":"Indirect Speech Acts and Collaborativeness in Human-Machine Dialogue Systems","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Physiology and Pharmacology","topic":"Speech and dialogue systems","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":"Computer science; Human communication; Human–machine system; Communication; Human–computer interaction; Speech recognition; Psychology","score_opus":0.01670327877508279,"score_gpt":0.2728446448523271,"score_spread":0.25614136607724436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W19448731","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4434731,0.004151319,0.4850141,0.0034422916,0.0003041995,0.00018858029,0.00034604804,0.0015728233,0.06150767],"genre_scores_gemma":[0.97649837,0.00033067382,0.019626841,0.000098106735,0.00010820101,0.00008966903,0.00011062726,0.000048880232,0.0030885292],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9975249,0.0013336604,0.00013904127,0.0004916412,0.00035223682,0.00015850944],"domain_scores_gemma":[0.9920216,0.005853572,0.00065150217,0.0005266092,0.00052934024,0.00041736278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017959926,0.00057224405,0.00053427764,0.00081395655,0.0010792885,0.0034048415,0.0007268068,0.0013963598,0.004664005],"category_scores_gemma":[0.010924847,0.00043996936,0.0004835756,0.00050644524,0.0029667516,0.004700221,0.0026149673,0.0007365004,0.00064008177],"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":[0.0013235328,0.0003466413,0.016577953,0.0011565812,0.00037312918,0.003567869,0.025750529,0.06757041,0.06116738,0.5944536,0.005345382,0.22236706],"study_design_scores_gemma":[0.00020596878,0.0006401091,0.014400498,0.00013522302,0.00018334361,0.00193736,0.0041582463,0.26155567,0.011073546,0.6839588,0.02150859,0.00024264242],"about_ca_topic_score_codex":0.0008751587,"about_ca_topic_score_gemma":0.00044429355,"teacher_disagreement_score":0.004664005,"about_ca_system_score_codex":0.00067856064,"about_ca_system_score_gemma":0.00047164346,"threshold_uncertainty_score":0.015602648},"labels":[],"label_agreement":null},{"id":"W1962650116","doi":"10.2312/egve/egve01/041-050","title":"On the Utility of Semantic Constraints","year":2001,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"York University","funders":"","keywords":"Computer science; Semantics (computer science); Human–computer interaction; Process (computing); Computer graphics; Object (grammar); User interface; Graphics; Interface (matter); Artificial intelligence; Programming language; Computer graphics (images)","score_opus":0.030446317492233338,"score_gpt":0.2408813149117861,"score_spread":0.21043499741955277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1962650116","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12863939,0.0037519909,0.80944693,0.0028598981,0.00018532132,0.00024562795,0.00032797197,0.0014286713,0.0531142],"genre_scores_gemma":[0.73642653,0.0017659458,0.2565533,0.00030178076,0.00013767798,0.00018103332,0.0003166423,0.00061009143,0.0037070906],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9923395,0.0045500877,0.00035546103,0.0004818204,0.0018959522,0.00037714464],"domain_scores_gemma":[0.9420201,0.05000898,0.001094206,0.004179973,0.0022858276,0.00041084492],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005753835,0.0010067942,0.0007252756,0.0018311422,0.0014946372,0.0040000784,0.0013338323,0.0019199373,0.007299975],"category_scores_gemma":[0.048982807,0.0008095877,0.0008755103,0.0016495365,0.004030387,0.0130260745,0.0037247525,0.0018876322,0.001000951],"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":[0.0012648,0.00018933942,0.0026513736,0.0007227916,0.00009772093,0.00031592298,0.0018181968,0.064578354,0.011168106,0.5913914,0.0044639916,0.321338],"study_design_scores_gemma":[0.00016866963,0.00037000564,0.0021711523,0.00025839097,0.00016524659,0.0005145907,0.0013045842,0.37237027,0.017855793,0.57176864,0.032913726,0.00013901775],"about_ca_topic_score_codex":0.0031272825,"about_ca_topic_score_gemma":0.0027474952,"teacher_disagreement_score":0.007299975,"about_ca_system_score_codex":0.0010735451,"about_ca_system_score_gemma":0.0010654238,"threshold_uncertainty_score":0.030429542},"labels":[],"label_agreement":null},{"id":"W1974722138","doi":"10.1121/1.4784172","title":"Function words of lexical bundles: The relation of frequency and reduction.","year":2009,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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 Alberta","funders":"","keywords":"Predictability; Reduction (mathematics); Word (group theory); Computer science; Word lists by frequency; Speech recognition; Speech production; Function (biology); Duration (music); Mathematics; Linguistics; Natural language processing; Acoustics; Statistics; Physics; Biology","score_opus":0.011750555454096872,"score_gpt":0.2316533026103731,"score_spread":0.21990274715627622,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1974722138","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":[0.9881698,0.0008679186,0.007349664,0.00006624445,0.00003239229,0.00004276916,0.00018947099,0.0000875054,0.0031941854],"genre_scores_gemma":[0.99425346,0.00023935502,0.0047153807,0.000024252464,0.000021329897,0.00004923098,0.00021211423,0.000046518053,0.0004383543],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990081,0.00018407805,0.00010251946,0.0002173469,0.00044815295,0.00003977434],"domain_scores_gemma":[0.98756987,0.007677076,0.002685321,0.00087792595,0.00085384055,0.00033585148],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076304685,0.0003275387,0.000343827,0.0010347082,0.00026686967,0.0009195708,0.00031028345,0.00038630897,0.0024693462],"category_scores_gemma":[0.018341336,0.00030597663,0.0001989419,0.0005670786,0.0006620589,0.0010463588,0.00071993866,0.00055141095,0.0003814012],"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":[0.002850175,0.00034737805,0.13000815,0.0005509011,0.0002517225,0.0005718956,0.0037936668,0.0012989914,0.6807521,0.0022055712,0.0004642487,0.17690524],"study_design_scores_gemma":[0.000037390357,0.0014162967,0.93634593,0.000052825086,0.00017847215,0.0024965398,0.000994258,0.0053327796,0.04645814,0.0042056353,0.0024142272,0.00006753075],"about_ca_topic_score_codex":0.00069036905,"about_ca_topic_score_gemma":0.00068307354,"teacher_disagreement_score":0.0024693462,"about_ca_system_score_codex":0.00026284056,"about_ca_system_score_gemma":0.00020644195,"threshold_uncertainty_score":0.008260846},"labels":[],"label_agreement":null},{"id":"W1975462382","doi":"10.1037/0278-7393.27.3.614","title":"Two modes of transfer in artificial grammar learning.","year":2001,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":97,"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":"Analogy; Grammar; Vocabulary; Repetition (rhetorical device); Basis (linear algebra); Natural language processing; Computer science; Transfer of learning; Artificial intelligence; Linguistics; Transfer (computing); Cognitive science; Psychology; Mathematics; Philosophy","score_opus":0.03329097887757934,"score_gpt":0.32124600960691285,"score_spread":0.2879550307293335,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1975462382","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":[0.6287352,0.001268375,0.26407346,0.006783093,0.00032520675,0.0006940493,0.00030686858,0.0011901129,0.09662367],"genre_scores_gemma":[0.9692485,0.00018615983,0.0238273,0.0003578863,0.00004810062,0.0006460977,0.000094527626,0.000055982433,0.005535469],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99718696,0.0010633433,0.00011903401,0.00079254893,0.00062091084,0.00021729709],"domain_scores_gemma":[0.9891599,0.0050249076,0.0008237296,0.004187583,0.0004032528,0.0004005793],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034538272,0.00050446385,0.0004935878,0.0006690855,0.00038670303,0.00222452,0.0015959541,0.0023822438,0.00723387],"category_scores_gemma":[0.025140258,0.00066582445,0.00063728326,0.00028783426,0.0049315766,0.0077740457,0.0054672677,0.0023408772,0.0011980839],"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":[0.0011375733,0.0012150899,0.013523169,0.0006949944,0.00020225096,0.00068332517,0.011860123,0.0065886495,0.038359668,0.61201763,0.0035203244,0.31019717],"study_design_scores_gemma":[0.00028691578,0.0006318089,0.009030036,0.00006393957,0.000054143642,0.0011379058,0.0010877011,0.025045946,0.013457761,0.94315076,0.0059653567,0.000087779685],"about_ca_topic_score_codex":0.00024017687,"about_ca_topic_score_gemma":0.00014452035,"teacher_disagreement_score":0.00723387,"about_ca_system_score_codex":0.0006529039,"about_ca_system_score_gemma":0.00054077804,"threshold_uncertainty_score":0.024199665},"labels":[],"label_agreement":null},{"id":"W197629641","doi":"","title":"Multimodal field data entry:performance and usability issues","year":2006,"lang":"en","type":"book-chapter","venue":"NPARC","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":11,"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":"Usability; Field (mathematics); Scope (computer science); Computer science; Context (archaeology); Human–computer interaction; Usability engineering; Data collection; Engineering; Systems engineering","score_opus":0.027943830339773875,"score_gpt":0.25279745486726946,"score_spread":0.22485362452749558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W197629641","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":[0.5333826,0.019553218,0.28462347,0.008955374,0.0004759843,0.0034178451,0.0010027466,0.007427449,0.14116128],"genre_scores_gemma":[0.7366564,0.0059354226,0.21027942,0.0010514689,0.0003502853,0.0022130462,0.0007949639,0.0013850427,0.04133393],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9852976,0.008285472,0.00073153735,0.0007625368,0.0046498613,0.0002730274],"domain_scores_gemma":[0.91391665,0.07240193,0.0008299189,0.003133856,0.009165516,0.0005520786],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021838123,0.0009054879,0.00088676426,0.0014889707,0.0009628619,0.005397449,0.0025723015,0.0015124651,0.009750205],"category_scores_gemma":[0.053997062,0.00042943316,0.00040768913,0.0017996134,0.0008961837,0.003899346,0.0014473544,0.0007313712,0.0033328037],"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":[0.0006216102,0.00039215235,0.0045095454,0.002469829,0.000037122798,0.0004485712,0.006963348,0.0010775425,0.022518577,0.0037363542,0.013479132,0.9437462],"study_design_scores_gemma":[0.0010387388,0.022936597,0.16474918,0.0074981553,0.00089665625,0.019731855,0.042760152,0.09756317,0.25294787,0.03183787,0.35668653,0.001353269],"about_ca_topic_score_codex":0.0013646964,"about_ca_topic_score_gemma":0.0021336207,"teacher_disagreement_score":0.021838123,"about_ca_system_score_codex":0.0011450534,"about_ca_system_score_gemma":0.00076302607,"threshold_uncertainty_score":0.11549246},"labels":[],"label_agreement":null},{"id":"W1978078764","doi":"10.1016/j.artint.2006.05.003","title":"Generating and evaluating evaluative arguments","year":2006,"lang":"en","type":"article","venue":"Artificial Intelligence","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":191,"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":"Argumentation theory; Argument (complex analysis); Computer science; Process (computing); Computational linguistics; Test (biology); Natural (archaeology); Computational model; Natural language; Artificial intelligence; Natural language generation; Selection (genetic algorithm); Management science; Psychology; Epistemology","score_opus":0.08029450825717041,"score_gpt":0.3471274194884037,"score_spread":0.2668329112312333,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1978078764","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.25778487,0.0007193945,0.6875207,0.002859438,0.0004219196,0.00079111813,0.0004735263,0.005652398,0.043776687],"genre_scores_gemma":[0.73813653,0.00023769845,0.2531649,0.00021454123,0.00018591483,0.00019808147,0.0007434252,0.00047239443,0.0066464883],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99235874,0.0037178418,0.00042064834,0.0009244534,0.0021701239,0.0004082487],"domain_scores_gemma":[0.9620112,0.029829474,0.001578509,0.0020506633,0.0039565153,0.00057373784],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007867843,0.0010813479,0.00090595474,0.0024004276,0.0011217907,0.005713544,0.002116523,0.0030892324,0.010169298],"category_scores_gemma":[0.0566094,0.0006756181,0.0010290522,0.00086641184,0.0013858626,0.0055563524,0.0023050208,0.002061045,0.0024656034],"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":[0.0015096368,0.0009899694,0.014037151,0.00105275,0.00034591256,0.0017884877,0.0068636443,0.040165957,0.03984568,0.21350019,0.018595632,0.66130495],"study_design_scores_gemma":[0.00021670826,0.00042037986,0.005209159,0.00041367486,0.0003538116,0.00055716914,0.0025849526,0.65226376,0.070654765,0.2370512,0.030157879,0.00011644469],"about_ca_topic_score_codex":0.00088108674,"about_ca_topic_score_gemma":0.0013273541,"teacher_disagreement_score":0.010169298,"about_ca_system_score_codex":0.0014333308,"about_ca_system_score_gemma":0.0014812717,"threshold_uncertainty_score":0.041609645},"labels":[],"label_agreement":null},{"id":"W1979347445","doi":"10.3115/1117736.1117751","title":"Flexible speech act based dialogue management","year":2000,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Simon Fraser University","funders":"Norges Forskningsråd","keywords":"Computer science; Speech act; Natural language processing; Artificial intelligence; Linguistics","score_opus":0.013131159542034069,"score_gpt":0.2279978512778446,"score_spread":0.21486669173581055,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979347445","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01591309,0.00026264234,0.9447068,0.00026860292,0.00010931784,0.00024664,0.00031133887,0.030305859,0.0078756185],"genre_scores_gemma":[0.6124965,0.00019545789,0.37133425,0.00029002823,0.0001226099,0.0004484467,0.0012228948,0.0013415802,0.012548248],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99810696,0.0006127071,0.000119863995,0.0004610219,0.0005387975,0.00016073967],"domain_scores_gemma":[0.9980963,0.00086657435,0.000106363164,0.00044927115,0.00032607862,0.00015537029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023903807,0.0010131911,0.0008482877,0.0008540766,0.0008636095,0.0027162563,0.0024145113,0.0011915325,0.0056813797],"category_scores_gemma":[0.0044336305,0.00047179798,0.0005926275,0.0003781781,0.0009313231,0.0021877964,0.0024022635,0.001496709,0.0034148311],"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":[0.0013804954,0.00071950426,0.0032586432,0.00044007882,0.00026736726,0.0011303879,0.0030167717,0.098935336,0.10339852,0.065645635,0.034933396,0.68687385],"study_design_scores_gemma":[0.00006164621,0.0001027408,0.00088080537,0.00003763667,0.00007020387,0.00021635718,0.00019135255,0.88012743,0.04481174,0.046333496,0.027074685,0.0000919341],"about_ca_topic_score_codex":0.0020104647,"about_ca_topic_score_gemma":0.0017645621,"teacher_disagreement_score":0.0056813797,"about_ca_system_score_codex":0.0005409188,"about_ca_system_score_gemma":0.0007565586,"threshold_uncertainty_score":0.019006073},"labels":[],"label_agreement":null},{"id":"W1979532929","doi":"10.3758/s13428-012-0210-4","title":"Age-of-acquisition ratings for 30,000 English words","year":2012,"lang":"en","type":"article","venue":"Behavior Research Methods","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":1250,"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":"Economic and Social Research Council","keywords":"Age of Acquisition; Vocabulary; Lexicon; Noun; Crowdsourcing; Computer science; Psychology; Natural language processing; Word (group theory); Variance (accounting); Similarity (geometry); Correlation; Artificial intelligence; Linguistics; Statistics; Mathematics; Cognition; World Wide Web","score_opus":0.2541210475944673,"score_gpt":0.5307494941877987,"score_spread":0.2766284465933314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1979532929","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":[0.9928665,0.00015070286,0.00025892895,0.00002423439,0.000044635803,0.00008411236,0.0009470966,0.000029176774,0.0055946424],"genre_scores_gemma":[0.984288,0.00027497517,0.0009805294,0.00008544661,0.00004387606,0.00014438403,0.0026458835,0.0000326668,0.011504188],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99884737,0.00021048877,0.00021759374,0.00017132457,0.0004300819,0.00012313465],"domain_scores_gemma":[0.97860706,0.008067862,0.003168167,0.0011242967,0.007026969,0.002005768],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021995804,0.00040113862,0.00044783382,0.0010882993,0.0003608512,0.00066949305,0.0002510975,0.0006906432,0.0064243185],"category_scores_gemma":[0.017401328,0.00021569077,0.00049273577,0.00025300146,0.00023455588,0.00097355025,0.0007124637,0.000610126,0.0033210467],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0040418063,0.0015110775,0.9128309,0.00021314253,0.00019923267,0.00043394722,0.0049273307,0.00054288766,0.024386179,0.0001883218,0.0033657602,0.04735943],"study_design_scores_gemma":[0.000016935595,0.0013944532,0.99410534,0.0000127934645,0.000028393233,0.00021793663,0.00071691367,0.00024039722,0.0019151584,0.000029770497,0.0013025342,0.00001931144],"about_ca_topic_score_codex":0.002724173,"about_ca_topic_score_gemma":0.008078604,"teacher_disagreement_score":0.0064243185,"about_ca_system_score_codex":0.00024998267,"about_ca_system_score_gemma":0.00019678666,"threshold_uncertainty_score":0.021491468},"labels":[],"label_agreement":null},{"id":"W1980200929","doi":"10.1121/1.3248650","title":"Talking heads: Speech synthesis and embodied cognition.","year":2009,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Embodied cognition; Computer science; Salient; Cognition; Cognitive science; Presentation (obstetrics); Human–computer interaction; Replicate; Kinematics; Artificial intelligence; Psychology; Neuroscience","score_opus":0.012946786966891789,"score_gpt":0.24027001871643308,"score_spread":0.2273232317495413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1980200929","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0079305535,0.5245927,0.24564701,0.011995569,0.0058199554,0.00007446981,0.00048591878,0.0014513622,0.20200244],"genre_scores_gemma":[0.39467058,0.3315893,0.10493727,0.005960771,0.0120923035,0.00052228064,0.0014834115,0.0007373201,0.14800674],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995902,0.00018688482,0.000027864073,0.00006727065,0.000089077745,0.000038671376],"domain_scores_gemma":[0.9995683,0.0002714088,0.000034171404,0.000036672347,0.00005377532,0.00003563903],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077574316,0.001044084,0.0005719829,0.0015967193,0.0005339847,0.00333275,0.0007855671,0.0026289606,0.013081123],"category_scores_gemma":[0.0021181148,0.00027749973,0.00037093324,0.0012442014,0.002393568,0.0046287887,0.0019644268,0.0013987342,0.0033493952],"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":[0.00008975554,0.00002432461,0.00036092056,0.001286543,0.000053134292,0.00049577834,0.0031444286,0.0015953624,0.0028136952,0.6053481,0.044559836,0.3402281],"study_design_scores_gemma":[0.000019041114,0.00007270609,0.0011167538,0.0010933402,0.000042746193,0.0014380186,0.0014163717,0.005300866,0.0021049015,0.5988015,0.3885335,0.000060242768],"about_ca_topic_score_codex":0.00070384296,"about_ca_topic_score_gemma":0.00077963306,"teacher_disagreement_score":0.013081123,"about_ca_system_score_codex":0.00056744844,"about_ca_system_score_gemma":0.00047803836,"threshold_uncertainty_score":0.043760777},"labels":[],"label_agreement":null},{"id":"W1981289880","doi":"10.1016/j.camwa.2007.07.009","title":"Focus to emphasize tone analysis for prosodic generation","year":2008,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Speech and dialogue systems","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":"York University; Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Royal Golden Jubilee (RGJ) Ph.D. Programme","keywords":"Focus (optics); Prosody; Intonation (linguistics); Utterance; Sentence; Computer science; Tone (literature); Ambiguity; Set (abstract data type); Speech recognition; Linguistics; Natural language processing","score_opus":0.03761260299924934,"score_gpt":0.27818334763036834,"score_spread":0.240570744631119,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1981289880","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018593008,0.00023798813,0.9680995,0.00010713164,0.00019882416,0.00013731162,0.00036081768,0.0025045138,0.0097610215],"genre_scores_gemma":[0.34948528,0.00042763364,0.6357509,0.0002053125,0.00021139394,0.00038647983,0.0009831486,0.0017515414,0.0107983565],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99969816,0.00007820937,0.000013036274,0.00009496758,0.000072574854,0.000043120566],"domain_scores_gemma":[0.9992385,0.00028759774,0.0000311768,0.00015784551,0.00023083072,0.000054028587],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006122718,0.00092074863,0.0003871069,0.00084613264,0.0007397002,0.0012146113,0.0008095356,0.00063371944,0.023043511],"category_scores_gemma":[0.002155975,0.00045229107,0.0004514068,0.00062393665,0.00035189255,0.0013480387,0.0011088754,0.0011562081,0.005363546],"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":[0.00092822564,0.0001473148,0.00082157215,0.0002764891,0.00006364831,0.00028538253,0.0006432093,0.0037396238,0.26779518,0.032959346,0.00922628,0.6831139],"study_design_scores_gemma":[0.0002789106,0.0010488894,0.010175307,0.00025551327,0.00034208834,0.0013118866,0.0009038543,0.48490173,0.35435513,0.054244377,0.09202951,0.00015281691],"about_ca_topic_score_codex":0.00082551467,"about_ca_topic_score_gemma":0.0012836838,"teacher_disagreement_score":0.023043511,"about_ca_system_score_codex":0.00023387298,"about_ca_system_score_gemma":0.00035289908,"threshold_uncertainty_score":0.07708824},"labels":[],"label_agreement":null},{"id":"W1987206778","doi":"10.1145/1978942.1979414","title":"Augmenting the web for second language vocabulary learning","year":2011,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":36,"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":"University of Toronto","keywords":"Computer science; Vocabulary; World Wide Web; Context (archaeology); Web page; Casual; Foreign language; Set (abstract data type); Artificial intelligence; Multimedia; Natural language processing; Linguistics; Mathematics education; Psychology","score_opus":0.02496691861523299,"score_gpt":0.22587969885842688,"score_spread":0.2009127802431939,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987206778","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":[0.83652955,0.0011743653,0.11591681,0.00073603145,0.00011620697,0.00039376228,0.00019302838,0.006761803,0.038178504],"genre_scores_gemma":[0.8454787,0.0009740428,0.14404254,0.00026595095,0.000048072718,0.00026837265,0.000344128,0.00018142385,0.008396755],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996394,0.00015158844,0.000016925633,0.000052612315,0.00009677938,0.000042707925],"domain_scores_gemma":[0.9976853,0.0016095481,0.00008908087,0.00034429147,0.00017473988,0.00009710104],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006742349,0.00043570175,0.0002916341,0.00036037457,0.00022288806,0.0010877205,0.00046749425,0.0005044107,0.005609869],"category_scores_gemma":[0.004453865,0.00016997724,0.00036205724,0.00030153603,0.0002397856,0.0023304592,0.001145772,0.00037677505,0.0013909858],"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":[0.0007011279,0.0031039235,0.012287934,0.00084910257,0.00007149537,0.001015702,0.0045241443,0.002198694,0.10631948,0.0024241218,0.005410317,0.8610939],"study_design_scores_gemma":[0.00084867346,0.01322549,0.1354611,0.0012836095,0.0009536812,0.012934855,0.01264606,0.08322555,0.20728563,0.032730468,0.4989333,0.0004716955],"about_ca_topic_score_codex":0.00049681787,"about_ca_topic_score_gemma":0.0010818018,"teacher_disagreement_score":0.005609869,"about_ca_system_score_codex":0.00009498887,"about_ca_system_score_gemma":0.00020983987,"threshold_uncertainty_score":0.01876688},"labels":[],"label_agreement":null},{"id":"W1987933202","doi":"10.1007/s10707-009-0079-2","title":"Evaluating the benefits of multimodal interface design for CoMPASS—a mobile GIS","year":2009,"lang":"en","type":"article","venue":"GeoInformatica","topic":"Speech and dialogue systems","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 Ottawa","funders":"","keywords":"Compass; Georeference; Geography; Interface (matter); Cartography; Computer science; Interface design; Geographic information system; Human–computer interaction; Remote sensing; Physical geography","score_opus":0.06374303628024089,"score_gpt":0.32852780529905923,"score_spread":0.2647847690188183,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1987933202","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":[0.9854403,0.0002327851,0.009649613,0.00018806601,0.0000576283,0.00036445592,0.00014377038,0.0002039435,0.0037192944],"genre_scores_gemma":[0.9739446,0.00014526227,0.023539761,0.000083880266,0.000034200177,0.0002921372,0.0001638299,0.00007959973,0.00171666],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9962935,0.0025307313,0.00024846848,0.00017486225,0.0006082891,0.0001441301],"domain_scores_gemma":[0.9748584,0.021307303,0.00065160467,0.0006767277,0.0019899707,0.0005159297],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037951511,0.0008185718,0.0004468986,0.00058147893,0.00040851306,0.001579567,0.000773658,0.0012388616,0.008044526],"category_scores_gemma":[0.041493632,0.00034235528,0.00040961336,0.0003771774,0.0005102708,0.002088826,0.001288423,0.00058832637,0.00078560004],"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":[0.09980098,0.010483824,0.050889973,0.0063873534,0.0009441143,0.0011655181,0.010218581,0.0657552,0.16435859,0.00590045,0.005728208,0.57836723],"study_design_scores_gemma":[0.0121788215,0.16415378,0.14899759,0.00095189404,0.0059212376,0.0020751245,0.014428402,0.45375016,0.15566458,0.0077271364,0.033504,0.00064720365],"about_ca_topic_score_codex":0.002596338,"about_ca_topic_score_gemma":0.0026284757,"teacher_disagreement_score":0.008044526,"about_ca_system_score_codex":0.0006383041,"about_ca_system_score_gemma":0.00054195785,"threshold_uncertainty_score":0.026911557},"labels":[],"label_agreement":null},{"id":"W1993970308","doi":"10.1111/j.1756-8765.2012.01182.x","title":"To Name or to Describe: Shared Knowledge Affects Referential Form","year":2012,"lang":"en","type":"article","venue":"Topics in Cognitive Science","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":137,"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":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institutes of Health; National Science Foundation","keywords":"Grice; Affect (linguistics); Expression (computer science); Computer science; Production (economics); Linguistics; Order (exchange); Common knowledge (logic); Psychology; Epistemology; Communication; Artificial intelligence; Pragmatics; Philosophy; Epistemic modal logic","score_opus":0.09457964928721374,"score_gpt":0.35645059222702175,"score_spread":0.261870942939808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993970308","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":[0.7528942,0.00094513764,0.0429551,0.0033676487,0.000113070004,0.000104199746,0.0001746046,0.00059108634,0.19885497],"genre_scores_gemma":[0.99222505,0.00013789163,0.0040471423,0.00025900043,0.000023526873,0.000026387372,0.000065148815,0.0001565506,0.0030592466],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.9863708,0.008184068,0.00042673634,0.0019378487,0.0024703636,0.0006102225],"domain_scores_gemma":[0.95304805,0.03439497,0.0037854097,0.005169716,0.0024858087,0.0011159588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007113379,0.0005043396,0.00046652713,0.0007410831,0.0018828947,0.006652078,0.0010672539,0.0029116205,0.013154581],"category_scores_gemma":[0.051899005,0.0005723894,0.00038260146,0.000593021,0.0046314364,0.015488574,0.006623084,0.00279456,0.0015896132],"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":[0.0012262915,0.00068615226,0.055694282,0.00086147676,0.00019283903,0.002428869,0.34841603,0.0031704581,0.079158194,0.33572617,0.00791389,0.16452532],"study_design_scores_gemma":[0.00032898996,0.0011649944,0.15967554,0.000593214,0.0006784643,0.006629951,0.13671345,0.0241718,0.026188172,0.56522226,0.07806443,0.00056868285],"about_ca_topic_score_codex":0.0021256043,"about_ca_topic_score_gemma":0.0011588307,"teacher_disagreement_score":0.013154581,"about_ca_system_score_codex":0.0012489758,"about_ca_system_score_gemma":0.00091804797,"threshold_uncertainty_score":0.044006526},"labels":[],"label_agreement":null},{"id":"W1998584145","doi":"10.1109/ais.2010.5547015","title":"Automated planning of tutorial dialogues","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 de Sherbrooke","funders":"","keywords":"Computer science; Planner; Nondeterministic algorithm; Plan (archaeology); Ask price; Artificial intelligence; Automated planning and scheduling; Human–computer interaction; Tree (set theory); Intelligent tutoring system; Machine learning; Theoretical computer science","score_opus":0.019714785792075612,"score_gpt":0.26076427430706767,"score_spread":0.24104948851499206,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998584145","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.05948945,0.0005357181,0.9273447,0.00034028132,0.00004173337,0.00027079778,0.0003073051,0.005631945,0.006038059],"genre_scores_gemma":[0.595271,0.0004759536,0.3997399,0.000058599566,0.00003299764,0.00028976996,0.0007202713,0.00027266474,0.0031389084],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99871504,0.0007334544,0.00007137724,0.0002004426,0.0001972547,0.00008238451],"domain_scores_gemma":[0.99792767,0.0014676782,0.00013546972,0.00015470138,0.00021008229,0.00010435315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012780566,0.00074272125,0.00053639297,0.0006725698,0.00088728144,0.0011620938,0.00076477544,0.00087281194,0.0031716723],"category_scores_gemma":[0.005751743,0.0004725489,0.00048528283,0.00030888917,0.00077531376,0.0011808426,0.0011065275,0.0006582095,0.0007156095],"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":[0.0007161434,0.00022611942,0.0035197698,0.00067334785,0.00008368613,0.0011944947,0.002848308,0.44248873,0.03809685,0.053559355,0.007838108,0.44875506],"study_design_scores_gemma":[0.00006688618,0.00012854712,0.0008146685,0.000049509734,0.00003941467,0.0002239107,0.00043479074,0.93947786,0.014033244,0.030957961,0.013731401,0.00004187515],"about_ca_topic_score_codex":0.0035116037,"about_ca_topic_score_gemma":0.005510531,"teacher_disagreement_score":0.0035116037,"about_ca_system_score_codex":0.0006936663,"about_ca_system_score_gemma":0.001629664,"threshold_uncertainty_score":0.010610342},"labels":[],"label_agreement":null},{"id":"W2002392467","doi":"10.4000/alsic.1861","title":"Rapport du congrès EUROCALL 2000 et du symposium InSTIL 2000 (Dundee, Ecosse)","year":2000,"lang":"fr","type":"article","venue":"Alsic","topic":"Speech and dialogue systems","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":"Humanities; Art","score_opus":0.031144728413065568,"score_gpt":0.24024870986278668,"score_spread":0.20910398144972112,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2002392467","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":[0.012761616,0.0700084,0.024094135,0.09956147,0.49693283,0.00087027426,0.00462251,0.0029174709,0.28823125],"genre_scores_gemma":[0.016646378,0.015900034,0.006037215,0.0068085636,0.032511257,0.00046346686,0.0039696107,0.0017129545,0.9159505],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9951467,0.0009244245,0.00022095014,0.00091750134,0.0019502713,0.0008400638],"domain_scores_gemma":[0.9907136,0.0007755898,0.00031294595,0.00055211043,0.00401528,0.0036304463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005610736,0.0024259917,0.0014012033,0.003211309,0.0023015146,0.00953274,0.0025021061,0.0041786805,0.15092078],"category_scores_gemma":[0.008443475,0.0006363774,0.0012269708,0.0015360592,0.001001721,0.0047991625,0.0057655415,0.004294679,0.083004616],"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":[0.00030186385,0.00011275471,0.00035534112,0.0002135051,0.000018498175,0.00019864913,0.00023319447,0.00031644022,0.0010773285,0.0042032567,0.9184117,0.07455748],"study_design_scores_gemma":[0.000013548456,0.000047292593,0.00037140193,0.00011528593,0.0000070382575,0.000076434946,0.00015021101,0.0001823018,0.0004146227,0.00057062216,0.99803656,0.000014585652],"about_ca_topic_score_codex":0.009095298,"about_ca_topic_score_gemma":0.013465374,"teacher_disagreement_score":0.15092078,"about_ca_system_score_codex":0.004388518,"about_ca_system_score_gemma":0.0055330126,"threshold_uncertainty_score":0.5048803},"labels":[],"label_agreement":null},{"id":"W2010415250","doi":"10.1121/1.4755413","title":"Predictability effects on vowel realization in spontaneous speech","year":2012,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Vowel; Realization (probability); Context (archaeology); Word (group theory); Computer science; Predictability; Formant; WordNet; Linguistics; Speech recognition; Natural language processing; Mathematics; Statistics; History","score_opus":0.008918392012123544,"score_gpt":0.23661470780022228,"score_spread":0.22769631578809874,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2010415250","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":[0.9934002,0.000093185845,0.0024415348,0.000023927882,0.000020225305,0.000028934632,0.00028298688,0.00006828222,0.0036406664],"genre_scores_gemma":[0.997618,0.000058069458,0.0013752475,0.000011548672,0.000011898607,0.000058869166,0.000405517,0.00006166583,0.00039910877],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9983107,0.0005375124,0.00015020928,0.00039129742,0.000517973,0.00009234025],"domain_scores_gemma":[0.9870488,0.009810436,0.000958851,0.0010672383,0.0007360752,0.00037856714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015332841,0.0003639537,0.0003362098,0.00036421107,0.0004493739,0.0014904524,0.00028232383,0.00027532794,0.003841631],"category_scores_gemma":[0.014252374,0.0003315393,0.0002612065,0.00024916077,0.000645849,0.0007579911,0.0010173367,0.00047369627,0.00052156544],"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":[0.007902815,0.0011075255,0.152581,0.0010870289,0.0003431625,0.0009065968,0.009484541,0.005676948,0.70947146,0.004100345,0.0012301949,0.10610843],"study_design_scores_gemma":[0.00010844994,0.0025443677,0.93367463,0.000048174326,0.00015376316,0.00064710726,0.0013796288,0.0069870395,0.049782127,0.0027385564,0.001835809,0.00010039913],"about_ca_topic_score_codex":0.0009837141,"about_ca_topic_score_gemma":0.0011856079,"teacher_disagreement_score":0.003841631,"about_ca_system_score_codex":0.0003129549,"about_ca_system_score_gemma":0.0002782102,"threshold_uncertainty_score":0.012851536},"labels":[],"label_agreement":null},{"id":"W2011408835","doi":"10.1007/s10772-014-9244-6","title":"Dialogue POMDP components (part I): learning states and observations","year":2014,"lang":"en","type":"article","venue":"International Journal of Speech Technology","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Partially observable Markov decision process; Computer science; Artificial intelligence; Context (archaeology); Machine learning; Process (computing); Set (abstract data type); Markov model; Markov chain","score_opus":0.018496216936909258,"score_gpt":0.24163162216468634,"score_spread":0.22313540522777708,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2011408835","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022529464,0.0002792068,0.9646601,0.0002346744,0.000093418894,0.00035583848,0.0010796546,0.0017526589,0.009014952],"genre_scores_gemma":[0.49863,0.0005240998,0.48228925,0.00013322817,0.00009297261,0.0008609987,0.0025177205,0.0005091499,0.014442517],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994375,0.00012722868,0.000038012982,0.00021013364,0.00014000441,0.000047151043],"domain_scores_gemma":[0.99903584,0.0005275487,0.000064104956,0.00016110177,0.0001679695,0.00004356425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00088448287,0.00082238164,0.00058489596,0.0003325827,0.00036403092,0.0018463377,0.0010602019,0.0009048609,0.012855056],"category_scores_gemma":[0.0061449814,0.0006188284,0.00076288,0.0004098815,0.0007621443,0.0022409556,0.0011900181,0.0016407523,0.0025067911],"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":[0.0008020483,0.00041319823,0.012309902,0.00088156096,0.00019267893,0.00046033127,0.0021808567,0.19307151,0.03228014,0.102510884,0.0093333395,0.6455636],"study_design_scores_gemma":[0.000061223094,0.00032437572,0.013288772,0.00019373377,0.00014225594,0.00025140998,0.00046141725,0.80870557,0.047615755,0.10236093,0.02649376,0.000100909405],"about_ca_topic_score_codex":0.004901627,"about_ca_topic_score_gemma":0.002867171,"teacher_disagreement_score":0.012855056,"about_ca_system_score_codex":0.0007272318,"about_ca_system_score_gemma":0.0012918045,"threshold_uncertainty_score":0.043004453},"labels":[],"label_agreement":null},{"id":"W2014301369","doi":"10.1145/1409240.1409284","title":"Evaluating the appropriateness of speech input in marine applications","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"National Research Council Canada","funders":"","keywords":"Usability; Computer science; Convergence (economics); Data science; Fishing; Human–computer interaction; Fishery","score_opus":0.0722661866375177,"score_gpt":0.3165196092127567,"score_spread":0.24425342257523897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2014301369","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":[0.96326274,0.0008913656,0.028276399,0.00020797306,0.00006584246,0.00040131618,0.00013081929,0.0007887856,0.0059748446],"genre_scores_gemma":[0.9765054,0.0004948459,0.021463683,0.00009809818,0.000056553203,0.00014344172,0.00019218492,0.00015181028,0.000894034],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9782534,0.016242376,0.0014146776,0.0009797757,0.0027296206,0.00038015284],"domain_scores_gemma":[0.86164325,0.1281423,0.0023772616,0.0018681384,0.005189947,0.0007791356],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011018724,0.00096824847,0.0008232783,0.0008476122,0.000583675,0.0037552689,0.001037732,0.001452266,0.002113876],"category_scores_gemma":[0.12197473,0.0002933728,0.00042554413,0.00053848635,0.00084110093,0.0019106434,0.0012201861,0.0006119518,0.0009028647],"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":[0.014931656,0.0009921773,0.08995389,0.007210737,0.0005556515,0.0023912624,0.030434519,0.01569747,0.31781536,0.0013830086,0.0018813113,0.51675296],"study_design_scores_gemma":[0.0007464684,0.023514614,0.3640579,0.0018254733,0.0018648127,0.0046270555,0.037016176,0.15159369,0.38925463,0.0057574417,0.018743662,0.0009980215],"about_ca_topic_score_codex":0.0012292536,"about_ca_topic_score_gemma":0.0016036379,"teacher_disagreement_score":0.011018724,"about_ca_system_score_codex":0.00042334202,"about_ca_system_score_gemma":0.00036053246,"threshold_uncertainty_score":0.058273256},"labels":[],"label_agreement":null},{"id":"W2015313388","doi":"10.1007/s10772-014-9224-x","title":"Dialogue POMDP components (Part II): learning the reward function","year":2014,"lang":"en","type":"article","venue":"International Journal of Speech Technology","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Partially observable Markov decision process; Computer science; Reinforcement learning; Markov decision process; Context (archaeology); Artificial intelligence; Function (biology); Process (computing); Bellman equation; Machine learning; Markov process; Markov chain; Markov model; Mathematical optimization; Mathematics","score_opus":0.012141879733216104,"score_gpt":0.23098924759122247,"score_spread":0.21884736785800638,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015313388","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.017489366,0.00023640103,0.9759453,0.00025951344,0.000118975375,0.00025530398,0.000274823,0.0013660747,0.004054229],"genre_scores_gemma":[0.52951384,0.00030409984,0.45804608,0.0002002034,0.00011497899,0.0006686873,0.00078997185,0.0004900264,0.009872055],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992594,0.00018979707,0.000038640486,0.00024959465,0.00016205863,0.0001005701],"domain_scores_gemma":[0.99883324,0.00060580065,0.000055709606,0.00019468518,0.00022235612,0.00008824966],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014771431,0.0010278726,0.0011280462,0.00031202743,0.00042839404,0.0018250992,0.0016256302,0.0014127197,0.0145713445],"category_scores_gemma":[0.00714266,0.00077650644,0.00069336087,0.00031073255,0.00065955863,0.002063914,0.0017440345,0.0026214386,0.0020306478],"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":[0.0012078967,0.00040293796,0.0031867374,0.00051842997,0.00017351224,0.00020435001,0.0005211631,0.32050046,0.021788673,0.056221653,0.007973084,0.5873011],"study_design_scores_gemma":[0.00007420477,0.00017125117,0.0011617535,0.00004813558,0.000046824294,0.000052465086,0.00004672063,0.9512985,0.012525552,0.030452223,0.0040868386,0.000035607103],"about_ca_topic_score_codex":0.0043152696,"about_ca_topic_score_gemma":0.0036105693,"teacher_disagreement_score":0.0145713445,"about_ca_system_score_codex":0.000931944,"about_ca_system_score_gemma":0.0019310797,"threshold_uncertainty_score":0.04874599},"labels":[],"label_agreement":null},{"id":"W2015373428","doi":"10.1017/s0272263100251061","title":"<b>ASPECTS OF ARGUMENT STRUCTURE ACQUISITION IN INUKTITUT.</b><i>Shanley E. M. Allen</i>. Amsterdam: Benjamins, 1996. Pp. xvii + 248. $79.00cloth.","year":2000,"lang":"en","type":"article","venue":"Studies in Second Language Acquisition","topic":"Speech and dialogue systems","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":"Argument (complex analysis); Variety (cybernetics); Linguistics; Language acquisition; Second-language acquisition; Theoretical linguistics; Cognitive science; Computer science; Psychology; Philosophy; Artificial intelligence","score_opus":0.011854686868541155,"score_gpt":0.26498747600785655,"score_spread":0.2531327891393154,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2015373428","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":[0.007337199,0.43847406,0.0032536522,0.028664032,0.002593041,0.000028116337,0.00015916493,0.000094740644,0.519396],"genre_scores_gemma":[0.22725229,0.28959757,0.0065606968,0.004991294,0.0024336865,0.00016692316,0.00073642295,0.00024753637,0.46801353],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997149,0.00010989586,0.000014341032,0.00004200293,0.00006730804,0.000051479754],"domain_scores_gemma":[0.9996371,0.00023441775,0.00003189792,0.000012492345,0.000046717203,0.000037333157],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049573934,0.00058239384,0.00041339747,0.0014545987,0.0020999738,0.0042271717,0.00085534144,0.0018939142,0.018027306],"category_scores_gemma":[0.00095913716,0.00058540964,0.00026548558,0.0025123786,0.0033742,0.0063374797,0.0010508487,0.0022610237,0.0038458619],"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":[0.00007312524,0.00012127418,0.0019213972,0.0007448233,0.000025706413,0.0005741251,0.018999692,0.00030997905,0.00087146123,0.3621456,0.3970454,0.21716744],"study_design_scores_gemma":[0.000007729565,0.000026351809,0.008704462,0.0008763992,0.000013435155,0.00085823063,0.0051351623,0.00028810347,0.00039145767,0.08908879,0.8945926,0.00001732795],"about_ca_topic_score_codex":0.018079882,"about_ca_topic_score_gemma":0.042333666,"teacher_disagreement_score":0.018079882,"about_ca_system_score_codex":0.004032788,"about_ca_system_score_gemma":0.0017046883,"threshold_uncertainty_score":0.060307324},"labels":[],"label_agreement":null},{"id":"W2018093467","doi":"10.1007/s10772-009-9039-3","title":"Synthetic speech in foreign language learning: an evaluation by learners","year":2008,"lang":"en","type":"article","venue":"International Journal of Speech Technology","topic":"Speech and dialogue systems","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":"University of Toronto","funders":"","keywords":"Computer science; Natural (archaeology); Active listening; Speech synthesis; Comprehension; Speech recognition; Natural language processing; Foreign language; Linguistics; Artificial intelligence; Psychology; Communication","score_opus":0.017741914160635894,"score_gpt":0.28750836916179695,"score_spread":0.26976645500116103,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2018093467","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":[0.99181753,0.00027722798,0.004653205,0.00007090984,0.00006816134,0.00030744897,0.0003853278,0.00020193169,0.0022182649],"genre_scores_gemma":[0.98666775,0.00052855816,0.007134277,0.00009250675,0.00007397689,0.00056002307,0.0013956612,0.00010380816,0.003443404],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99512637,0.0032943212,0.00033392923,0.00036212656,0.0007448766,0.00013839774],"domain_scores_gemma":[0.9811473,0.012000853,0.0004969353,0.001412008,0.0030412877,0.0019016704],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063696727,0.0011351018,0.0011576898,0.00089053303,0.0005885126,0.0013415753,0.00081021787,0.0016097977,0.0029792534],"category_scores_gemma":[0.020712648,0.00025087516,0.0006939989,0.00038569627,0.0007718752,0.0012415125,0.00186906,0.00065329607,0.0012889986],"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":[0.07240538,0.03125343,0.09350332,0.005202436,0.0013746748,0.0032050712,0.05337587,0.030216888,0.10129282,0.0017835404,0.0061506475,0.6002359],"study_design_scores_gemma":[0.009578382,0.21487187,0.3528445,0.0010081704,0.0032032472,0.010677264,0.05605473,0.10799064,0.19755653,0.0048386273,0.040500507,0.0008755053],"about_ca_topic_score_codex":0.00113357,"about_ca_topic_score_gemma":0.00082517765,"teacher_disagreement_score":0.0063696727,"about_ca_system_score_codex":0.0004502956,"about_ca_system_score_gemma":0.0006820581,"threshold_uncertainty_score":0.0336864},"labels":[],"label_agreement":null},{"id":"W2022473919","doi":"10.1121/1.4779541","title":"Auditory and visual clear speech effects measured during a simulated conversational intercation","year":2002,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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 Montréal","funders":"","keywords":"Intelligibility (philosophy); Speech recognition; Perception; Modalities; Psychology; Articulation (sociology); Speech perception; Audiology; Computer science","score_opus":0.010329072395252594,"score_gpt":0.22545842305716104,"score_spread":0.21512935066190844,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2022473919","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":[0.99855286,0.000057449008,0.00082108594,0.0000051032675,0.0000039111915,0.000024878042,0.00005010304,0.00002012907,0.00046439556],"genre_scores_gemma":[0.99780434,0.000061980296,0.0013271455,0.000013681896,0.000008374094,0.00005976337,0.0001305026,0.000017478445,0.0005767439],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99926883,0.00028874565,0.000052529304,0.00012280751,0.0001882209,0.00007893128],"domain_scores_gemma":[0.996148,0.0028005014,0.00030043215,0.00016754147,0.00031626006,0.0002672973],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00070166134,0.00052074605,0.0003942002,0.00038208588,0.00027334195,0.0005505765,0.0002616362,0.0005825004,0.0018774243],"category_scores_gemma":[0.0061719418,0.00031799774,0.00023778487,0.00014871874,0.000501336,0.00031978538,0.0007533855,0.0003707805,0.00032316154],"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":[0.007063285,0.0002486211,0.0066945725,0.00031368976,0.000111195855,0.00068344764,0.005918208,0.00084616547,0.9650331,0.00011788858,0.00011247463,0.012857348],"study_design_scores_gemma":[0.00047926634,0.02506877,0.5823215,0.00013538216,0.0005784075,0.0033953036,0.0068299365,0.006244922,0.37154126,0.00053153967,0.0026714995,0.0002022013],"about_ca_topic_score_codex":0.0004429813,"about_ca_topic_score_gemma":0.0008042284,"teacher_disagreement_score":0.0018774243,"about_ca_system_score_codex":0.00013328064,"about_ca_system_score_gemma":0.00013996908,"threshold_uncertainty_score":0.006280601},"labels":[],"label_agreement":null},{"id":"W2028811096","doi":"10.1016/j.eswa.2012.01.019","title":"Erratum to “DiSeg 1.0: The first system for Spanish discourse segmentation” [Expert Systems with Applications 39 (2) (2011) 1671–1678]","year":2012,"lang":"en","type":"erratum","venue":"Expert Systems with Applications","topic":"Speech and dialogue systems","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":"Polytechnique Montréal","funders":"","keywords":"Computer science; Segmentation; Artificial intelligence; Natural language processing; Information retrieval","score_opus":0.0163932684451305,"score_gpt":0.2655787540280244,"score_spread":0.24918548558289388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2028811096","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":[0.00087485043,0.0017221029,0.00283133,0.12781428,0.8321926,0.0001037988,0.00516053,0.002020485,0.027280023],"genre_scores_gemma":[0.018664626,0.005600417,0.006918733,0.13837804,0.10990378,0.00046233812,0.013881095,0.0050047464,0.7011862],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99620795,0.0007027788,0.0006126134,0.00049817516,0.0016339378,0.00034439182],"domain_scores_gemma":[0.9835855,0.0033757777,0.0006895416,0.00070002297,0.011129517,0.00051969715],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030573704,0.0021135823,0.0018885991,0.0035475416,0.0055507803,0.0035410796,0.0027458745,0.006669096,0.07456285],"category_scores_gemma":[0.032516327,0.00092710095,0.0010436365,0.0027004674,0.0018463396,0.0022634303,0.00252477,0.007493624,0.052213356],"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":[0.000038488797,0.000005740978,0.00003643132,0.0000476759,0.0000032151925,0.00010665365,0.00004152893,0.000024633959,0.00005102065,0.0005119841,0.99592066,0.0032119332],"study_design_scores_gemma":[0.000034978155,0.000028774053,0.0006560502,0.00022892366,0.000018199667,0.00016497781,0.00019160699,0.00027931316,0.0004961667,0.00088773796,0.99697113,0.000042191343],"about_ca_topic_score_codex":0.059504498,"about_ca_topic_score_gemma":0.055613715,"teacher_disagreement_score":0.07456285,"about_ca_system_score_codex":0.005249899,"about_ca_system_score_gemma":0.0061813467,"threshold_uncertainty_score":0.24943757},"labels":[],"label_agreement":null},{"id":"W2030867710","doi":"10.1111/j.1756-8765.2012.01184.x","title":"Underspecification of Cognitive Status in Reference Production: Some Empirical Predictions","year":2012,"lang":"en","type":"article","venue":"Topics in Cognitive Science","topic":"Speech and dialogue systems","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":"Simon Fraser University","funders":"","keywords":"Underspecification; Referent; Salience (neuroscience); Hierarchy; Cognition; Cognitive psychology; Psychology; Psycholinguistics; Linguistics; Computer science; Cognitive science; Natural language processing; Philosophy","score_opus":0.14928682155752626,"score_gpt":0.3738790549075488,"score_spread":0.22459223335002254,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2030867710","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":[0.9800555,0.0004917514,0.007535648,0.00051895774,0.000015109425,0.0000706003,0.00015917944,0.000052027517,0.011101193],"genre_scores_gemma":[0.9980398,0.00011068076,0.001167716,0.00011192852,0.000026840948,0.00004055569,0.00013781105,0.000046140587,0.00031851855],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9935644,0.0023023982,0.0007344425,0.001759179,0.0011686038,0.00047097987],"domain_scores_gemma":[0.8165192,0.14836147,0.012167787,0.017199978,0.0041752667,0.0015763054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.015791526,0.00055172667,0.0010298486,0.0015272959,0.00067577587,0.0021912928,0.0016336015,0.0016975251,0.008376444],"category_scores_gemma":[0.08946295,0.0011234147,0.0005485297,0.0009496925,0.006701679,0.0083915405,0.0039504375,0.0017638281,0.00068904366],"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":[0.009059082,0.002816301,0.47464037,0.0030312384,0.00047112632,0.0017142415,0.0485637,0.0122938035,0.14040093,0.1350771,0.0020860885,0.16984597],"study_design_scores_gemma":[0.00024613526,0.00068492355,0.8848905,0.00012892377,0.000271893,0.0009388162,0.0047879186,0.014947579,0.0117947515,0.07930224,0.0018388858,0.00016747486],"about_ca_topic_score_codex":0.0026114266,"about_ca_topic_score_gemma":0.0011565665,"teacher_disagreement_score":0.015791526,"about_ca_system_score_codex":0.00066271255,"about_ca_system_score_gemma":0.0004028689,"threshold_uncertainty_score":0.08351451},"labels":[],"label_agreement":null},{"id":"W2031396317","doi":"10.1145/1096000.1096003","title":"Call for a public-domain SpeechWeb","year":2005,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Public domain; Computer science; Domain (mathematical analysis); Telecommunications; Computer security; Internet privacy; Public relations; World Wide Web; Political science; Mathematics","score_opus":0.0759108349846406,"score_gpt":0.3009099224441927,"score_spread":0.22499908745955208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031396317","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011190187,0.0011039816,0.07543801,0.48852202,0.023028975,0.0011428292,0.008001916,0.09920607,0.29236612],"genre_scores_gemma":[0.05017105,0.0007012633,0.05663017,0.16343153,0.0059010275,0.0008219204,0.014879499,0.00790573,0.69955784],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99690056,0.00057105423,0.00019331297,0.00035048384,0.0014992881,0.0004852427],"domain_scores_gemma":[0.972024,0.0074776444,0.00087859476,0.005394702,0.0056242906,0.008600812],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007872144,0.00067454466,0.00060209207,0.0013612871,0.0019489495,0.0053736563,0.0028666623,0.014275834,0.27233526],"category_scores_gemma":[0.018944304,0.00073667633,0.0011745823,0.00088215823,0.001234029,0.009675652,0.005053051,0.007056755,0.17557977],"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":[0.00016515687,0.00017009446,0.00036101972,0.000093922084,0.000010907228,0.00023695045,0.0001072043,0.00009600069,0.0027859306,0.01204603,0.959964,0.023962708],"study_design_scores_gemma":[0.000067404115,0.0000446305,0.0007114336,0.000040283358,0.000010448145,0.00020041066,0.0002304349,0.0005857629,0.0012043692,0.003212328,0.9936579,0.00003463471],"about_ca_topic_score_codex":0.004561506,"about_ca_topic_score_gemma":0.005739216,"teacher_disagreement_score":0.27233526,"about_ca_system_score_codex":0.0014014229,"about_ca_system_score_gemma":0.003314459,"threshold_uncertainty_score":0.9110522},"labels":[],"label_agreement":null},{"id":"W2031582216","doi":"10.1007/s10115-006-0062-2","title":"Toward understanding the importance of gesture in distributed scientific collaboration","year":2007,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Speech and dialogue systems","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 Victoria","funders":"University of Victoria","keywords":"Artifact (error); Computer science; Gesture; Coding (social sciences); Set (abstract data type); Data science; Human–computer interaction; Software; Artificial intelligence; Sociology","score_opus":0.03044051358999905,"score_gpt":0.25883442101330445,"score_spread":0.2283939074233054,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2031582216","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23255555,0.003019229,0.685172,0.0066277604,0.00026272013,0.00016355314,0.00020507429,0.00048467694,0.07150945],"genre_scores_gemma":[0.92287296,0.0011453098,0.07325347,0.00022495691,0.00008817753,0.00009402881,0.000078422905,0.00008304465,0.002159575],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99874604,0.0006293973,0.000065685,0.0002396927,0.00017578085,0.00014336065],"domain_scores_gemma":[0.99266934,0.00529576,0.00056051905,0.00071864773,0.0005261295,0.00022957972],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002272963,0.0005658026,0.000493765,0.0014693093,0.0013361782,0.0072178645,0.0011566872,0.002828991,0.0044315387],"category_scores_gemma":[0.016766487,0.00088404136,0.0006011801,0.00096273574,0.0059775272,0.015038581,0.0035128535,0.0027153767,0.0006243352],"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":[0.0006055194,0.00015894017,0.015782453,0.0008797938,0.00008923442,0.00069087686,0.03536339,0.027427962,0.039318155,0.6991892,0.0020193008,0.17847523],"study_design_scores_gemma":[0.000073853145,0.00010192347,0.009462976,0.0002322192,0.00008842133,0.0003746116,0.013192292,0.1487848,0.008286304,0.80614734,0.013151901,0.00010324948],"about_ca_topic_score_codex":0.004519685,"about_ca_topic_score_gemma":0.0029493526,"teacher_disagreement_score":0.99866384,"about_ca_system_score_codex":0.0010913828,"about_ca_system_score_gemma":0.0014228745,"threshold_uncertainty_score":0.014824986},"labels":[],"label_agreement":null},{"id":"W2035595087","doi":"10.1109/vecims.2012.6273227","title":"A task ontology model for domain independent dialogue management","year":2012,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Computer science; Ontology; Task (project management); Domain (mathematical analysis); Domain model; Human–computer interaction; Situated; Knowledge management; Reuse; Ticket; Software engineering; Artificial intelligence; Domain knowledge; Systems engineering","score_opus":0.025410187465376995,"score_gpt":0.2538948497064011,"score_spread":0.2284846622410241,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2035595087","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005216579,0.00015903325,0.9853351,0.0005569511,0.00008909997,0.00024089984,0.00038407347,0.00060087594,0.007417387],"genre_scores_gemma":[0.14122403,0.0005313171,0.84726584,0.00038604668,0.00008479714,0.0008868178,0.002021902,0.00025137168,0.0073479335],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973224,0.00082796393,0.00040944663,0.00040694274,0.0007904428,0.00024273939],"domain_scores_gemma":[0.99806875,0.0006121134,0.0001970904,0.0004344099,0.00049636344,0.00019127011],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027949468,0.00065174414,0.0005536257,0.0012650068,0.0013679335,0.0027242727,0.0015406566,0.0015227557,0.002197667],"category_scores_gemma":[0.004151849,0.00053269294,0.0020267777,0.0010066604,0.0012072077,0.0053965244,0.0023067982,0.0023932878,0.0011684262],"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":[0.0001902993,0.00034326722,0.0024631133,0.0006141809,0.00013966161,0.000628033,0.0064672586,0.045761578,0.014114521,0.7456154,0.015221878,0.16844074],"study_design_scores_gemma":[0.00010572735,0.0001673404,0.0017939808,0.0003185433,0.00024051833,0.000957448,0.0016282242,0.42624122,0.0086617125,0.2653915,0.2943355,0.00015833713],"about_ca_topic_score_codex":0.009891168,"about_ca_topic_score_gemma":0.00968661,"teacher_disagreement_score":0.009891168,"about_ca_system_score_codex":0.0016835645,"about_ca_system_score_gemma":0.004605467,"threshold_uncertainty_score":0.019667208},"labels":[],"label_agreement":null},{"id":"W2041963928","doi":"10.1145/765891.766087","title":"Establishing remote conversations through eye contact with physical awareness proxies","year":2003,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Queen's University","funders":"","keywords":"Computer science; Eye contact; Human–computer interaction; Remote sensing; Psychology; Geology; Communication","score_opus":0.02167573367589991,"score_gpt":0.26398375304420557,"score_spread":0.24230801936830565,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2041963928","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21157503,0.000882657,0.7423336,0.00057284633,0.00019959398,0.0005894866,0.000092643655,0.0053498955,0.038404245],"genre_scores_gemma":[0.8505468,0.00023528392,0.13796715,0.00019852897,0.00012963587,0.00045463635,0.00007889883,0.0002246395,0.010164369],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9970221,0.0013667741,0.00017123508,0.00048556848,0.0006220711,0.00033217523],"domain_scores_gemma":[0.9936586,0.0028814455,0.0007670328,0.0016214502,0.00055404165,0.00051755976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018243296,0.00079158694,0.0005862726,0.00048882625,0.001260813,0.0025094491,0.0012770747,0.0015762316,0.006626941],"category_scores_gemma":[0.008963444,0.0004796862,0.000564732,0.00018412662,0.0010859024,0.003334152,0.00552663,0.0012885684,0.002253529],"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":[0.0016843231,0.0008625008,0.008299349,0.00082961953,0.00015579083,0.0037554223,0.02463592,0.0064782393,0.4996676,0.07495717,0.0056367638,0.37303728],"study_design_scores_gemma":[0.0005459493,0.0032563151,0.01040694,0.00051538186,0.000458978,0.0053131017,0.0067920364,0.09102018,0.6134883,0.045704596,0.2219796,0.0005185821],"about_ca_topic_score_codex":0.00044450536,"about_ca_topic_score_gemma":0.00039359022,"teacher_disagreement_score":0.006626941,"about_ca_system_score_codex":0.00024955688,"about_ca_system_score_gemma":0.0005649151,"threshold_uncertainty_score":0.022169292},"labels":[],"label_agreement":null},{"id":"W2042685959","doi":"10.7202/039602ar","title":"Le dialogue homme-machine : un système de traduction automatique spécifique","year":2010,"lang":"fr","type":"article","venue":"Meta Journal des traducteurs","topic":"Speech and dialogue systems","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":"Humanities; Philosophy","score_opus":0.028183371840205525,"score_gpt":0.24876662939275568,"score_spread":0.22058325755255015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2042685959","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":[0.026971864,0.0010565099,0.9216443,0.00074651855,0.0005136953,0.0002618096,0.0006554664,0.025624096,0.022525767],"genre_scores_gemma":[0.34261203,0.00078284566,0.6086184,0.0008188944,0.00030740417,0.00055969524,0.0014198375,0.0040666284,0.040814143],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974377,0.0009836613,0.0001854076,0.00078661426,0.0004658171,0.00014069666],"domain_scores_gemma":[0.99606776,0.001980169,0.00018555827,0.0009680581,0.0005960946,0.00020231739],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032031804,0.0010110312,0.0013325848,0.0011776631,0.0014800944,0.004181833,0.0012266319,0.0022124304,0.016941568],"category_scores_gemma":[0.008861708,0.0006441511,0.0008737019,0.00081278436,0.0018585294,0.0052432693,0.0027840012,0.0015896639,0.006118584],"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":[0.0020437452,0.00021778418,0.0075043347,0.00217624,0.00024123093,0.0017480829,0.014168009,0.007760685,0.17506151,0.12508309,0.036604438,0.62739086],"study_design_scores_gemma":[0.00015780621,0.0006400523,0.0067608734,0.00043890817,0.0002693413,0.0042312443,0.002085126,0.10058037,0.15522096,0.048871282,0.68033236,0.00041169603],"about_ca_topic_score_codex":0.0024772377,"about_ca_topic_score_gemma":0.0020398682,"teacher_disagreement_score":0.016941568,"about_ca_system_score_codex":0.00070195633,"about_ca_system_score_gemma":0.001096426,"threshold_uncertainty_score":0.056675196},"labels":[],"label_agreement":null},{"id":"W2047264345","doi":"10.1121/1.4805595","title":"Coordinating conversation through posture","year":2013,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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 British Columbia Hospital","funders":"","keywords":"Conversation; Movement (music); Motion (physics); Categorization; Perception; Computer science; Dynamics (music); Communication; Speech recognition; Psychology; Cognitive psychology; Artificial intelligence; Acoustics","score_opus":0.011007921039585407,"score_gpt":0.23128763662941174,"score_spread":0.22027971558982634,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2047264345","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":[0.79290736,0.0016884691,0.12600805,0.00058619096,0.00016124264,0.0002125401,0.0005690684,0.0011362254,0.07673085],"genre_scores_gemma":[0.9846267,0.00025903282,0.0124858655,0.000045519308,0.000035731002,0.000049838807,0.00013664788,0.000066615285,0.002293965],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.998801,0.00047464893,0.000057019803,0.00026360634,0.00024767042,0.00015606277],"domain_scores_gemma":[0.9990989,0.00028494291,0.00020137956,0.000110351626,0.00021012558,0.00009434302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057981175,0.00039845327,0.00034030929,0.0010770459,0.00086044753,0.0028963583,0.00035791117,0.00051694346,0.003046208],"category_scores_gemma":[0.00401612,0.00020599522,0.00026074247,0.0007142472,0.0009036186,0.0013277485,0.0013678304,0.00032415453,0.001048258],"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":[0.0005753237,0.00009015382,0.06905453,0.0007203524,0.00018394008,0.0010211719,0.048328828,0.005677148,0.29722762,0.023091657,0.00487738,0.5491519],"study_design_scores_gemma":[0.000047960468,0.00065093214,0.7168376,0.00046430228,0.0003552868,0.0034872189,0.04873423,0.03942532,0.044243027,0.04785956,0.09754341,0.00035120454],"about_ca_topic_score_codex":0.0019269749,"about_ca_topic_score_gemma":0.00164661,"teacher_disagreement_score":0.003046208,"about_ca_system_score_codex":0.0004309829,"about_ca_system_score_gemma":0.0005485203,"threshold_uncertainty_score":0.010190606},"labels":[],"label_agreement":null},{"id":"W2048977551","doi":"10.1117/12.739788","title":"&lt;title&gt;Design of interaction manager supporting collaborative display and multimodal interaction for advanced collaborative environment&lt;/title&gt;","year":2007,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Speech and dialogue systems","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":"Hongik University; University of Toronto; Institute of Museum and Library Services","keywords":"Computer science; Human–computer interaction; Collaborative design; Collaborative software; Ubiquitous computing; Interaction design; User interface; Multimodal interaction; World Wide Web; Software engineering; Systems design; Operating system","score_opus":0.008959038836749924,"score_gpt":0.24462825411395625,"score_spread":0.23566921527720633,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048977551","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":[0.021147033,0.00087139365,0.95999193,0.00057048176,0.0005932638,0.0005203964,0.00017873502,0.0060824677,0.010044287],"genre_scores_gemma":[0.2696297,0.0007867874,0.69049084,0.00062060537,0.00027738637,0.0008771232,0.0008087225,0.0006100185,0.03589886],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999451,0.00013419856,0.00006890494,0.00013792841,0.00013520736,0.000072793395],"domain_scores_gemma":[0.9995048,0.0000799048,0.00005044321,0.00007733848,0.00019911332,0.00008848485],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000598125,0.00046085624,0.00043929883,0.00030067025,0.0005528498,0.0010349769,0.0015031699,0.0009795056,0.0072894883],"category_scores_gemma":[0.000769072,0.00034207196,0.00040720223,0.00021350083,0.0003817309,0.0010010297,0.0006815939,0.00044180153,0.002872614],"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":[0.0009182689,0.00027392677,0.0037998576,0.00097635144,0.00014071741,0.0012224405,0.0011178716,0.0073073087,0.55817074,0.033198528,0.05411067,0.3387634],"study_design_scores_gemma":[0.0002705293,0.002122511,0.0052221683,0.00006987922,0.00024165788,0.0023381533,0.00043381282,0.23042783,0.37495053,0.003954489,0.37977833,0.00019015146],"about_ca_topic_score_codex":0.0011697715,"about_ca_topic_score_gemma":0.0013924555,"teacher_disagreement_score":0.0072894883,"about_ca_system_score_codex":0.0005384869,"about_ca_system_score_gemma":0.0005254836,"threshold_uncertainty_score":0.02438581},"labels":[],"label_agreement":null},{"id":"W2050958592","doi":"10.1145/1125451.1125689","title":"Put a grammar here","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Unification; Computer science; Parsing; Grammar; Phenomenon; Natural language processing; Artificial intelligence; Generative grammar; Linguistics; Programming language; Philosophy; Epistemology","score_opus":0.006837003613713832,"score_gpt":0.19143375573816848,"score_spread":0.18459675212445464,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050958592","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":[0.007841217,0.0015039718,0.6111956,0.039310444,0.0047671595,0.00020390813,0.0019891288,0.0034607023,0.3297278],"genre_scores_gemma":[0.38429564,0.0033831364,0.39594412,0.020982556,0.003109259,0.00059148663,0.0036486513,0.0050341953,0.18301089],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99821055,0.0007632156,0.00009190438,0.00046031715,0.00032498123,0.00014914453],"domain_scores_gemma":[0.9982181,0.0006236596,0.00009116431,0.0005818499,0.00037193706,0.000113221904],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0019268731,0.0009180956,0.0008644476,0.0016500156,0.002545737,0.0048471456,0.0016623717,0.0028195744,0.033211462],"category_scores_gemma":[0.005973814,0.0005226033,0.00089712517,0.0014293663,0.007871887,0.012678975,0.0044278987,0.004783546,0.012953755],"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":[0.00000872026,0.000004254141,0.00018793285,0.000026188029,0.000007795977,0.00007672919,0.0010498434,0.0002353385,0.00021042221,0.9753019,0.01112839,0.011762338],"study_design_scores_gemma":[0.000007735015,0.000012305863,0.00014334441,0.000055370547,0.000012152975,0.00016793536,0.00089725346,0.0011570324,0.00041415016,0.707428,0.28968507,0.000019674766],"about_ca_topic_score_codex":0.0040131724,"about_ca_topic_score_gemma":0.0037229536,"teacher_disagreement_score":0.96678853,"about_ca_system_score_codex":0.0015831181,"about_ca_system_score_gemma":0.0024603922,"threshold_uncertainty_score":0.111103415},"labels":[],"label_agreement":null},{"id":"W2051020089","doi":"10.1080/09588220500173377","title":"Search by Fuzzy Inference in a Children's Dictionary","year":2005,"lang":"en","type":"article","venue":"Computer Assisted Language Learning","topic":"Speech and dialogue systems","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":"National Research Council Canada; University of Ottawa","funders":"","keywords":"Computer science; Vocabulary; Natural language processing; Artificial intelligence; Lexical database; Inference; Information retrieval; Process (computing); Context (archaeology); Reading (process); Reading comprehension; Linguistics","score_opus":0.008278503140220246,"score_gpt":0.2493878804876587,"score_spread":0.24110937734743845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2051020089","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4602279,0.00025959237,0.51628256,0.0006276964,0.00002466987,0.00008487044,0.00016516674,0.0008601368,0.021467395],"genre_scores_gemma":[0.7502614,0.00015688798,0.24274233,0.00006383929,0.000007155381,0.00005017379,0.00015868102,0.000048568545,0.0065109213],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996668,0.000083032704,0.000024530636,0.00009277661,0.000102809776,0.000030031124],"domain_scores_gemma":[0.9991003,0.0006236924,0.000073370626,0.00007355115,0.00009309804,0.00003598009],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006587112,0.0001983657,0.000368211,0.0006715565,0.0004975404,0.0009708252,0.0005927125,0.000766532,0.0049474435],"category_scores_gemma":[0.0032717616,0.0002686731,0.0005374702,0.00042239332,0.0008123484,0.0022220057,0.0006499057,0.0006064747,0.0004625954],"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":[0.0007511839,0.00030029152,0.024739925,0.0006781096,0.00014781336,0.0021993958,0.009348446,0.14066292,0.07139394,0.36251476,0.006121254,0.381142],"study_design_scores_gemma":[0.0001471742,0.0002661488,0.008478144,0.00010024566,0.000098467455,0.0011090147,0.0018894001,0.78968424,0.032946587,0.1468844,0.018299785,0.00009644908],"about_ca_topic_score_codex":0.008164458,"about_ca_topic_score_gemma":0.007399196,"teacher_disagreement_score":0.008164458,"about_ca_system_score_codex":0.00073995825,"about_ca_system_score_gemma":0.00073410367,"threshold_uncertainty_score":0.016550899},"labels":[],"label_agreement":null},{"id":"W2053772744","doi":"10.1145/1132736.1132765","title":"Qui parle?","year":2006,"lang":"fr","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Recall; Task (project management); Avatar; Speech recognition; Speaker recognition; Speaker diarisation; Representation (politics); Natural language processing; Artificial intelligence; Human–computer interaction; Psychology; Cognitive psychology","score_opus":0.019121314732131734,"score_gpt":0.22444547869491804,"score_spread":0.2053241639627863,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2053772744","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":[0.019526022,0.0024467772,0.008144596,0.024258224,0.009865935,0.00020704308,0.0016090621,0.002393121,0.9315492],"genre_scores_gemma":[0.104411386,0.0011987868,0.00463673,0.014306714,0.0010562028,0.000171382,0.0007618848,0.0008519829,0.87260497],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.999297,0.00025627148,0.000020290952,0.00014497356,0.00014421582,0.00013716819],"domain_scores_gemma":[0.99915826,0.00018417736,0.00006114036,0.000100216406,0.00023968212,0.00025661787],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010269191,0.00068038446,0.0003915801,0.0006816354,0.0036071301,0.0034542193,0.00077701453,0.0015026575,0.28389728],"category_scores_gemma":[0.0040843575,0.0002545359,0.00037401877,0.00039538348,0.001113585,0.0040450566,0.0026105335,0.0020745164,0.13646111],"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":[0.00023232795,0.00017108454,0.0024388393,0.0002232057,0.000015414622,0.0010694936,0.010194232,0.00005782791,0.001017417,0.047284722,0.7542931,0.1830023],"study_design_scores_gemma":[0.000008440277,0.000043695993,0.0008709778,0.00005518873,0.0000044265507,0.00057816977,0.003375557,0.000061552804,0.00022451676,0.0034113724,0.9913522,0.000013971047],"about_ca_topic_score_codex":0.0028120605,"about_ca_topic_score_gemma":0.0067386064,"teacher_disagreement_score":0.28389728,"about_ca_system_score_codex":0.0007800761,"about_ca_system_score_gemma":0.00054199144,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2054795804","doi":"10.1109/icmla.2012.31","title":"An Inverse Reinforcement Learning Algorithm for Partially Observable Domains with Application on Healthcare Dialogue Management","year":2012,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Université Laval","funders":"McGill University","keywords":"Partially observable Markov decision process; Markov decision process; Computer science; Reinforcement learning; Margin (machine learning); Artificial intelligence; Observable; Machine learning; Inverse; Markov process; Markov chain; Mathematical optimization; Markov model; Mathematics","score_opus":0.024514113832056067,"score_gpt":0.2634534985663381,"score_spread":0.23893938473428203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2054795804","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0057387305,0.000087615714,0.99287593,0.00012859775,0.00001764938,0.000041707073,0.000014670666,0.00039462486,0.00070049893],"genre_scores_gemma":[0.39523616,0.00012802106,0.6020771,0.00016538645,0.000032242937,0.00028677614,0.0001054401,0.00012273634,0.0018460816],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991629,0.00034251442,0.00004273209,0.0001949479,0.00018001212,0.000076891716],"domain_scores_gemma":[0.99800426,0.0014229141,0.00015340243,0.00009370428,0.00023773916,0.00008811858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019604063,0.0007874116,0.0011901611,0.0005563481,0.00055396487,0.0008212747,0.001293124,0.0012124914,0.0025646836],"category_scores_gemma":[0.0058086202,0.00043077,0.0005630345,0.00037476327,0.0010289595,0.0012538126,0.0013732322,0.0017219499,0.0004076384],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00011033098,0.000093795585,0.0007644765,0.00007848089,0.000035584224,0.00008006344,0.00015821871,0.86006045,0.0010578918,0.018810237,0.0009801555,0.11777027],"study_design_scores_gemma":[0.000013552947,0.000016214613,0.000029324803,0.0000043121545,0.0000024146839,0.000009984085,0.000005004558,0.99592066,0.0002217475,0.0034852407,0.00028786573,0.0000035891535],"about_ca_topic_score_codex":0.0047843703,"about_ca_topic_score_gemma":0.0028953806,"teacher_disagreement_score":0.0047843703,"about_ca_system_score_codex":0.0011358871,"about_ca_system_score_gemma":0.00183638,"threshold_uncertainty_score":0.010367751},"labels":[],"label_agreement":null},{"id":"W2055456146","doi":"10.5539/ibr.v1n4p40","title":"Data Enriched Voice Service Analysis and Forecast","year":2009,"lang":"en","type":"article","venue":"International Business Research","topic":"Speech and dialogue systems","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":"Interoperability; Service (business); Personalization; Computer science; Call centre; Work (physics); Business; Telecommunications; World Wide Web; Marketing; Engineering","score_opus":0.1398868676905564,"score_gpt":0.3984806820133297,"score_spread":0.2585938143227733,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2055456146","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":[0.5508625,0.00063285895,0.41662237,0.0015698889,0.00026586457,0.00024638852,0.0064185956,0.0033191943,0.020062389],"genre_scores_gemma":[0.95268536,0.00031637496,0.039211325,0.00007765259,0.00010250045,0.00007756407,0.003717273,0.00011430554,0.0036975709],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990251,0.00013873525,0.000052798565,0.00015627609,0.0005271703,0.0000998861],"domain_scores_gemma":[0.997171,0.0010646632,0.000224209,0.0001968076,0.001231819,0.00011156051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012634727,0.00068006554,0.0004244909,0.0022922198,0.00036579638,0.0018015185,0.00056805613,0.0008152463,0.0026453263],"category_scores_gemma":[0.005274625,0.00022736593,0.00040158283,0.0016698352,0.00026228384,0.002279233,0.0004755482,0.0008116211,0.0012964883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012860182,0.00025628423,0.11308236,0.00019377533,0.00013123316,0.000736416,0.0005269065,0.5500023,0.024027033,0.034070507,0.010647749,0.26503944],"study_design_scores_gemma":[0.000013804362,0.000041039522,0.008934788,0.000009981462,0.000023270648,0.000054465683,0.00016370018,0.97601014,0.004963451,0.0051186765,0.004633514,0.000033209915],"about_ca_topic_score_codex":0.01743719,"about_ca_topic_score_gemma":0.00814237,"teacher_disagreement_score":0.01743719,"about_ca_system_score_codex":0.0019238759,"about_ca_system_score_gemma":0.0010196223,"threshold_uncertainty_score":0.034671366},"labels":[],"label_agreement":null},{"id":"W2057484293","doi":"10.1006/brln.2000.2385","title":"Knowledge-Based Inferencing after Childhood Head Injury","year":2001,"lang":"en","type":"article","venue":"Brain and Language","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":47,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"National Institute of Neurological Disorders and Stroke","keywords":"Psychology; Comprehension; Cognition; Knowledge base; Cognitive psychology; Task (project management); Head injury; Developmental psychology; Working memory; Metacognition; Psychiatry; Linguistics; Artificial intelligence; Computer science","score_opus":0.009245023184830172,"score_gpt":0.25766944915013307,"score_spread":0.2484244259653029,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057484293","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":[0.9455801,0.00025956312,0.043418057,0.00085783243,0.000052120824,0.00010580725,0.00027479828,0.00076846115,0.00868328],"genre_scores_gemma":[0.99382013,0.00006881416,0.0053467476,0.00003939556,0.000008919575,0.000024728133,0.00011483009,0.000016779175,0.00055971264],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99790347,0.0011713131,0.0001516851,0.00016849056,0.00037213377,0.00023299931],"domain_scores_gemma":[0.98531437,0.01219976,0.0006201307,0.0009234863,0.0006951383,0.00024706576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022493363,0.0004139395,0.00030714367,0.00060571276,0.0008648274,0.0014307589,0.00083720876,0.001238664,0.0020217204],"category_scores_gemma":[0.030224482,0.00029414947,0.00026244868,0.00030345502,0.0008606357,0.0016367377,0.0015317234,0.001448416,0.00031184455],"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":[0.005683366,0.0018642346,0.09605955,0.0005603883,0.00030154697,0.0155926645,0.04525334,0.096016474,0.03349367,0.034202956,0.0073222197,0.6636496],"study_design_scores_gemma":[0.00028983306,0.0018162596,0.1246459,0.000413756,0.0005607869,0.008854169,0.027462624,0.5434876,0.08762066,0.19490607,0.009604334,0.0003379626],"about_ca_topic_score_codex":0.009428283,"about_ca_topic_score_gemma":0.009581624,"teacher_disagreement_score":0.009428283,"about_ca_system_score_codex":0.0008112596,"about_ca_system_score_gemma":0.001572189,"threshold_uncertainty_score":0.018746853},"labels":[],"label_agreement":null},{"id":"W2059616890","doi":"10.1109/icce.2010.5418754","title":"Mobile multimedia broadcasting applications: Speech enabled data services","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Multimedia; Broadcasting (networking); Profiling (computer programming); Synchronization (alternating current); Computer network; Human–computer interaction; World Wide Web","score_opus":0.020126829010509977,"score_gpt":0.2710644486359172,"score_spread":0.2509376196254072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059616890","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":[0.032378137,0.007035032,0.8659479,0.0019525157,0.00063148065,0.0004508003,0.0005109918,0.0143824015,0.07671077],"genre_scores_gemma":[0.45751938,0.009894818,0.43433544,0.0018962799,0.0016098913,0.00056884484,0.0020240608,0.0015934042,0.09055783],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995328,0.00007634984,0.00002755678,0.000051830346,0.00023310704,0.00007842886],"domain_scores_gemma":[0.99972206,0.00005110201,0.0000195034,0.000032363925,0.00011643986,0.00005843473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042166433,0.0005042386,0.000353221,0.0006186724,0.0005545756,0.001798833,0.0008722441,0.0010621758,0.0040478967],"category_scores_gemma":[0.00077227945,0.00024242878,0.0003167212,0.0005561405,0.00045699542,0.0010676567,0.0011186923,0.0009569419,0.0036802012],"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":[0.00038014376,0.00017615846,0.0013821992,0.0009235072,0.000047735262,0.0018496955,0.0015687617,0.002772952,0.17915827,0.18751393,0.040853657,0.58337295],"study_design_scores_gemma":[0.00006809678,0.00027899104,0.0020235174,0.0002508008,0.000093354625,0.0028558644,0.00044872824,0.050693065,0.09130543,0.022249147,0.8296438,0.00008923615],"about_ca_topic_score_codex":0.0019633605,"about_ca_topic_score_gemma":0.0015965338,"teacher_disagreement_score":0.0040478967,"about_ca_system_score_codex":0.00054280856,"about_ca_system_score_gemma":0.00071982964,"threshold_uncertainty_score":0.013541579},"labels":[],"label_agreement":null},{"id":"W2063358261","doi":"10.1145/792704.792730","title":"Game-like navigation and responsiveness in non-game applications","year":2003,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Speech and dialogue systems","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 Toronto","funders":"","keywords":"Computer science; Human–computer interaction; Game design; Video game development","score_opus":0.02558136271059952,"score_gpt":0.283212504251202,"score_spread":0.25763114154060246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2063358261","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":[0.58773124,0.0010438669,0.35341516,0.0005399966,0.00012705856,0.00033216708,0.000179737,0.008218279,0.04841248],"genre_scores_gemma":[0.96788263,0.00014924083,0.02429013,0.000120981036,0.000021458067,0.00011973829,0.000122034144,0.0002881003,0.007005653],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99907374,0.00051254005,0.000029384166,0.00009585866,0.00017207002,0.00011629513],"domain_scores_gemma":[0.9978708,0.0014450217,0.000074411255,0.0002270148,0.00022172322,0.00016099309],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007505843,0.0005159245,0.00030710938,0.00029411638,0.0004200271,0.0017802141,0.0008729067,0.0010220166,0.0054962994],"category_scores_gemma":[0.0050540557,0.00035059566,0.00025698903,0.0002173023,0.0005703339,0.0019906254,0.0010180537,0.00065091765,0.0014213306],"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":[0.005156394,0.002098897,0.013560142,0.0012807939,0.00013316276,0.0022644135,0.0073632095,0.0314376,0.39909554,0.09784398,0.014924186,0.4248417],"study_design_scores_gemma":[0.0005379942,0.004014723,0.03817639,0.00025978262,0.00022265145,0.0045699645,0.0039738216,0.6093214,0.15045588,0.09397932,0.09415785,0.0003302632],"about_ca_topic_score_codex":0.0010787977,"about_ca_topic_score_gemma":0.0013145293,"teacher_disagreement_score":0.0054962994,"about_ca_system_score_codex":0.00021714819,"about_ca_system_score_gemma":0.0002639269,"threshold_uncertainty_score":0.01838696},"labels":[],"label_agreement":null},{"id":"W2064296938","doi":"10.1162/coli_a_00064","title":"A Strategy for Information Presentation in Spoken Dialog Systems","year":2011,"lang":"en","type":"article","venue":"Computational Linguistics","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":35,"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":"Ames Research Center; Atomic Energy of Canada Limited; National Aeronautics and Space Administration","keywords":"Dialog box; Computer science; Structuring; Dialog system; Process (computing); Presentation (obstetrics); User satisfaction; Human–computer interaction; Information retrieval; World Wide Web","score_opus":0.06398151558250546,"score_gpt":0.27997948751890905,"score_spread":0.21599797193640358,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2064296938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0073882765,0.0006360658,0.979122,0.00092746614,0.00016279674,0.00047823024,0.000084913656,0.0037310862,0.0074691707],"genre_scores_gemma":[0.17024484,0.0005164403,0.81628233,0.00084741006,0.00017345152,0.0012715757,0.00024778015,0.0005221314,0.009894004],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99388605,0.003331413,0.0004494616,0.00091342797,0.001253006,0.00016659923],"domain_scores_gemma":[0.9948985,0.0028630018,0.00034553534,0.0009449609,0.0007223396,0.00022578474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041529136,0.0023625328,0.0011083173,0.0017254385,0.0016870277,0.004986439,0.002877066,0.0034430642,0.006273338],"category_scores_gemma":[0.0133602265,0.0009415048,0.0011570135,0.0010129132,0.002904812,0.00517786,0.0033322053,0.0020559318,0.0038106672],"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":[0.0008624864,0.00046041954,0.0014856581,0.0013011921,0.00024050921,0.0012071917,0.009580569,0.025991842,0.130729,0.29332748,0.018115465,0.51669824],"study_design_scores_gemma":[0.00047287755,0.0016915117,0.0011466765,0.0004682843,0.00027553653,0.0023269965,0.0025029636,0.4424582,0.08469159,0.27734512,0.18621776,0.00040232347],"about_ca_topic_score_codex":0.0011522701,"about_ca_topic_score_gemma":0.0008716763,"teacher_disagreement_score":0.006273338,"about_ca_system_score_codex":0.0011719938,"about_ca_system_score_gemma":0.0011533957,"threshold_uncertainty_score":0.02196294},"labels":[],"label_agreement":null},{"id":"W2065341059","doi":"10.1177/154193120705100457","title":"Supporting Asynchronous Dialogs in the Communication of Army Operations Orders","year":2007,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Speech and dialogue systems","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":"Army Research Laboratory","keywords":"Asynchronous communication; Usability; Computer science; Likert scale; Face-to-face; Plan (archaeology); Multimedia; Human–computer interaction; Psychology; Telecommunications","score_opus":0.015246863750400328,"score_gpt":0.25836169208356813,"score_spread":0.2431148283331678,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065341059","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":[0.98021597,0.00016281116,0.013892033,0.00022928063,0.000034318982,0.00033267972,0.000079200174,0.00029489445,0.0047587026],"genre_scores_gemma":[0.9825152,0.00008947309,0.015915127,0.00008738061,0.000036270398,0.0002570599,0.00007258159,0.00003068047,0.0009961639],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98325205,0.013512554,0.00057048723,0.0007674685,0.0015236173,0.00037378285],"domain_scores_gemma":[0.8464628,0.13754213,0.00687937,0.0035106337,0.003995344,0.0016096759],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011035698,0.00083139946,0.0004213883,0.0014508291,0.0015593412,0.0024268066,0.0017192208,0.0014421509,0.0029625667],"category_scores_gemma":[0.0832448,0.00048715566,0.0002700947,0.00071967934,0.0008267471,0.0035976376,0.0018149777,0.0009930559,0.0008191546],"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":[0.004877721,0.00717285,0.08851962,0.003698453,0.00019815461,0.004498442,0.30272168,0.008727458,0.0659834,0.004107516,0.005617339,0.5038774],"study_design_scores_gemma":[0.0028483737,0.028009476,0.2954063,0.003373126,0.0010623024,0.00831536,0.29762697,0.15821777,0.07355686,0.012011392,0.118398815,0.0011732292],"about_ca_topic_score_codex":0.00093603315,"about_ca_topic_score_gemma":0.0011180387,"teacher_disagreement_score":0.011035698,"about_ca_system_score_codex":0.0007379935,"about_ca_system_score_gemma":0.00097382895,"threshold_uncertainty_score":0.05836302},"labels":[],"label_agreement":null},{"id":"W2065905229","doi":"10.3115/1628195.1628197","title":"Testing the efficacy of part-of-speech information in word completion","year":2003,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Toronto","funders":"","keywords":"Bigram; Trigram; Word (group theory); Computer science; Keystroke logging; Natural language processing; Artificial intelligence; Speech recognition; Test (biology); Part of speech; Mathematics","score_opus":0.043537412831188456,"score_gpt":0.24864578464466247,"score_spread":0.20510837181347402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2065905229","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":[0.9231483,0.0009417592,0.06714267,0.00021576796,0.00019270284,0.00035175803,0.0006364445,0.004999364,0.002371236],"genre_scores_gemma":[0.82438093,0.000311113,0.1688689,0.0001266433,0.00009964264,0.00024834837,0.0027045,0.00055060786,0.0027093145],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959019,0.0017146218,0.00038221804,0.001083713,0.00064581435,0.0002717628],"domain_scores_gemma":[0.93817484,0.05081137,0.0013495479,0.004384457,0.0042552594,0.0010244774],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0075885262,0.0022159617,0.0014080107,0.0011203763,0.00077983935,0.0012383349,0.0021568194,0.0020069527,0.0028762303],"category_scores_gemma":[0.045961082,0.0005730617,0.0007449914,0.0015458498,0.0007279883,0.004270961,0.0016401589,0.001847842,0.0020104416],"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":[0.012468056,0.0067768474,0.022930775,0.0017073598,0.0008966343,0.0004063957,0.00078562106,0.111350976,0.14598322,0.0013490339,0.0049205194,0.69042456],"study_design_scores_gemma":[0.0010633157,0.0075344522,0.01579887,0.00006200653,0.00047101174,0.0003942922,0.00045861152,0.7821069,0.18811767,0.0014478735,0.0023965947,0.00014841325],"about_ca_topic_score_codex":0.005009709,"about_ca_topic_score_gemma":0.0056153936,"teacher_disagreement_score":0.0075885262,"about_ca_system_score_codex":0.00038417176,"about_ca_system_score_gemma":0.0012448379,"threshold_uncertainty_score":0.040132403},"labels":[],"label_agreement":null},{"id":"W2067870511","doi":"10.1075/lab.1.1.10per","title":"What I don’t understand about interfaces","year":2011,"lang":"en","type":"article","venue":"Linguistic Approaches to Bilingualism","topic":"Speech and dialogue systems","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":"University of Toronto","funders":"","keywords":"Psychology; Computer science; Human–computer interaction","score_opus":0.23936654446420005,"score_gpt":0.26830916414070854,"score_spread":0.02894261967650849,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2067870511","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0038376385,0.041182995,0.010167382,0.83043736,0.023410194,0.000022011616,0.0001847441,0.00021510053,0.09054258],"genre_scores_gemma":[0.17752203,0.06255367,0.011386113,0.6214463,0.030380715,0.00017056872,0.0004833732,0.0006249042,0.09543227],"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99356985,0.0029843654,0.0003299588,0.00056821894,0.0019758146,0.0005717026],"domain_scores_gemma":[0.9852174,0.007008117,0.0006250202,0.0009909801,0.004831482,0.0013268646],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004847155,0.00062176486,0.00074772723,0.0015540185,0.003089833,0.009477218,0.0011939945,0.0055680186,0.0148197105],"category_scores_gemma":[0.027503725,0.00033213088,0.00057622825,0.0010866403,0.009305159,0.019008169,0.0029951176,0.009499665,0.006125178],"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":[0.00011919376,0.000107556756,0.0022038424,0.0018446133,0.000077364355,0.00061839353,0.021921752,0.00022170905,0.0013868444,0.25376794,0.49948478,0.21824613],"study_design_scores_gemma":[0.00002503306,0.000039905357,0.0007572703,0.0018678821,0.000044392877,0.0010724805,0.014589226,0.00029993826,0.0004967574,0.14682041,0.83394146,0.000045334808],"about_ca_topic_score_codex":0.008207822,"about_ca_topic_score_gemma":0.0076013035,"teacher_disagreement_score":0.0148197105,"about_ca_system_score_codex":0.0027586387,"about_ca_system_score_gemma":0.005080946,"threshold_uncertainty_score":0.04957688},"labels":[],"label_agreement":null},{"id":"W2069858636","doi":"10.1177/00238309060490040301","title":"On the Function of Stress Rhythms in Speech: Evidence of a Link with Grouping Effects on Serial Memory","year":2006,"lang":"en","type":"article","venue":"Language and Speech","topic":"Speech and dialogue systems","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":"Université de Montréal","funders":"","keywords":"Prosody; Recall; Stress (linguistics); Rhythm; Psychology; Set (abstract data type); Cognitive psychology; Speech recognition; Variation (astronomy); Communication; Linguistics; Computer science","score_opus":0.009674822164700498,"score_gpt":0.21910835411460028,"score_spread":0.20943353194989978,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2069858636","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":[0.9980724,0.00022803457,0.00072411686,0.000027445598,0.0000020187335,0.0000069106322,0.00001996887,0.000009186209,0.00090988586],"genre_scores_gemma":[0.9988651,0.00025024274,0.0004962086,0.00003155228,0.000012595438,0.000012312423,0.000052434272,0.0000063124485,0.00027320252],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99962604,0.0001250232,0.000033183627,0.00007076797,0.000105130595,0.000039953644],"domain_scores_gemma":[0.9872104,0.008251901,0.0020794317,0.0014581446,0.000527336,0.00047270383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012518687,0.00035667894,0.00025035927,0.0007407858,0.00023614145,0.00065662124,0.00030905823,0.0004548806,0.0027480912],"category_scores_gemma":[0.0056713144,0.00024811627,0.00016503302,0.00033760426,0.001242754,0.0005849495,0.00050915167,0.0003834124,0.00043206353],"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":[0.007613401,0.0015716177,0.15682824,0.00066824874,0.00028669377,0.0009864728,0.004791278,0.00090192637,0.69680756,0.0013308084,0.00028322282,0.12793052],"study_design_scores_gemma":[0.00011457763,0.0035271165,0.93375826,0.000030187226,0.00015444773,0.00093380484,0.0004764015,0.0011667174,0.05792916,0.0013742788,0.0005015601,0.000033425178],"about_ca_topic_score_codex":0.0008824588,"about_ca_topic_score_gemma":0.0008166342,"teacher_disagreement_score":0.0027480912,"about_ca_system_score_codex":0.00015089539,"about_ca_system_score_gemma":0.00015568962,"threshold_uncertainty_score":0.009193301},"labels":[],"label_agreement":null},{"id":"W2074991903","doi":"10.1145/2370216.2370408","title":"Modeling ontology for multimodal interaction in ubiquitous computing systems","year":2012,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 à Montréal","funders":"","keywords":"Gesture; Ontology; Computer science; Human–computer interaction; Ubiquitous computing; Robot; Multimodal interaction; Human–robot interaction; World Wide Web; Artificial intelligence","score_opus":0.04593518450828474,"score_gpt":0.30451104698778336,"score_spread":0.2585758624794986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2074991903","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":[0.012210828,0.0007670411,0.9646426,0.0016288854,0.00013537041,0.00031528005,0.0009972625,0.0008234009,0.018479384],"genre_scores_gemma":[0.28878224,0.0014857624,0.69373375,0.0004420787,0.00009501468,0.0009202164,0.0031216438,0.00034099317,0.011078287],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980288,0.0007917122,0.00026434803,0.00023236217,0.0004901388,0.00019252462],"domain_scores_gemma":[0.9989324,0.00040847543,0.00009161333,0.00019723256,0.00029098225,0.00007920522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022685651,0.00055059564,0.0006947824,0.0015305673,0.0017373692,0.003603185,0.0019937218,0.0016124363,0.004417315],"category_scores_gemma":[0.004610734,0.00062095944,0.0022806767,0.0016997003,0.0013333833,0.006092672,0.0028426882,0.0018124249,0.0008958294],"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":[0.000051798637,0.000101735124,0.0013533155,0.0002525207,0.000097339434,0.0005455175,0.002233976,0.044464357,0.0013331732,0.8973045,0.006266422,0.045995355],"study_design_scores_gemma":[0.000039921062,0.000037462225,0.0007279858,0.00024849316,0.00015036669,0.0003816376,0.0013382293,0.39857158,0.0016159468,0.47719657,0.11963241,0.00005929576],"about_ca_topic_score_codex":0.029055996,"about_ca_topic_score_gemma":0.029322332,"teacher_disagreement_score":0.029055996,"about_ca_system_score_codex":0.0022881255,"about_ca_system_score_gemma":0.002914637,"threshold_uncertainty_score":0.05777371},"labels":[],"label_agreement":null},{"id":"W2075848916","doi":"10.4236/jsea.2013.67045","title":"Modeling Rules Fission and Modality Selection Using Ontology","year":2013,"lang":"en","type":"article","venue":"Journal of Software Engineering and Applications","topic":"Speech and dialogue systems","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":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Ontology; Modality (human–computer interaction); Modalities; Vocabulary; Software engineering; Architecture; Human–computer interaction; Selection (genetic algorithm); Artificial intelligence","score_opus":0.013007006563956973,"score_gpt":0.225039342293484,"score_spread":0.212032335729527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2075848916","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014628697,0.00018864103,0.97156817,0.00041000615,0.00004647,0.00029544538,0.00060845807,0.0006740919,0.011580068],"genre_scores_gemma":[0.18932323,0.0005501246,0.7996303,0.00014462622,0.00004837142,0.0005297892,0.0024777576,0.00023965888,0.0070561594],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99664116,0.00089219934,0.0004992905,0.0006550387,0.0009885593,0.00032377138],"domain_scores_gemma":[0.9978345,0.000942969,0.00021687035,0.0004216633,0.00045886938,0.00012507197],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029639092,0.0007460891,0.00058216794,0.003037451,0.0016454228,0.0042554154,0.0022729782,0.0014245271,0.004008503],"category_scores_gemma":[0.0051372666,0.0007500877,0.0027993652,0.0017761439,0.0018572826,0.0061904346,0.0029002852,0.0018973933,0.0008364788],"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":[0.00014311059,0.00017562594,0.0035448058,0.00026616018,0.00013098307,0.0013860845,0.0025941564,0.07035297,0.006802348,0.82975423,0.0035812233,0.08126818],"study_design_scores_gemma":[0.00005729188,0.00005865376,0.0010926175,0.00023428614,0.00025033826,0.0007898928,0.0010786395,0.52356195,0.01008725,0.35098732,0.11170577,0.00009591556],"about_ca_topic_score_codex":0.019164553,"about_ca_topic_score_gemma":0.017082674,"teacher_disagreement_score":0.019164553,"about_ca_system_score_codex":0.0019459893,"about_ca_system_score_gemma":0.0026613849,"threshold_uncertainty_score":0.038106024},"labels":[],"label_agreement":null},{"id":"W2076370088","doi":"10.1037//0882-7974.15.1.65","title":"Effect of off-target verbosity on communication efficiency in a referential communication task.","year":2000,"lang":"en","type":"article","venue":"Psychology and Aging","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":66,"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":"Psychology; Task (project management); Focus (optics); Cognitive psychology; Inhibitory control; Nonverbal communication; Cognition; Developmental psychology; Neuroscience","score_opus":0.011705810173394322,"score_gpt":0.2994140197466366,"score_spread":0.2877082095732423,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076370088","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":[0.99926883,0.000024865416,0.00006057744,0.00001235117,0.000003098081,0.0000064275814,0.00002274006,0.0000045106995,0.00059666584],"genre_scores_gemma":[0.9994486,0.00002373393,0.00014919756,0.000020399666,0.0000035478727,0.000016732734,0.00007017031,0.0000070239175,0.00026057192],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99887925,0.00052323844,0.000111782014,0.00015258069,0.0002309701,0.00010209706],"domain_scores_gemma":[0.97484684,0.019250268,0.0029719379,0.00083515316,0.00051654316,0.0015792231],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016556673,0.00048141996,0.00048501894,0.0005141042,0.0002598877,0.0009019889,0.00026961562,0.00050381775,0.0022677795],"category_scores_gemma":[0.025018245,0.00025633175,0.00013832595,0.00020354455,0.00050300104,0.00042207516,0.0009618775,0.0005031514,0.0003266543],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.039421335,0.007931639,0.60605454,0.0003908821,0.00052919594,0.0021575168,0.010170071,0.0007009577,0.23845766,0.0004958833,0.0013759339,0.09231444],"study_design_scores_gemma":[0.00028912723,0.005326889,0.9823683,0.000023808227,0.00012070387,0.00094150257,0.0008038047,0.00084478076,0.008460136,0.0003743717,0.00041716354,0.00002941884],"about_ca_topic_score_codex":0.0005523191,"about_ca_topic_score_gemma":0.00050752505,"teacher_disagreement_score":0.0022677795,"about_ca_system_score_codex":0.00014498646,"about_ca_system_score_gemma":0.00014430692,"threshold_uncertainty_score":0.008756101},"labels":[],"label_agreement":null},{"id":"W2076778058","doi":"10.2466/pr0.94.2.655-662","title":"Concordance among Readers of Self-Help Books about Important Ideas","year":2004,"lang":"en","type":"article","venue":"Psychological Reports","topic":"Speech and dialogue systems","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 Manitoba","funders":"","keywords":"Concordance; Psychology; Agreement; Social psychology; Linguistics; Medicine","score_opus":0.02151090814869273,"score_gpt":0.28631874979833294,"score_spread":0.2648078416496402,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2076778058","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":[0.9989034,0.000062921376,0.00012363662,0.000022307724,0.0000044437943,0.0000068630075,0.00003488542,0.00000654266,0.000835081],"genre_scores_gemma":[0.99928516,0.000036391575,0.00012501537,0.0000127574785,0.0000071522372,0.000008592317,0.000082411185,0.000004325592,0.0004382472],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99489343,0.002193378,0.00054098136,0.0005918552,0.0014908925,0.00028953113],"domain_scores_gemma":[0.93433225,0.048185833,0.0075279814,0.0028002844,0.0055611064,0.001592439],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005754321,0.0001861269,0.00035474348,0.00246488,0.000508157,0.0016850043,0.000486999,0.0005936026,0.002187093],"category_scores_gemma":[0.04542454,0.00044163797,0.00022438515,0.00071054616,0.0010628479,0.00071680837,0.0010430977,0.0006364538,0.0006956377],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00084618287,0.00015300847,0.92669916,0.000091766255,0.00012925922,0.0003439778,0.050443202,0.00015207176,0.0047026975,0.00016736175,0.00030631636,0.015964951],"study_design_scores_gemma":[0.000025748446,0.00034493025,0.98003334,0.000034797304,0.00003800746,0.0005532767,0.01506107,0.0010360758,0.0019339441,0.00023509415,0.0006635085,0.000040339797],"about_ca_topic_score_codex":0.0015899992,"about_ca_topic_score_gemma":0.0015920085,"teacher_disagreement_score":0.005754321,"about_ca_system_score_codex":0.00029490425,"about_ca_system_score_gemma":0.00015712163,"threshold_uncertainty_score":0.030432105},"labels":[],"label_agreement":null},{"id":"W2077983110","doi":"10.4018/jdet.2008040101","title":"Speech-Enabled Tools for Augmented Interaction in E-Learning Applications","year":2008,"lang":"en","type":"article","venue":"International Journal of Distance Education Technologies","topic":"Speech and dialogue systems","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":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université de Moncton","funders":"","keywords":"Computer science; Multimedia; Dictation; Human–computer interaction; Context (archaeology); The Internet; World Wide Web; Cognitive load; Process (computing); Cognition; Speech recognition","score_opus":0.024588835351077663,"score_gpt":0.3022224609579237,"score_spread":0.27763362560684607,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2077983110","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.259271,0.005623517,0.6823774,0.0006065032,0.00041549804,0.0004512228,0.00032246395,0.009128174,0.041804276],"genre_scores_gemma":[0.769594,0.0018058484,0.20164372,0.00024794225,0.00013763395,0.00038111303,0.00028626787,0.0003139576,0.025589531],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994197,0.00025452214,0.000042754815,0.000050896364,0.00019140156,0.000040680567],"domain_scores_gemma":[0.99892455,0.0007506508,0.000046759473,0.00010682272,0.00012568367,0.000045541976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005758063,0.0004440175,0.00021667087,0.00042571532,0.00036224406,0.0014446313,0.0005840935,0.000731579,0.009043325],"category_scores_gemma":[0.0020526405,0.0001888394,0.0002545597,0.00028560316,0.00034927722,0.0012460842,0.0010851807,0.00035029813,0.0019934343],"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":[0.0009001384,0.00028131233,0.002042988,0.0010629401,0.00006427575,0.0009618712,0.0027417496,0.0037011728,0.14359513,0.0127240755,0.0071894866,0.8247349],"study_design_scores_gemma":[0.00047124305,0.0038162302,0.02202328,0.00095382734,0.00062296103,0.007145284,0.003665912,0.10275111,0.30498102,0.024109783,0.5290652,0.00039418993],"about_ca_topic_score_codex":0.0003442086,"about_ca_topic_score_gemma":0.0006333901,"teacher_disagreement_score":0.009043325,"about_ca_system_score_codex":0.00015806712,"about_ca_system_score_gemma":0.00023550738,"threshold_uncertainty_score":0.030252993},"labels":[],"label_agreement":null},{"id":"W2078790381","doi":"10.1145/587078.587085","title":"Explaining effects of eye gaze on mediated group conversations:","year":2002,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":101,"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":"Gaze; Task (project management); Psychology; Nonverbal communication; Cognitive psychology; Computer science; Communication; Artificial intelligence","score_opus":0.014912988056642096,"score_gpt":0.21219965305005678,"score_spread":0.19728666499341468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2078790381","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":[0.9465581,0.00029845885,0.0509504,0.00012028369,0.000017242244,0.00009142056,0.00015257561,0.00017482722,0.0016365836],"genre_scores_gemma":[0.9930434,0.0001120125,0.0064255777,0.000017400558,0.000012497799,0.000049665774,0.00008332942,0.000025825455,0.0002302305],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9986639,0.0008865259,0.000035372712,0.00021702495,0.00012279485,0.00007449206],"domain_scores_gemma":[0.97814524,0.019370155,0.0008516283,0.0010407956,0.00047416822,0.0001179885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021615648,0.00064322416,0.00040724335,0.00046451186,0.0002917773,0.00061204867,0.00047570578,0.00075371977,0.0025788036],"category_scores_gemma":[0.023804184,0.00033655728,0.00063752016,0.00022853022,0.00038221027,0.001099904,0.0008227677,0.0005003726,0.0003498219],"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":[0.006633207,0.00095138303,0.26875812,0.0014792079,0.0009546158,0.0011968673,0.014287469,0.08215333,0.2766096,0.008137753,0.0014946472,0.33734384],"study_design_scores_gemma":[0.00047741423,0.002861324,0.40385985,0.00018299709,0.0008602435,0.0009461623,0.0017968486,0.50974435,0.06141424,0.014832713,0.0028279438,0.0001959336],"about_ca_topic_score_codex":0.003602307,"about_ca_topic_score_gemma":0.0023278412,"teacher_disagreement_score":0.003602307,"about_ca_system_score_codex":0.00039595016,"about_ca_system_score_gemma":0.00025140386,"threshold_uncertainty_score":0.011431575},"labels":[],"label_agreement":null},{"id":"W2079908694","doi":"10.1002/1097-4571(2000)9999:9999<::aid-asi1005>3.0.co;2-2","title":"Using Kintsch's discourse comprehension theory to model the user's coding of an informative message from an enabling information retrieval system","year":2000,"lang":"en","type":"article","venue":"Journal of the American Society for Information Science","topic":"Speech and dialogue systems","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":"Concordia University; McGill University","funders":"","keywords":"Computer science; Comprehension; Coding (social sciences); Human–computer interaction; Task (project management); Focus (optics); Information retrieval; Natural language processing; Programming language; Engineering","score_opus":0.029616780525867668,"score_gpt":0.3159648314828491,"score_spread":0.2863480509569814,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2079908694","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022784203,0.00037220513,0.9372193,0.0013228498,0.000027857011,0.0002178946,0.00012818798,0.0005239354,0.03740358],"genre_scores_gemma":[0.5746078,0.000762045,0.41267353,0.00035526784,0.000041932806,0.0008899588,0.0002259099,0.00016996154,0.010273559],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99674463,0.0018338243,0.00024379366,0.0004504473,0.0005401943,0.00018703472],"domain_scores_gemma":[0.9950599,0.0033679423,0.0003981499,0.00060320133,0.0004926718,0.00007808548],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038838307,0.0008793682,0.0004510251,0.0032151574,0.0015140467,0.004349263,0.0015921565,0.0020197143,0.005421816],"category_scores_gemma":[0.010814132,0.0006670503,0.0012998453,0.0016396616,0.008549624,0.01159216,0.0027351817,0.0021459472,0.0014434679],"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":[0.00004732804,0.000029627952,0.0009330191,0.00017063487,0.000016853508,0.00024617085,0.0190835,0.0047494546,0.0029947252,0.94619596,0.0007375051,0.024795268],"study_design_scores_gemma":[0.000054876487,0.00020761586,0.0020424102,0.00023604954,0.00011853422,0.0010800041,0.006006527,0.101768576,0.016578607,0.8065854,0.0651721,0.00014939513],"about_ca_topic_score_codex":0.006041824,"about_ca_topic_score_gemma":0.002579016,"teacher_disagreement_score":0.006041824,"about_ca_system_score_codex":0.0034760714,"about_ca_system_score_gemma":0.00219746,"threshold_uncertainty_score":0.025220752},"labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low"},{"model":"gpt","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"low"}],"label_agreement":"agree"},{"id":"W208017534","doi":"10.1016/b978-008044910-4.00451-x","title":"Haptic or Touch-Based Knowledge","year":2009,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Speech and dialogue systems","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 Calgary","funders":"","keywords":"Haptic technology; Computer science; Human–computer interaction; Artificial intelligence","score_opus":0.026795479803276966,"score_gpt":0.2514630887228468,"score_spread":0.22466760891956983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W208017534","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":[0.0012594443,0.013992806,0.03234908,0.0009943225,0.0004672739,0.000019038416,0.00014725681,0.00024296518,0.9505277],"genre_scores_gemma":[0.027025,0.021127954,0.015819749,0.00067614426,0.0004949205,0.00006311202,0.0004739351,0.00017026438,0.934149],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.999884,0.000012899605,0.00000798527,0.000029539995,0.00005566609,0.000009911035],"domain_scores_gemma":[0.9998385,0.00009401439,0.0000061992296,0.000024377372,0.000023619272,0.000013350528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00018817886,0.00067740434,0.00040899258,0.0008141292,0.0004388579,0.004079837,0.00069824635,0.0011764226,0.072096765],"category_scores_gemma":[0.00053027575,0.0002733021,0.00028328123,0.0011174668,0.0016616698,0.005507989,0.00094466045,0.0011211962,0.022647472],"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":[0.000024919495,0.00003641866,0.00009811652,0.00053992815,0.000012393235,0.00018694009,0.0012288116,0.00053996366,0.0033904093,0.44821897,0.06362405,0.48209915],"study_design_scores_gemma":[0.000006513281,0.000021477712,0.0003124594,0.0004889219,0.000009990598,0.00044773705,0.0003542115,0.00079365453,0.00095910294,0.14275192,0.8538412,0.00001274475],"about_ca_topic_score_codex":0.0013271746,"about_ca_topic_score_gemma":0.0016818374,"teacher_disagreement_score":0.072096765,"about_ca_system_score_codex":0.0005566022,"about_ca_system_score_gemma":0.0005493736,"threshold_uncertainty_score":0.24118769},"labels":[],"label_agreement":null},{"id":"W2080765428","doi":"10.3166/ria.23.485-501","title":"Cultural elements in internet software localization","year":2009,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":3,"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":"The Internet; Software; Computer science; Business; World Wide Web; Programming language","score_opus":0.055862524815685675,"score_gpt":0.2924090768366667,"score_spread":0.23654655202098104,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2080765428","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":[0.6824938,0.007992183,0.07063186,0.004715199,0.00013384309,0.00010191339,0.00007027294,0.0001725309,0.23368832],"genre_scores_gemma":[0.9923308,0.0009919247,0.0044408836,0.00011377333,0.000021788966,0.000024123754,0.000015962476,0.000028857845,0.0020318676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99733186,0.0017187294,0.00013873358,0.00019554293,0.00040899875,0.00020620011],"domain_scores_gemma":[0.9964742,0.001776069,0.0005000774,0.00036136652,0.0006863878,0.00020183652],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013435546,0.00037661186,0.00023539692,0.0018038636,0.0029535368,0.0040619485,0.00050362496,0.0009006934,0.001641232],"category_scores_gemma":[0.0072538787,0.00030794792,0.000293621,0.0022627315,0.009020753,0.0048242016,0.0030122716,0.0010406406,0.00023880319],"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":[0.00014500052,0.000090206224,0.024183284,0.00046036794,0.000052487667,0.0018310494,0.161912,0.0028132845,0.002615632,0.663137,0.0019417643,0.14081788],"study_design_scores_gemma":[0.000074279014,0.00029021845,0.05633022,0.0014630313,0.0002750541,0.0056466535,0.23259422,0.020192534,0.0068383636,0.46678448,0.20922889,0.00028203745],"about_ca_topic_score_codex":0.0049307737,"about_ca_topic_score_gemma":0.0035305107,"teacher_disagreement_score":0.0049307737,"about_ca_system_score_codex":0.0019152529,"about_ca_system_score_gemma":0.0010811172,"threshold_uncertainty_score":0.013896167},"labels":[],"label_agreement":null},{"id":"W2082373168","doi":"10.1007/s10055-005-0156-2","title":"A two visual systems approach to understanding voice and gestural interaction","year":2005,"lang":"en","type":"article","venue":"Virtual Reality","topic":"Speech and dialogue systems","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":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Human–computer interaction; Computer graphics; Computer graphics (images); Computer vision; Multimedia; Artificial intelligence","score_opus":0.0800735956009654,"score_gpt":0.3234852322685822,"score_spread":0.24341163666761684,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2082373168","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0070192358,0.00070136215,0.9704624,0.0009677746,0.00015200538,0.00007635362,0.000059090024,0.0005788661,0.01998286],"genre_scores_gemma":[0.577643,0.0012037889,0.39590424,0.00046401456,0.0002580974,0.00031872722,0.00021482821,0.00031691047,0.023676377],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993864,0.00016427731,0.00003948864,0.00016462468,0.00015887796,0.0000862503],"domain_scores_gemma":[0.9993087,0.00029854645,0.00006268936,0.00009147111,0.00017303873,0.0000654864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000583692,0.0008238876,0.00050201913,0.0013756185,0.0007813825,0.004524311,0.001657355,0.001628069,0.009168016],"category_scores_gemma":[0.0026302286,0.0007060539,0.0012833048,0.0005904954,0.0022207852,0.0042332434,0.0024546352,0.0014918292,0.001188507],"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":[0.00029297732,0.000094718795,0.0010754676,0.0004256953,0.00013605766,0.00078759267,0.0038856186,0.021673037,0.050504163,0.7345672,0.0035662958,0.18299109],"study_design_scores_gemma":[0.00010442187,0.00022744082,0.0025769547,0.00017218996,0.00016187248,0.00077838294,0.0024306206,0.2575356,0.02172956,0.6717999,0.04234811,0.00013498588],"about_ca_topic_score_codex":0.0075735743,"about_ca_topic_score_gemma":0.004225028,"teacher_disagreement_score":0.009168016,"about_ca_system_score_codex":0.0012209387,"about_ca_system_score_gemma":0.0010294841,"threshold_uncertainty_score":0.030670106},"labels":[],"label_agreement":null},{"id":"W2084857899","doi":"10.1007/s10606-014-9215-0","title":"From I-Awareness to We-Awareness in CSCW","year":2015,"lang":"en","type":"article","venue":"Computer Supported Cooperative Work (CSCW)","topic":"Speech and dialogue systems","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":"University of Victoria","funders":"","keywords":"Computer-supported cooperative work; Psychology; Computer science; Engineering; Work (physics)","score_opus":0.05386134155656846,"score_gpt":0.2875855563739215,"score_spread":0.23372421481735306,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2084857899","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":[0.3421261,0.018679874,0.2036163,0.033233967,0.0009665073,0.00016400784,0.00020333982,0.0006099585,0.40039995],"genre_scores_gemma":[0.9932846,0.0007903479,0.0032472569,0.00038697166,0.00006300203,0.00003183277,0.000023574488,0.00003387624,0.0021386233],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9968086,0.0017376235,0.00016057468,0.0005069044,0.0003850987,0.00040122255],"domain_scores_gemma":[0.99332386,0.0038494412,0.0006476672,0.00094425154,0.0005266198,0.0007081968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002767363,0.00042234742,0.00035775846,0.0019864899,0.0030356178,0.008994566,0.0010552986,0.002430632,0.0032254877],"category_scores_gemma":[0.010399511,0.00055905856,0.0003864773,0.0022939153,0.012313271,0.01785817,0.0054379622,0.003104346,0.00039712072],"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":[0.00011116518,0.00014246284,0.010042521,0.00031845606,0.000049841565,0.00042325872,0.08785688,0.0020057429,0.0019419518,0.8019477,0.003927983,0.091232084],"study_design_scores_gemma":[0.00002674608,0.00010267164,0.0053377706,0.00041590683,0.000054508844,0.0003618339,0.0636733,0.0055747605,0.0020732323,0.8742865,0.048012868,0.00007996106],"about_ca_topic_score_codex":0.0061983573,"about_ca_topic_score_gemma":0.003292319,"teacher_disagreement_score":0.008994566,"about_ca_system_score_codex":0.0017191096,"about_ca_system_score_gemma":0.0028058526,"threshold_uncertainty_score":0.014635444},"labels":[],"label_agreement":null},{"id":"W2086217601","doi":"10.1145/1414471.1414522","title":"MySpeechWeb","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Software deployment; Computer science; Documentation; Open source; Suite; World Wide Web; Software; Web application; Speech synthesis; Human–computer interaction; Software engineering; Multimedia; Artificial intelligence; Operating system","score_opus":0.023984350620219606,"score_gpt":0.20413143585233468,"score_spread":0.18014708523211506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086217601","genre_codex":"other","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":[0.012495041,0.0022944845,0.046137337,0.0014139798,0.0010396896,0.000764106,0.11875999,0.33861133,0.47848403],"genre_scores_gemma":[0.066752106,0.0017914389,0.029359441,0.0026645795,0.0006671208,0.0011196254,0.26815072,0.04879947,0.58069545],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993666,0.0000897896,0.000060063714,0.00013395466,0.0002499344,0.000099709396],"domain_scores_gemma":[0.99767727,0.00081786694,0.00009300969,0.00066785055,0.00040307204,0.00034100303],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007866893,0.0009772885,0.0008592448,0.0019628848,0.0007160689,0.0024545195,0.001956962,0.0015745215,0.43105894],"category_scores_gemma":[0.004311567,0.00054058764,0.00043918221,0.0015743086,0.00028660696,0.005998749,0.003237408,0.0010969454,0.3358759],"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":[0.00040831283,0.00012730955,0.00081862055,0.0005583535,0.00001931112,0.00035129985,0.00022673556,0.00015679204,0.0043760748,0.0050250236,0.78650683,0.20142536],"study_design_scores_gemma":[0.00005027738,0.000044576394,0.0023176635,0.00008453138,0.000010157041,0.00040476528,0.00008749161,0.00086852186,0.0044168974,0.0039179036,0.98774827,0.00004907544],"about_ca_topic_score_codex":0.0010194188,"about_ca_topic_score_gemma":0.0013529628,"teacher_disagreement_score":0.43105894,"about_ca_system_score_codex":0.00037874785,"about_ca_system_score_gemma":0.00060153456,"threshold_uncertainty_score":0.81152534},"labels":[],"label_agreement":null},{"id":"W2086334724","doi":"10.1037/a0027921","title":"Prosodic temporal alignment of co-speech gestures to speech facilitates referent resolution.","year":2012,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Human Perception & Performance","topic":"Speech and dialogue systems","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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Referent; Gesture; Perception; Speech recognition; Object (grammar); Prosody; Motion (physics); Computer science; Psychology; Communication; Linguistics; Artificial intelligence","score_opus":0.05606240103822245,"score_gpt":0.3640536705010532,"score_spread":0.30799126946283073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2086334724","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":[0.9416867,0.0004490359,0.04178961,0.00021314187,0.00012850993,0.00014152548,0.00012940055,0.00020030848,0.01526179],"genre_scores_gemma":[0.9741701,0.00018338156,0.023930708,0.00011237976,0.000036546633,0.000115279916,0.00011110398,0.000066453526,0.0012739197],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9994074,0.00019162531,0.000027776101,0.0001979519,0.00013028066,0.00004488189],"domain_scores_gemma":[0.9977937,0.0012110884,0.0004188602,0.00020528802,0.00023284729,0.00013821688],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010149523,0.00032956968,0.00021447528,0.00033866483,0.0002753967,0.0008915633,0.00045504948,0.0005968997,0.0037262163],"category_scores_gemma":[0.0076201684,0.0003566344,0.00020055314,0.00014938759,0.00043778593,0.0011438783,0.0007781501,0.00063460215,0.0006611925],"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":[0.0005613917,0.000075705415,0.0021983911,0.00019732119,0.000015158132,0.00019922169,0.001430824,0.00017370062,0.96311885,0.001143043,0.000155672,0.030730642],"study_design_scores_gemma":[0.00035750362,0.0045898925,0.37463212,0.00026295945,0.0003719806,0.002809862,0.0051379465,0.025674498,0.5615774,0.009152764,0.015272847,0.0001602969],"about_ca_topic_score_codex":0.00033649136,"about_ca_topic_score_gemma":0.0006108973,"teacher_disagreement_score":0.0037262163,"about_ca_system_score_codex":0.00019019684,"about_ca_system_score_gemma":0.00027764792,"threshold_uncertainty_score":0.012465417},"labels":[],"label_agreement":null},{"id":"W2088868719","doi":"10.1109/ifsa-nafips.2013.6608485","title":"Using tagging in social networks to find groups of compatible users","year":2013,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"","keywords":"Computer science; Process (computing); Matching (statistics); Construct (python library); Information retrieval; Fuzzy logic; World Wide Web; Artificial intelligence","score_opus":0.044740560135071945,"score_gpt":0.27365686149958407,"score_spread":0.22891630136451213,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2088868719","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1418156,0.0004058424,0.8455721,0.00058054045,0.00006113109,0.00043487255,0.00026938884,0.0006849757,0.010175543],"genre_scores_gemma":[0.5338758,0.00021565933,0.46261528,0.00009985923,0.000040239218,0.0001890495,0.0004224684,0.00006165411,0.0024800017],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954157,0.0023130423,0.00030115125,0.00089575304,0.0008831934,0.00019114811],"domain_scores_gemma":[0.98877805,0.0069972905,0.0014719047,0.0015557063,0.00083676784,0.0003603346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004504185,0.00064029015,0.0006264527,0.0066276407,0.0029279192,0.004351089,0.0011734873,0.0016048598,0.0015534223],"category_scores_gemma":[0.015906228,0.00057664525,0.0007995272,0.0049055084,0.002555589,0.0075457306,0.0030482782,0.000670507,0.0006259119],"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":[0.0006186489,0.00040059022,0.059894186,0.00081315293,0.00048157806,0.0019747654,0.024140742,0.05067747,0.03731532,0.31575653,0.004630171,0.50329685],"study_design_scores_gemma":[0.00009255471,0.00031388915,0.014932602,0.00028138346,0.0003363758,0.0018730143,0.009219402,0.41786334,0.026664192,0.4857901,0.04236711,0.00026602615],"about_ca_topic_score_codex":0.0034034534,"about_ca_topic_score_gemma":0.005880308,"teacher_disagreement_score":0.0066276407,"about_ca_system_score_codex":0.001291123,"about_ca_system_score_gemma":0.0012054449,"threshold_uncertainty_score":0.023820698},"labels":[],"label_agreement":null},{"id":"W2090373925","doi":"10.1145/2207676.2208598","title":"Evaluating the implicit acquisition of second language vocabulary using a live wallpaper","year":2012,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":53,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nokia (Canada); University of Toronto","funders":"","keywords":"Vocabulary; Computer science; Wallpaper; Vocabulary learning; Recall; Language acquisition; Process (computing); Natural language processing; Linguistics; Psychology; Cognitive psychology; Mathematics education; Programming language","score_opus":0.047037801748276514,"score_gpt":0.3316468275054616,"score_spread":0.28460902575718505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090373925","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":[0.9981989,0.00006790194,0.0008230355,0.000012336628,0.0000063671314,0.00007657763,0.0000444797,0.000022878727,0.00074747414],"genre_scores_gemma":[0.98980147,0.00027303887,0.0054098223,0.000030314748,0.000011392059,0.00027111595,0.00021639296,0.000024305167,0.0039620944],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9987668,0.00041732937,0.00017715339,0.00018893524,0.00033220922,0.0001176774],"domain_scores_gemma":[0.9844148,0.011036156,0.0016776059,0.00083767215,0.0012768359,0.00075688853],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021058053,0.0005997656,0.00045853335,0.00048433658,0.000233943,0.0008233861,0.00054788805,0.0007352357,0.0033644086],"category_scores_gemma":[0.018304352,0.0002408134,0.00037951296,0.00016658907,0.00050446624,0.0016109837,0.00093466643,0.0007966369,0.00070415327],"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":[0.011087362,0.020566167,0.18804401,0.0025130925,0.00035726474,0.0013343472,0.036598314,0.0036712473,0.39564583,0.001180192,0.0013615274,0.33764067],"study_design_scores_gemma":[0.0007557765,0.12574708,0.57293844,0.0005111104,0.0005546427,0.00284953,0.014665439,0.019503994,0.24926299,0.0011594685,0.011739685,0.00031186605],"about_ca_topic_score_codex":0.0008973582,"about_ca_topic_score_gemma":0.0010563396,"teacher_disagreement_score":0.0033644086,"about_ca_system_score_codex":0.00017473017,"about_ca_system_score_gemma":0.00027194968,"threshold_uncertainty_score":0.0112550855},"labels":[],"label_agreement":null},{"id":"W2090668572","doi":"10.3115/1556328.1556339","title":"Enhancing commercial grammar-based applications using robust approaches to speech understanding","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Quebec Network for Research on Aging","funders":"","keywords":"Computer science; Leverage (statistics); Parsing; Spotting; Natural language processing; Grammar; Artificial intelligence; Rule-based machine translation; Dialog box; Phrase; Robustness (evolution); Speech recognition; Linguistics","score_opus":0.31945124128099844,"score_gpt":0.2900401565027381,"score_spread":0.02941108477826032,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2090668572","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.40264028,0.00045967315,0.5096472,0.00042807672,0.000087016095,0.0005487605,0.00071247766,0.08179092,0.0036855764],"genre_scores_gemma":[0.6984501,0.00018397688,0.295044,0.00024303726,0.00004852563,0.0002206895,0.0012862331,0.0029149763,0.0016083602],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9930981,0.0030325146,0.0004936626,0.001470486,0.001669539,0.00023572323],"domain_scores_gemma":[0.9560208,0.029655276,0.0015646301,0.0077079446,0.0046594613,0.00039191925],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006807664,0.0015046371,0.0009778193,0.0012462961,0.0004136691,0.0020989168,0.0020877516,0.0017300879,0.0021188566],"category_scores_gemma":[0.043163434,0.0005995073,0.00066506345,0.00063261576,0.00071162323,0.0029135465,0.0017503276,0.0015911653,0.0021714226],"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":[0.0013088812,0.00087015855,0.0116337715,0.0010673878,0.00040602568,0.0010977889,0.00397196,0.07261452,0.26390874,0.002593271,0.0055602207,0.63496727],"study_design_scores_gemma":[0.00012584869,0.00091287686,0.01201771,0.000078701545,0.00025910194,0.0011968133,0.0007539204,0.6792384,0.2852043,0.0062598777,0.0136537,0.00029889963],"about_ca_topic_score_codex":0.0015070158,"about_ca_topic_score_gemma":0.001361079,"teacher_disagreement_score":0.006807664,"about_ca_system_score_codex":0.0006158422,"about_ca_system_score_gemma":0.0008281593,"threshold_uncertainty_score":0.036002815},"labels":[],"label_agreement":null},{"id":"W2095667476","doi":"10.21236/ada434940","title":"\"Excuse me, where's the registration desk?\" Report on Integrating Systems for the Robot Challenge AAAI 2002","year":2002,"lang":"en","type":"report","venue":"","topic":"Speech and dialogue systems","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":"","keywords":"Excuse; Desk; Robot; Computer science; Aeronautics; Engineering; Operations research; Artificial intelligence; Political science; Operating system; Law","score_opus":0.09732591827250936,"score_gpt":0.3025008001036562,"score_spread":0.20517488183114685,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095667476","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":[0.029130844,0.0045160637,0.024549535,0.1660294,0.027745955,0.0027828913,0.01455303,0.007759458,0.7229329],"genre_scores_gemma":[0.033424363,0.0018849813,0.009560471,0.013730962,0.0015448871,0.0008400114,0.013093993,0.001361056,0.9245593],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9960402,0.00062819006,0.000185775,0.00030772144,0.002312176,0.00052585703],"domain_scores_gemma":[0.99237776,0.0013856082,0.00026585124,0.00051499513,0.0038691033,0.0015866703],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0073977215,0.0007886859,0.0003990242,0.0010329811,0.0038759026,0.005322215,0.0011599942,0.003171656,0.07664671],"category_scores_gemma":[0.010294993,0.0004986583,0.00029789767,0.00083735684,0.0005527207,0.0033099267,0.0023440989,0.0031940264,0.052157227],"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":[0.000034303488,0.000100137644,0.00072970625,0.000034060795,0.0000022944653,0.00006105422,0.00024197414,0.00004929147,0.0004114994,0.0009375773,0.97649837,0.020899704],"study_design_scores_gemma":[0.00001183169,0.000056666493,0.0021239633,0.000025916335,0.0000043206087,0.00006845905,0.00073021825,0.00029394668,0.0007461517,0.00017688877,0.9957457,0.000015931866],"about_ca_topic_score_codex":0.026562275,"about_ca_topic_score_gemma":0.0498905,"teacher_disagreement_score":0.07664671,"about_ca_system_score_codex":0.0014771249,"about_ca_system_score_gemma":0.0042633107,"threshold_uncertainty_score":0.2564088},"labels":[],"label_agreement":null},{"id":"W2095994713","doi":"","title":"The computational costs of recipient design and intention recognition in communication","year":2011,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":7,"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","keywords":"Task (project management); Inference; Computer science; Cognitive psychology; Psychology; Work (physics); Human–computer interaction; Artificial intelligence; Engineering","score_opus":0.03999759207546438,"score_gpt":0.21717338695062122,"score_spread":0.17717579487515683,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095994713","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35005066,0.0011418167,0.5508625,0.009136987,0.0002490525,0.00017782903,0.0002353355,0.0012219197,0.08692387],"genre_scores_gemma":[0.8976911,0.0005000366,0.09243703,0.00026005064,0.00009118396,0.000169933,0.00023619944,0.0002644302,0.008350022],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99272764,0.0042320653,0.00039476168,0.0009422262,0.0011944663,0.00050888583],"domain_scores_gemma":[0.9494761,0.04052648,0.0020087203,0.0062428727,0.0012143443,0.0005314182],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065252376,0.00072036864,0.00083168154,0.0010371559,0.0016565573,0.0068584885,0.0018082975,0.002980901,0.017523088],"category_scores_gemma":[0.053544294,0.0012528743,0.0013500244,0.0012132099,0.0047691893,0.014118364,0.005021543,0.0028499449,0.0025146334],"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":[0.0011408422,0.00030711503,0.007747953,0.000539025,0.00012202335,0.0006621549,0.003372978,0.04936388,0.010964073,0.6788471,0.0033379444,0.24359494],"study_design_scores_gemma":[0.00013672351,0.00023370801,0.008742443,0.000097730335,0.00018730568,0.0010681617,0.0015154263,0.28108296,0.009360204,0.6896062,0.007822563,0.00014665467],"about_ca_topic_score_codex":0.0021807752,"about_ca_topic_score_gemma":0.0014588666,"teacher_disagreement_score":0.017523088,"about_ca_system_score_codex":0.0016914585,"about_ca_system_score_gemma":0.0014473193,"threshold_uncertainty_score":0.058620572},"labels":[],"label_agreement":null},{"id":"W2100687392","doi":"10.1109/icassp.1987.1169435","title":"Pitch assignment rules for speech synthesis by word concatenation","year":2005,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Victoria","funders":"","keywords":"Concatenation (mathematics); Computer science; Stress (linguistics); Speech recognition; Pitch accent; Syllable; Word (group theory); Sentence; Natural language processing; Speech synthesis; Artificial intelligence; Vocabulary; Linguistics; Mathematics; Arithmetic; Prosody","score_opus":0.016023046106131526,"score_gpt":0.23986575824316256,"score_spread":0.22384271213703102,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2100687392","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":[0.0014312176,0.000113359085,0.9954732,0.000018009663,0.00004886103,0.00007165666,0.00005053778,0.0014300757,0.0013630432],"genre_scores_gemma":[0.038465098,0.00018919977,0.95830595,0.000044081622,0.0000613094,0.00022121126,0.00028203963,0.00071695255,0.0017141583],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9984151,0.0003261433,0.00027649396,0.00041311226,0.0004947268,0.0000743906],"domain_scores_gemma":[0.9982547,0.0009881844,0.00012803901,0.00024669553,0.00033595288,0.0000463965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016759232,0.0008311519,0.000901108,0.0008830383,0.00096441346,0.0017835278,0.0013542764,0.0006338699,0.005660131],"category_scores_gemma":[0.004508581,0.0006749745,0.0006497118,0.00063235115,0.0010703375,0.0011205192,0.0008784655,0.0014184066,0.0034978825],"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":[0.00037010442,0.000093138195,0.00076223246,0.00053450715,0.00010988784,0.00058116694,0.0007307236,0.055774793,0.08025506,0.10898668,0.007273339,0.7445283],"study_design_scores_gemma":[0.00017817256,0.00018679611,0.0006349646,0.00016830505,0.00018290087,0.0008612392,0.00014626948,0.6356576,0.13761073,0.12286243,0.10136256,0.00014805846],"about_ca_topic_score_codex":0.0013360103,"about_ca_topic_score_gemma":0.001584826,"teacher_disagreement_score":0.005660131,"about_ca_system_score_codex":0.00041839862,"about_ca_system_score_gemma":0.0007806642,"threshold_uncertainty_score":0.018934965},"labels":[],"label_agreement":null},{"id":"W2105269006","doi":"10.1145/1279540.1279552","title":"Multimodal multiplayer tabletop gaming","year":2007,"lang":"en","type":"article","venue":"Computers in entertainment","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":102,"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":"","keywords":"Gesture; Table (database); Computer science; Human–computer interaction; Utterance; Multimedia; Space (punctuation); Multimodal interaction; Speech recognition; Artificial intelligence; Database","score_opus":0.009624540675051162,"score_gpt":0.24197370626909853,"score_spread":0.23234916559404736,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105269006","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":[0.5556428,0.000908168,0.32428896,0.00031135618,0.00008783746,0.0010661738,0.0014584763,0.0059351274,0.11030112],"genre_scores_gemma":[0.91289663,0.00034133682,0.06328525,0.00012779285,0.000031853204,0.00049869204,0.0005145641,0.0001675826,0.022136232],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99966466,0.00007343979,0.000016957632,0.000089188856,0.00009818627,0.000057557474],"domain_scores_gemma":[0.9997435,0.000109494664,0.000012945248,0.00004666598,0.000045140932,0.000042156345],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022683326,0.0007922737,0.00032213633,0.0002780572,0.0002949574,0.0011946805,0.0005253254,0.00042768504,0.022423256],"category_scores_gemma":[0.00077687757,0.00016212031,0.0003557044,0.00017281016,0.0002502495,0.0007476642,0.0018030489,0.00025793607,0.0021256327],"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":[0.0022816644,0.0010225233,0.005777464,0.0010583454,0.0002031156,0.0014699466,0.0067462316,0.019567382,0.36895818,0.022730412,0.01691149,0.5532733],"study_design_scores_gemma":[0.00061742886,0.00621149,0.06982219,0.00059493294,0.00051336875,0.008202315,0.007870321,0.37810892,0.2501488,0.02437869,0.25292942,0.00060219393],"about_ca_topic_score_codex":0.0009926391,"about_ca_topic_score_gemma":0.0017925064,"teacher_disagreement_score":0.022423256,"about_ca_system_score_codex":0.00022258927,"about_ca_system_score_gemma":0.00012662313,"threshold_uncertainty_score":0.07501328},"labels":[],"label_agreement":null},{"id":"W2105649448","doi":"10.1109/isspa.2007.4555311","title":"Soft computing-based approach for natural language call routing systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; Learning vector quantization; Natural language; Natural language understanding; Artificial intelligence; Language model; Soft computing; Cache language model; Natural language processing; Vector quantization; Machine learning; Universal Networking Language; Artificial neural network; Comprehension approach","score_opus":0.015271891483466526,"score_gpt":0.2556043590638831,"score_spread":0.2403324675804166,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105649448","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013691109,0.00012384354,0.981768,0.00051638397,0.000033521363,0.00011357014,0.000038384005,0.00042694475,0.0032882032],"genre_scores_gemma":[0.5185276,0.00020226983,0.47480074,0.00029916072,0.00006562664,0.00039767922,0.00014517743,0.0000833141,0.005478388],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99904925,0.000359023,0.00006822246,0.00013184956,0.0003298206,0.000061871484],"domain_scores_gemma":[0.9984577,0.0009796345,0.00010306443,0.000114050476,0.00030515058,0.000040385057],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010158418,0.00042253084,0.0006051063,0.0008082345,0.00065133465,0.0017591404,0.0012058452,0.0010216322,0.0032968912],"category_scores_gemma":[0.0039993646,0.00023122474,0.0005140351,0.00070312264,0.0011842535,0.0016185343,0.0008052633,0.0011983744,0.00048711454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00009967582,0.0001888083,0.00069633435,0.00016066768,0.000052050746,0.00017525128,0.0002644888,0.7333294,0.0073983725,0.106336944,0.0018955733,0.14940238],"study_design_scores_gemma":[0.0000050235476,0.000010096472,0.000059945796,0.000004364376,0.000003596377,0.000012668003,0.000022224815,0.9751429,0.0011688857,0.022923386,0.00064218504,0.0000047113303],"about_ca_topic_score_codex":0.0043014376,"about_ca_topic_score_gemma":0.0047035594,"teacher_disagreement_score":0.0043014376,"about_ca_system_score_codex":0.001605297,"about_ca_system_score_gemma":0.0014960057,"threshold_uncertainty_score":0.011647344},"labels":[],"label_agreement":null},{"id":"W2105768841","doi":"10.5381/jot.2004.3.8.a3","title":"Generic Pipelined Multi-Agents Architecture for Multimedia Multimodal Software Environment.","year":2004,"lang":"en","type":"article","venue":"The Journal of Object Technology","topic":"Speech and dialogue systems","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":"École de Technologie Supérieure","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Flexibility (engineering); Architecture; Interface (matter); Computer architecture; Agent architecture; Reference architecture; Intelligent agent; Distributed computing; Software architecture; Embedded system; Human–computer interaction; Software; Artificial intelligence; Operating system","score_opus":0.016772939035008247,"score_gpt":0.24172728631913146,"score_spread":0.22495434728412322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2105768841","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":[0.008350647,0.00034191558,0.98332256,0.00013640469,0.000036983765,0.00012387235,0.000071882554,0.001354932,0.0062607997],"genre_scores_gemma":[0.29063928,0.0006604967,0.694465,0.00013000569,0.000024516683,0.00033471416,0.00033248082,0.00011062171,0.013302845],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99978644,0.000042267777,0.00001926013,0.000048125417,0.000069964,0.00003393239],"domain_scores_gemma":[0.99985254,0.000025826621,0.000014991785,0.00003439845,0.000045685858,0.00002654808],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004363315,0.0003907651,0.00024684917,0.00035344178,0.0004657011,0.0010663632,0.0011695321,0.00094616297,0.003331423],"category_scores_gemma":[0.0005491737,0.0002788284,0.0006071441,0.0002949875,0.0006377049,0.001171004,0.0009828939,0.0008023818,0.0009047234],"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":[0.00025791593,0.00012191844,0.0015334329,0.00051358424,0.00012868684,0.00090762356,0.0009216603,0.18840316,0.07086744,0.5609905,0.0064334064,0.16892073],"study_design_scores_gemma":[0.000033666023,0.00015500467,0.0005301526,0.00008208044,0.000086825865,0.00049945206,0.00008717433,0.8069556,0.019560948,0.094692506,0.07727089,0.000045796096],"about_ca_topic_score_codex":0.0023852456,"about_ca_topic_score_gemma":0.0041414523,"teacher_disagreement_score":0.003331423,"about_ca_system_score_codex":0.00083859963,"about_ca_system_score_gemma":0.0011555798,"threshold_uncertainty_score":0.011144698},"labels":[],"label_agreement":null},{"id":"W2106099507","doi":"10.1109/slt.2008.4777874","title":"Real-time speech recognition captioning of events and meetings","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer Research Institute of Montréal","funders":"","keywords":"Closed captioning; Computer science; Sentence; Speech recognition; Event (particle physics); Natural language processing; Selection (genetic algorithm); Shadow (psychology); Artificial intelligence; Multimedia; Image (mathematics)","score_opus":0.022350352932482873,"score_gpt":0.2208618410850236,"score_spread":0.19851148815254072,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106099507","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1736956,0.0012208964,0.7346227,0.0010956575,0.002190684,0.00093780836,0.007830809,0.03971551,0.038690373],"genre_scores_gemma":[0.6240859,0.00055764057,0.3387611,0.00044891643,0.000862974,0.0006330568,0.011280797,0.0018923498,0.021477195],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990823,0.00032325715,0.000054068078,0.0002362376,0.00022313454,0.00008090582],"domain_scores_gemma":[0.9973779,0.0010480635,0.00016845884,0.00040199517,0.00084070046,0.00016284033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009562652,0.001007354,0.00064828363,0.0006922771,0.0004921964,0.0011194508,0.00085451576,0.00095204747,0.015476954],"category_scores_gemma":[0.0046014665,0.00020812187,0.00041017367,0.00051135075,0.000441189,0.0012835939,0.0007042741,0.0008467876,0.0074852766],"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":[0.0026191587,0.00026663847,0.0015799804,0.0012454535,0.00011431529,0.0013322437,0.0017429348,0.025909076,0.31491607,0.006356182,0.07151684,0.5724011],"study_design_scores_gemma":[0.00015112504,0.000991539,0.012975158,0.0001293572,0.00012479778,0.0015061441,0.0010306761,0.4236408,0.43684325,0.006420646,0.11591119,0.00027543513],"about_ca_topic_score_codex":0.000731141,"about_ca_topic_score_gemma":0.0009273033,"teacher_disagreement_score":0.015476954,"about_ca_system_score_codex":0.0003908987,"about_ca_system_score_gemma":0.0003023585,"threshold_uncertainty_score":0.051775515},"labels":[],"label_agreement":null},{"id":"W2106657563","doi":"10.1109/robio.2010.5723431","title":"A modified approach of POMDP-based dialogue management","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Partially observable Markov decision process; Computer science; Artificial intelligence; Process management; Machine learning; Engineering; Markov chain; Markov model","score_opus":0.013869976176490755,"score_gpt":0.21602460964529124,"score_spread":0.2021546334688005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106657563","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":[0.002052766,0.000250104,0.9930091,0.00025126323,0.00009851797,0.00012696054,0.00006613901,0.0003359171,0.0038092053],"genre_scores_gemma":[0.19150159,0.00049982086,0.8015181,0.00026776007,0.00012429683,0.0005004893,0.00020037,0.00010135055,0.0052862386],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998376,0.0006103912,0.00009777367,0.00033456026,0.0004959261,0.00008529753],"domain_scores_gemma":[0.9993592,0.0002966882,0.00004040626,0.000104527964,0.00015105392,0.000048197708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011837116,0.0006102243,0.00074096944,0.00054631603,0.00067135144,0.0014354858,0.0018238808,0.00095313886,0.0034692874],"category_scores_gemma":[0.002182704,0.00032344452,0.00089911604,0.00047464925,0.0008981216,0.0017446564,0.0016848624,0.0014470222,0.0007589039],"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":[0.00025592808,0.0002796126,0.0007830562,0.00080981344,0.00017979127,0.0005225625,0.0016739167,0.22760232,0.019618401,0.36816198,0.0071787243,0.37293383],"study_design_scores_gemma":[0.00006731459,0.00017659776,0.00030593135,0.00007220754,0.00006838645,0.00021421911,0.00019446366,0.8310738,0.006617154,0.10672646,0.054409094,0.00007438749],"about_ca_topic_score_codex":0.0025591261,"about_ca_topic_score_gemma":0.0020056139,"teacher_disagreement_score":0.0034692874,"about_ca_system_score_codex":0.0007950804,"about_ca_system_score_gemma":0.001385408,"threshold_uncertainty_score":0.011605918},"labels":[],"label_agreement":null},{"id":"W2106989228","doi":"10.1017/s0890060406060112","title":"Design space and typed feature logic","year":2006,"lang":"en","type":"article","venue":"Artificial intelligence for engineering design analysis and manufacturing","topic":"Speech and dialogue systems","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":"Computer science; Context (archaeology); Grammar; Space (punctuation); Feature (linguistics); Programming language; Strengths and weaknesses; Natural language processing; Natural language; Artificial intelligence; Human–computer interaction; Linguistics; Epistemology; History; Philosophy","score_opus":0.03017141613535088,"score_gpt":0.23551431497914643,"score_spread":0.20534289884379556,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106989228","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":[0.030746577,0.00624775,0.8561215,0.006891197,0.00033327256,0.000055065102,0.00027649483,0.0008794361,0.098448694],"genre_scores_gemma":[0.73754674,0.0035015377,0.2186089,0.0017865899,0.00037284143,0.00016804301,0.00035767967,0.0002756156,0.037382033],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.998178,0.0006283789,0.00016543514,0.00028635186,0.0005177784,0.00022415457],"domain_scores_gemma":[0.9982368,0.0009489358,0.00013524364,0.00023847361,0.00033594682,0.00010460172],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002101798,0.00041781712,0.0003559313,0.0013507026,0.0011428164,0.003894654,0.0010710403,0.0012071052,0.0046238196],"category_scores_gemma":[0.0033004766,0.00037982877,0.0009334187,0.0014074289,0.0057546347,0.0070681516,0.0018472413,0.0017936272,0.00068974297],"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":[0.0000127809535,0.0000062183744,0.000090499976,0.000028125085,0.000004215929,0.000054810407,0.0001698217,0.001250857,0.00020620941,0.98706377,0.00086635945,0.010246253],"study_design_scores_gemma":[0.000009049802,0.000010723871,0.000034654277,0.000020552783,0.000005200241,0.00006968889,0.0000651187,0.0033977798,0.0003413432,0.9788817,0.017155953,0.000008211447],"about_ca_topic_score_codex":0.0042259535,"about_ca_topic_score_gemma":0.0023729855,"teacher_disagreement_score":0.0046238196,"about_ca_system_score_codex":0.0026231545,"about_ca_system_score_gemma":0.0015217628,"threshold_uncertainty_score":0.019032419},"labels":[],"label_agreement":null},{"id":"W2107237294","doi":"10.1145/1460096.1460112","title":"A critical assessment of spoken utterance retrieval through approximate lattice representations","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Utterance; Robustness (evolution); Computer science; Recall; Confusion; Lossy compression; Artificial intelligence; Natural language processing; Speech recognition; Precision and recall; Pattern recognition (psychology); Linguistics; Psychology","score_opus":0.048799445109376,"score_gpt":0.347358651681253,"score_spread":0.298559206571877,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107237294","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.38132852,0.010144687,0.5841939,0.0024303654,0.00031768167,0.00045262906,0.0013398121,0.005274845,0.014517638],"genre_scores_gemma":[0.8696224,0.0013195989,0.12345893,0.00026058842,0.00016968587,0.00015450708,0.001429175,0.00044084326,0.0031442211],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9854093,0.0073549803,0.0007378621,0.0018027867,0.004213086,0.0004820394],"domain_scores_gemma":[0.9337329,0.054335296,0.0013977382,0.0042482694,0.005722139,0.0005637362],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019082913,0.00148806,0.0017894948,0.0024851712,0.0011353262,0.005978961,0.0017783477,0.0027815546,0.0042668707],"category_scores_gemma":[0.12593032,0.00061628304,0.0005925394,0.0013154317,0.0023781564,0.008913991,0.003753154,0.0021419534,0.0021989578],"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":[0.00835425,0.00027621293,0.011636004,0.0011492085,0.0005692919,0.00026341985,0.0014351703,0.16141853,0.03906623,0.013811226,0.004367567,0.75765294],"study_design_scores_gemma":[0.0002714701,0.0023589984,0.011381319,0.00019592459,0.00044451028,0.00088407245,0.0015074024,0.87250006,0.08802173,0.016452296,0.0056595854,0.00032271646],"about_ca_topic_score_codex":0.006125318,"about_ca_topic_score_gemma":0.004354118,"teacher_disagreement_score":0.019082913,"about_ca_system_score_codex":0.0015885744,"about_ca_system_score_gemma":0.0014903339,"threshold_uncertainty_score":0.10092133},"labels":[],"label_agreement":null},{"id":"W2107241286","doi":"10.1007/11795018_25","title":"Representing and Querying Line Graphs in Natural Language: The iGraph System","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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":"Computer science; Natural language; Architecture; Natural (archaeology); Graph; Interface (matter); User interface; Human–computer interaction; Artificial intelligence; Natural language processing; World Wide Web; Theoretical computer science; Programming language","score_opus":0.009458823394421336,"score_gpt":0.22874835825665282,"score_spread":0.2192895348622315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2107241286","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":[0.02685479,0.0006863614,0.81421095,0.00058237015,0.000083408144,0.00016738512,0.0034851818,0.1472133,0.006716209],"genre_scores_gemma":[0.21350989,0.0009751377,0.75708723,0.00074749254,0.000085406755,0.0002190562,0.012651586,0.00797973,0.0067445724],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9993643,0.00018780872,0.000057063222,0.00017789904,0.00015152144,0.000061327366],"domain_scores_gemma":[0.9987771,0.00063231465,0.00006218686,0.00033883878,0.00010719176,0.00008238075],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009845218,0.0010287184,0.0013341417,0.0017477508,0.0007170475,0.003394642,0.003355427,0.0016206206,0.008671409],"category_scores_gemma":[0.0029551843,0.0007840314,0.0012011342,0.0018864251,0.0012804308,0.005785683,0.003044668,0.0011973411,0.0031851926],"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":[0.002019395,0.00062012736,0.0049291835,0.0014465399,0.0003038171,0.0013289454,0.0025093588,0.050523408,0.027329145,0.08448556,0.14346501,0.68103945],"study_design_scores_gemma":[0.0005626386,0.0002310927,0.0011302828,0.00024636218,0.00028671086,0.0006867297,0.0010267706,0.6581615,0.03686886,0.19791457,0.10272158,0.00016294685],"about_ca_topic_score_codex":0.010532474,"about_ca_topic_score_gemma":0.012483795,"teacher_disagreement_score":0.010532474,"about_ca_system_score_codex":0.0008483443,"about_ca_system_score_gemma":0.0010092994,"threshold_uncertainty_score":0.029008746},"labels":[],"label_agreement":null},{"id":"W2108703806","doi":"10.1145/2468356.2468803","title":"We need to talk","year":2013,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Toronto; National Research Council Canada; Research and Productivity Council","funders":"","keywords":"Computer science; Usability; Leverage (statistics); Natural language; Human–computer interaction; Natural (archaeology); Domain (mathematical analysis); Spoken language; Perception; Speech community; Natural language understanding; Speech processing; Natural language processing; Artificial intelligence; Linguistics; Psychology","score_opus":0.013905340738127624,"score_gpt":0.21724788895085348,"score_spread":0.20334254821272585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2108703806","genre_codex":"commentary","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":[0.0031014904,0.014706352,0.0077718827,0.51821303,0.09412133,0.00014545592,0.000481544,0.0012095986,0.36024922],"genre_scores_gemma":[0.042263802,0.007513598,0.003616005,0.34621397,0.015749061,0.00020632269,0.0005209875,0.0011109208,0.5828053],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9957847,0.0015077546,0.00016721193,0.00069294265,0.0011348798,0.00071250973],"domain_scores_gemma":[0.9932508,0.0016408177,0.00033805528,0.0008680591,0.0020902178,0.0018121062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004214109,0.0013716167,0.001044563,0.0011802044,0.01040855,0.0129605485,0.0019586121,0.008109065,0.13538395],"category_scores_gemma":[0.017997516,0.0004711443,0.0010540808,0.0006892886,0.010232899,0.021367956,0.008978642,0.016579513,0.12211631],"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":[0.000066176224,0.00005388767,0.0006027681,0.00023393144,0.000020264692,0.0004748682,0.011285651,0.00004078465,0.0005549408,0.119794086,0.8191571,0.04771551],"study_design_scores_gemma":[0.0000048636703,0.000013052527,0.000107221094,0.00016167083,0.000005410542,0.00029119602,0.0061977743,0.000019657125,0.00009103555,0.013798167,0.97929364,0.00001635746],"about_ca_topic_score_codex":0.0037773098,"about_ca_topic_score_gemma":0.0038837534,"teacher_disagreement_score":0.13538395,"about_ca_system_score_codex":0.0027575411,"about_ca_system_score_gemma":0.0038292555,"threshold_uncertainty_score":0.4529044},"labels":[],"label_agreement":null},{"id":"W2110664110","doi":"10.3115/1596324.1596335","title":"Fast mapping in word learning","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; Referent; Natural language processing; Context (archaeology); Word (group theory); Artificial intelligence; Probabilistic logic; Selection (genetic algorithm); Interpretation (philosophy); Meaning (existential); Context model; Speech recognition; Machine learning; Linguistics; Psychology","score_opus":0.028130499702613315,"score_gpt":0.21377149452496927,"score_spread":0.18564099482235596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2110664110","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43326527,0.00086145714,0.5465337,0.0015351694,0.000070669455,0.00008002372,0.00014443569,0.00041263158,0.01709659],"genre_scores_gemma":[0.9451354,0.00041464673,0.051268075,0.00013069724,0.00002958876,0.00008862642,0.00008975933,0.000082481856,0.0027606008],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","domain_scores_codex":[0.99798715,0.0011145774,0.00005269655,0.00041546382,0.00031100886,0.00011907853],"domain_scores_gemma":[0.992679,0.005624563,0.0004414816,0.0007365486,0.00032731,0.00019108909],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026794116,0.0005116077,0.00053432555,0.0006741648,0.0005346526,0.002042931,0.0011376245,0.0015159601,0.0030439212],"category_scores_gemma":[0.016588394,0.0007242496,0.0009126784,0.00054885604,0.0034497462,0.0074424674,0.001976406,0.002146895,0.00053545076],"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":[0.00026021284,0.0001701105,0.009041246,0.000280252,0.00009971644,0.00052502897,0.0027768018,0.1872641,0.010461287,0.72204924,0.0010237333,0.0660483],"study_design_scores_gemma":[0.000047748345,0.00014496766,0.0022119563,0.000024489038,0.000016079981,0.00040994628,0.0002133249,0.23848867,0.0035031626,0.7529185,0.001976007,0.00004527989],"about_ca_topic_score_codex":0.0021244558,"about_ca_topic_score_gemma":0.0010999873,"teacher_disagreement_score":0.0030439212,"about_ca_system_score_codex":0.0010718349,"about_ca_system_score_gemma":0.0007896289,"threshold_uncertainty_score":0.014170229},"labels":[],"label_agreement":null},{"id":"W2111293753","doi":"10.1080/09588220802343421","title":"Modeling learner variability in CALL","year":2008,"lang":"en","type":"article","venue":"Computer Assisted Language Learning","topic":"Speech and dialogue systems","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":"Simon Fraser University","funders":"","keywords":"Computer science; Interlanguage; Dynamism; TUTOR; Language acquisition; Natural language processing; Artificial intelligence; Process (computing); Linguistics; Programming language","score_opus":0.020188695573617015,"score_gpt":0.23909398132972987,"score_spread":0.21890528575611284,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111293753","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46790865,0.00032090934,0.5216567,0.0006343198,0.000051826482,0.00012147528,0.00066509313,0.0013215424,0.007319448],"genre_scores_gemma":[0.98275834,0.000060504182,0.015712775,0.000045235574,0.000019316862,0.00008132415,0.00027114543,0.00010473445,0.0009466342],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99422294,0.0024585014,0.00023642812,0.0013495708,0.0013627472,0.00036976053],"domain_scores_gemma":[0.9769304,0.01567578,0.0017360435,0.0032034768,0.001816577,0.00063781627],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0070523266,0.00046224784,0.0008440965,0.0011477525,0.0006342859,0.003382026,0.0015700145,0.0011092938,0.0013456611],"category_scores_gemma":[0.031962685,0.00028648484,0.0006162106,0.0011127827,0.00092572125,0.003522088,0.0027413773,0.0014783082,0.00044363164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006195204,0.00033416844,0.11501794,0.00013352798,0.00023968414,0.00048724315,0.0042599,0.7046659,0.004082922,0.05477391,0.0020462384,0.113339],"study_design_scores_gemma":[0.000013540739,0.000074758995,0.008466834,0.000018571258,0.000040278406,0.0001122274,0.00038608938,0.9566292,0.0012600395,0.030503357,0.0024492072,0.00004591309],"about_ca_topic_score_codex":0.0044212467,"about_ca_topic_score_gemma":0.0034419145,"teacher_disagreement_score":0.0070523266,"about_ca_system_score_codex":0.0015468023,"about_ca_system_score_gemma":0.0016420432,"threshold_uncertainty_score":0.037296772},"labels":[],"label_agreement":null},{"id":"W2111297944","doi":"10.1145/1753326.1753480","title":"Where are you pointing?","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Saskatchewan","funders":"","keywords":"Deixis; Gesture; Conversation; Computer science; Point (geometry); Natural (archaeology); Human–computer interaction; Artificial intelligence; Communication; Psychology; Linguistics","score_opus":0.0084490204895194,"score_gpt":0.21798397118046914,"score_spread":0.20953495069094974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111297944","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":[0.16749957,0.077447,0.044689465,0.23189753,0.0166502,0.00030565594,0.005711807,0.0041513876,0.45164734],"genre_scores_gemma":[0.5311692,0.04643766,0.01993803,0.037707742,0.002127155,0.000332178,0.0032929685,0.00072830805,0.3582667],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989429,0.00047525088,0.00007750463,0.0001843492,0.0001687449,0.00015124824],"domain_scores_gemma":[0.9973309,0.0009162964,0.00039881587,0.00016934454,0.00077826163,0.0004064013],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018935412,0.00077243336,0.0005507331,0.0011714369,0.0023890508,0.0030989395,0.00046587453,0.001987429,0.059945825],"category_scores_gemma":[0.01271132,0.00025450898,0.00046282276,0.0009131282,0.0010781669,0.004260437,0.0010443566,0.0018631234,0.046971533],"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":[0.0005322198,0.00013080263,0.034918178,0.00084785814,0.000082160535,0.0016202573,0.026674718,0.00012351625,0.0019774912,0.023807837,0.5054163,0.4038687],"study_design_scores_gemma":[0.00003960991,0.00016088084,0.025525259,0.0012697723,0.00007231151,0.0073950295,0.036928367,0.00042906753,0.0012704161,0.014221549,0.91252154,0.00016617622],"about_ca_topic_score_codex":0.003225753,"about_ca_topic_score_gemma":0.0055989893,"teacher_disagreement_score":0.059945825,"about_ca_system_score_codex":0.00086182484,"about_ca_system_score_gemma":0.00066943216,"threshold_uncertainty_score":0.20053875},"labels":[],"label_agreement":null},{"id":"W2112476714","doi":"10.1109/icassp.2011.5946754","title":"Bayesian reinforcement learning for POMDP-based dialogue systems","year":2011,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Reinforcement learning; Computer science; Partially observable Markov decision process; Robustness (evolution); Artificial intelligence; Machine learning; Bayesian probability; Popularity; Domain (mathematical analysis); Markov chain","score_opus":0.03669384001913174,"score_gpt":0.23138962003827437,"score_spread":0.19469578001914262,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2112476714","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045792386,0.00023295393,0.9926287,0.00020105261,0.000027017291,0.000040077713,0.00003829304,0.00029620653,0.0019563637],"genre_scores_gemma":[0.71186864,0.0005692958,0.2830317,0.00017406126,0.000087659326,0.00040142686,0.00021467621,0.00016553712,0.003487017],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983966,0.0007288962,0.00008100928,0.00022474161,0.0004331851,0.0001355379],"domain_scores_gemma":[0.9966363,0.0025557387,0.00022275664,0.00014302725,0.00029882905,0.00014331986],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002632847,0.0009569351,0.0015200495,0.00048960315,0.00065234664,0.0013453907,0.0014536295,0.0012212069,0.0030364548],"category_scores_gemma":[0.009550112,0.0007532821,0.00082123873,0.00045889738,0.0019049604,0.0017308095,0.0018602933,0.002372501,0.00050874025],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000044295917,0.000025948479,0.00019417609,0.00007436098,0.000024540035,0.000047712354,0.00006898108,0.94895697,0.00044656728,0.036827665,0.00046664546,0.012822199],"study_design_scores_gemma":[0.000009037608,0.000007004667,0.000019444256,0.0000043920622,0.0000027657811,0.000004242177,0.0000037366274,0.98508704,0.00008846107,0.01450671,0.0002634334,0.000003663935],"about_ca_topic_score_codex":0.009810604,"about_ca_topic_score_gemma":0.008466557,"teacher_disagreement_score":0.009810604,"about_ca_system_score_codex":0.0020918488,"about_ca_system_score_gemma":0.0021616379,"threshold_uncertainty_score":0.01950699},"labels":[],"label_agreement":null},{"id":"W2113651401","doi":"10.1145/2362724.2362735","title":"Human question answering performance using an interactive document retrieval system","year":2012,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency","keywords":"Question answering; Computer science; Information retrieval; Document retrieval; Human–computer information retrieval; World Wide Web; Search engine","score_opus":0.029607982171155126,"score_gpt":0.2972875870218249,"score_spread":0.2676796048506698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113651401","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":[0.9787243,0.00092314056,0.011142143,0.00017881258,0.000055151868,0.00019253198,0.0004478749,0.0013662443,0.0069696694],"genre_scores_gemma":[0.9887057,0.00019257635,0.007950667,0.0001370722,0.00004027729,0.00010386872,0.00057999545,0.000093504896,0.0021963264],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99302727,0.0035884273,0.0007073941,0.0011734125,0.0011722749,0.00033117103],"domain_scores_gemma":[0.94135255,0.04756584,0.0015615005,0.0032390312,0.005090041,0.0011910248],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006240576,0.00064595,0.00082031306,0.0010852469,0.0005450519,0.0019380398,0.0007244046,0.0016272274,0.0045251334],"category_scores_gemma":[0.03296662,0.00022541636,0.00044304293,0.0007212775,0.00049618894,0.0014651555,0.0009985432,0.0005761646,0.002088635],"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":[0.015363625,0.0043997383,0.122948416,0.0030337344,0.0013691774,0.00092417316,0.026629137,0.01872773,0.24504541,0.0024473933,0.017645666,0.54146576],"study_design_scores_gemma":[0.0015331908,0.03337198,0.40684974,0.0004329063,0.0017653734,0.003494996,0.008381955,0.21946667,0.26946467,0.0032974398,0.0507218,0.0012192576],"about_ca_topic_score_codex":0.0038224421,"about_ca_topic_score_gemma":0.0017716637,"teacher_disagreement_score":0.006240576,"about_ca_system_score_codex":0.000452965,"about_ca_system_score_gemma":0.00046004597,"threshold_uncertainty_score":0.033003688},"labels":[],"label_agreement":null},{"id":"W2113817270","doi":"10.1109/iit.2007.4430395","title":"Using Text-to-Speech Engine to Improve the Accuracy of a Speech-Enabled Interface","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Institut National de la Recherche Scientifique; Université de Moncton","funders":"","keywords":"Computer science; Speech analytics; Speech recognition; Interface (matter); Speech synthesis; User interface; Natural language processing; Speech corpus; Artificial intelligence; Operating system","score_opus":0.027466686289673165,"score_gpt":0.3007159662487276,"score_spread":0.27324927995905446,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2113817270","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22774896,0.0010914154,0.6838035,0.00029698503,0.0004743805,0.00024184605,0.00036864317,0.07934106,0.0066332147],"genre_scores_gemma":[0.5379764,0.00037873624,0.4473254,0.00043879755,0.00013690049,0.000096422606,0.0011643044,0.0018341272,0.010648874],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99841285,0.0002820228,0.00019163993,0.00036591536,0.0006111523,0.00013634766],"domain_scores_gemma":[0.9953798,0.002291988,0.00015721198,0.0005272019,0.0015224152,0.000121347366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001854419,0.001168979,0.0010395572,0.0011111335,0.00040097558,0.0014333983,0.0016120641,0.0013171956,0.0064229425],"category_scores_gemma":[0.007185255,0.00043502508,0.00041620078,0.00047440775,0.00023737598,0.002593407,0.0007739338,0.000925735,0.006414656],"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":[0.0015443997,0.00045075058,0.003550876,0.00037130527,0.00015897828,0.0003959685,0.00030975294,0.0049016858,0.285864,0.00092809903,0.005993867,0.6955303],"study_design_scores_gemma":[0.000119030745,0.00066220557,0.005765244,0.000038957445,0.00029962306,0.0011081236,0.000097565564,0.2938492,0.6845095,0.0005421764,0.012871536,0.00013677665],"about_ca_topic_score_codex":0.0026463517,"about_ca_topic_score_gemma":0.00222196,"teacher_disagreement_score":0.0064229425,"about_ca_system_score_codex":0.0003259811,"about_ca_system_score_gemma":0.0004218016,"threshold_uncertainty_score":0.021486878},"labels":[],"label_agreement":null},{"id":"W2114041930","doi":"10.1007/s11049-010-9104-2","title":"Biases in Harmonic Grammar: the road to restrictive learning","year":2010,"lang":"en","type":"article","venue":"Natural Language & Linguistic Theory","topic":"Speech and dialogue systems","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":"Markedness; Learnability; Optimality theory; Constraint (computer-aided design); Grammar; Computer science; Variety (cybernetics); Ranking (information retrieval); Rule-based machine translation; Linguistics; Weighting; Linguistic universal; Philosophy of language; Artificial intelligence; Mathematics; Natural language processing; Phonology","score_opus":0.008639937890571612,"score_gpt":0.26461463338747626,"score_spread":0.25597469549690466,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114041930","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3202023,0.0017140711,0.5392035,0.033645336,0.0003522499,0.00006250343,0.00051325175,0.0009254943,0.10338131],"genre_scores_gemma":[0.9690642,0.00040716171,0.024507664,0.0014414183,0.0002839786,0.000043451666,0.00022922666,0.0003811628,0.0036417944],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9964259,0.0018515692,0.00012586541,0.00068646285,0.00064835505,0.0002618164],"domain_scores_gemma":[0.96468353,0.022617985,0.0009806447,0.008030702,0.002620725,0.0010665196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00629563,0.00031752634,0.00082691805,0.00079654885,0.001333323,0.0043251337,0.0020626178,0.0018756371,0.007768419],"category_scores_gemma":[0.049704153,0.00070158776,0.00043731375,0.00083344034,0.012433822,0.011382112,0.004391778,0.00638325,0.0010284984],"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":[0.000090602625,0.000043298085,0.0055811424,0.00006953744,0.00003564648,0.00007515779,0.0025494073,0.002256657,0.0018888118,0.9312579,0.0029750583,0.053176753],"study_design_scores_gemma":[0.0000061963137,0.0000051900615,0.00071107177,0.000007963724,0.0000036999913,0.000033516448,0.00017625371,0.002743674,0.00027891312,0.994635,0.0013889406,0.000009656354],"about_ca_topic_score_codex":0.0022694233,"about_ca_topic_score_gemma":0.0020202834,"teacher_disagreement_score":0.007768419,"about_ca_system_score_codex":0.0011091031,"about_ca_system_score_gemma":0.0011078233,"threshold_uncertainty_score":0.033294916},"labels":[],"label_agreement":null},{"id":"W2115667691","doi":"10.21307/ijssis-2017-283","title":"Human-Computer Interaction: Overview on State of the Art","year":2008,"lang":"en","type":"article","venue":"International Journal on Smart Sensing and Intelligent Systems","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":409,"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":"Terminology; Computer science; Field (mathematics); Human–computer interaction; Subject (documents); Multimodal interaction; Data science; World Wide Web; Mathematics; Linguistics","score_opus":0.057926344091643586,"score_gpt":0.29601510955095595,"score_spread":0.23808876545931235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115667691","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":[0.0003534618,0.989518,0.0025181824,0.0006017538,0.00037544983,0.000020276757,0.000044474997,0.00005833619,0.0065100146],"genre_scores_gemma":[0.0059191515,0.98682654,0.0035886082,0.00063774816,0.0009132969,0.000051929095,0.00016486247,0.000030167106,0.0018676531],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997804,0.00051579723,0.00029334635,0.00047180426,0.0007526293,0.00016254227],"domain_scores_gemma":[0.9959643,0.0025523223,0.00019162992,0.00015920957,0.00096907886,0.00016347639],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026391654,0.001210646,0.0016371312,0.009137222,0.0007998812,0.006373845,0.002136757,0.0029671127,0.008178077],"category_scores_gemma":[0.0031336453,0.0010069117,0.0009888051,0.010320766,0.0014997785,0.007961961,0.0020333738,0.0025848646,0.0049162386],"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":[0.0001278768,0.00012504912,0.0004957377,0.01513425,0.0000701268,0.00008499468,0.00021191349,0.0011259316,0.001314909,0.021537641,0.02307528,0.9366963],"study_design_scores_gemma":[0.000013846722,0.00023967614,0.0018666184,0.018909078,0.00011436802,0.00068436447,0.00043515646,0.0019843937,0.0009902689,0.015143292,0.95953214,0.00008684726],"about_ca_topic_score_codex":0.0028114524,"about_ca_topic_score_gemma":0.0018453291,"teacher_disagreement_score":0.009137222,"about_ca_system_score_codex":0.0014400937,"about_ca_system_score_gemma":0.0017098042,"threshold_uncertainty_score":0.027358413},"labels":[],"label_agreement":null},{"id":"W21176108","doi":"10.1111/j.1742-7843.2010.00655.x","title":"Topic Segmentation : A First Stage to Dialog-Based Information Extraction.","year":2001,"lang":"en","type":"article","venue":"NLPRS","topic":"Speech and dialogue systems","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":"Université de Montréal","funders":"","keywords":"Segmentation; Computer science; Dialog box; Information extraction; Artificial intelligence; Natural language processing; Hidden Markov model; Speech recognition; World Wide Web","score_opus":0.015602393950015721,"score_gpt":0.25592303165491265,"score_spread":0.24032063770489692,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W21176108","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.021030432,0.007569425,0.8798203,0.0013737079,0.00077509606,0.0022113412,0.024383405,0.05175575,0.0110804355],"genre_scores_gemma":[0.15527076,0.00209731,0.78466713,0.00038402766,0.0007642869,0.0013286092,0.04438111,0.0014956685,0.009611067],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99738353,0.0006217832,0.0002978571,0.0008778066,0.0005085934,0.0003103871],"domain_scores_gemma":[0.9972144,0.0014238191,0.00015838818,0.00039060466,0.0006004698,0.00021245779],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030878522,0.0030027367,0.0021051262,0.011139002,0.0020899265,0.0037337097,0.0024986928,0.002670517,0.013715159],"category_scores_gemma":[0.005537625,0.0008360325,0.0027939393,0.005864418,0.00060438615,0.0051759155,0.0030785745,0.0019187187,0.011950588],"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":[0.00080177607,0.00038013514,0.0041049784,0.0018569404,0.00040088058,0.0005268946,0.0012071634,0.0026694257,0.030709624,0.005175165,0.05552555,0.8966414],"study_design_scores_gemma":[0.0002363291,0.0012732985,0.02423609,0.0009298821,0.0013861097,0.0025789372,0.006205135,0.5532376,0.084150806,0.054741707,0.27058527,0.00043875683],"about_ca_topic_score_codex":0.006231713,"about_ca_topic_score_gemma":0.008846205,"teacher_disagreement_score":0.013715159,"about_ca_system_score_codex":0.0011466864,"about_ca_system_score_gemma":0.0026784865,"threshold_uncertainty_score":0.04588175},"labels":[],"label_agreement":null},{"id":"W2120339397","doi":"10.2991/icaicte.2013.96","title":"An I-POMDP Based Multi-Agent Architecture for Dialogue Tutoring","year":2013,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Guelph","funders":"","keywords":"Partially observable Markov decision process; Computer science; Reinforcement learning; Architecture; Artificial intelligence; Process (computing); Markov decision process; Human–computer interaction; Markov process; Machine learning; Markov chain; Markov model; Programming language","score_opus":0.02735021883052694,"score_gpt":0.25875876282157106,"score_spread":0.23140854399104413,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2120339397","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009279782,0.00018078208,0.9839495,0.00031523994,0.000084915126,0.000104943225,0.00004461223,0.0011610813,0.0048792385],"genre_scores_gemma":[0.6096487,0.00030798747,0.3826905,0.00019912396,0.000051882307,0.00046348048,0.0001263637,0.000075725686,0.0064361333],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99962044,0.0001283959,0.00002695799,0.00009299118,0.00008632926,0.000044918437],"domain_scores_gemma":[0.99967325,0.00012569982,0.000028970186,0.000031540578,0.00008750876,0.00005314198],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007377766,0.0005448125,0.000647302,0.00021058509,0.0006801189,0.00092421257,0.0016416134,0.0010919513,0.0037508707],"category_scores_gemma":[0.0013476035,0.00035529293,0.000576136,0.00021163479,0.000689489,0.0008870274,0.0013174033,0.0016076304,0.00074587436],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017572299,0.00017600592,0.00080415834,0.00020265269,0.00008219171,0.00031607776,0.00033514062,0.85192454,0.010855031,0.046691872,0.0027360802,0.085700504],"study_design_scores_gemma":[0.00002415241,0.00004767933,0.00005393946,0.0000065011714,0.000010069096,0.000022884342,0.000011279928,0.99198055,0.00096759934,0.004833097,0.0020334972,0.00000890923],"about_ca_topic_score_codex":0.0054050745,"about_ca_topic_score_gemma":0.005380514,"teacher_disagreement_score":0.0054050745,"about_ca_system_score_codex":0.00076010247,"about_ca_system_score_gemma":0.0016328519,"threshold_uncertainty_score":0.012547851},"labels":[],"label_agreement":null},{"id":"W2124326526","doi":"10.1109/icassp.2011.5947634","title":"A conditional model for triggering understanding actions in a speech understanding system","year":2011,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Dialog box; Recall; Computer science; Frame (networking); Speech recognition; Artificial intelligence; Precision and recall; Natural language processing; Cognitive psychology; Psychology","score_opus":0.3893734030093067,"score_gpt":0.2960936975568439,"score_spread":0.09327970545246278,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2124326526","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060297847,0.00015560185,0.93118334,0.00035256433,0.00007356717,0.00009008035,0.0005591469,0.0051247347,0.0021630672],"genre_scores_gemma":[0.8764127,0.0001403774,0.118602335,0.00012544575,0.000058767266,0.00019014264,0.0009865718,0.00030410552,0.003179541],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9987048,0.00039676068,0.00007524066,0.00038105738,0.00025547072,0.00018666551],"domain_scores_gemma":[0.9954436,0.003097995,0.00031823764,0.00045149965,0.00050680706,0.00018188366],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017455951,0.0010223566,0.00067212636,0.0006684981,0.00047430166,0.00129899,0.0016719,0.0013312617,0.0038013726],"category_scores_gemma":[0.006124325,0.00063597417,0.0009392604,0.00030690274,0.0009691571,0.0019636406,0.0012537434,0.0017399581,0.0012245668],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0020508394,0.0003832468,0.008018685,0.0003665888,0.0002374132,0.0010650152,0.000915526,0.71110564,0.06431824,0.05780572,0.0054734335,0.14825967],"study_design_scores_gemma":[0.000015021059,0.000059084723,0.0005376879,0.000008923352,0.000039539722,0.000067896,0.000013449827,0.9860175,0.0057186657,0.006962546,0.0005347885,0.000024818595],"about_ca_topic_score_codex":0.008193418,"about_ca_topic_score_gemma":0.008503456,"teacher_disagreement_score":0.008193418,"about_ca_system_score_codex":0.0010269309,"about_ca_system_score_gemma":0.0017264944,"threshold_uncertainty_score":0.0162915},"labels":[],"label_agreement":null},{"id":"W2126620235","doi":"","title":"Dialogue Systems for Language Learning","year":2013,"lang":"es","type":"article","venue":"IE Comunicaciones: Revista Iberoamericana de Informática Educativa","topic":"Speech and dialogue systems","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":"Western University; University of Waterloo","funders":"","keywords":"Computer science; Dialog box; Conversation; Language industry; Grammar; Foreign language; Comprehension approach; Vocabulary; Natural language; Natural language processing; Universal Networking Language; Language technology; Language acquisition; Bridging (networking); Linguistics; Artificial intelligence; World Wide Web","score_opus":0.015747657581840286,"score_gpt":0.2756735919831672,"score_spread":0.25992593440132694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2126620235","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0065093534,0.084046476,0.7545232,0.012125995,0.0034977393,0.0003414968,0.00064665003,0.0026002042,0.13570885],"genre_scores_gemma":[0.420925,0.043353893,0.458015,0.0032519095,0.0046478817,0.0012191335,0.0019082163,0.000788712,0.06589015],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9972613,0.0014614254,0.00019379462,0.00047606643,0.000461,0.00014646226],"domain_scores_gemma":[0.9973272,0.0018191173,0.00011874721,0.00036306126,0.0002510924,0.00012072515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024800496,0.00094413635,0.0009173222,0.0013716709,0.0016260342,0.0064698434,0.0013965726,0.0028076037,0.017177176],"category_scores_gemma":[0.0057869563,0.00041980777,0.00078118744,0.0012643189,0.0038145864,0.0075159073,0.003788424,0.002736575,0.0041703633],"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":[0.000050314324,0.000035996865,0.00020209549,0.0005125355,0.000037733316,0.00015479766,0.0011042714,0.0030578433,0.0010755251,0.8817616,0.012766953,0.099240325],"study_design_scores_gemma":[0.000030075744,0.000047115587,0.00020864484,0.00029406036,0.000025809211,0.00032897742,0.00046065703,0.017449914,0.00075419026,0.7184052,0.26195547,0.0000400117],"about_ca_topic_score_codex":0.0020581558,"about_ca_topic_score_gemma":0.0010763356,"teacher_disagreement_score":0.017177176,"about_ca_system_score_codex":0.0018071781,"about_ca_system_score_gemma":0.0010845006,"threshold_uncertainty_score":0.057463348},"labels":[],"label_agreement":null},{"id":"W2127550634","doi":"10.1016/j.concog.2004.05.008","title":"Opposition logic and neural network models in artificial grammar learning","year":2004,"lang":"en","type":"article","venue":"Consciousness and Cognition","topic":"Speech and dialogue systems","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 Lethbridge","funders":"","keywords":"Opposition (politics); Artificial neural network; Psychology; Cognitive science; Artificial intelligence; Grammar; Cognitive psychology; Computer science; Linguistics; Philosophy; Political science","score_opus":0.024860767113314745,"score_gpt":0.22988212860430762,"score_spread":0.20502136149099287,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127550634","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11364368,0.0052983514,0.8345866,0.009179821,0.00039896436,0.00003609132,0.00017133847,0.00023518031,0.036449946],"genre_scores_gemma":[0.91647583,0.0020776836,0.07152848,0.0003874499,0.00042463292,0.00008396477,0.00012638983,0.00006948813,0.0088260425],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99923754,0.0005118125,0.000028823244,0.00007137856,0.00009992945,0.00005055912],"domain_scores_gemma":[0.9947214,0.004724002,0.00013910505,0.0001276546,0.00019148133,0.000096323085],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021784264,0.00042474284,0.000791294,0.0008805681,0.00050008175,0.0021881047,0.0014593829,0.00178861,0.005318185],"category_scores_gemma":[0.009596871,0.0004768633,0.00070842035,0.00095137337,0.0028301629,0.0051625883,0.0010594442,0.002343353,0.00039758554],"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":[0.00006892165,0.000035668683,0.0003046876,0.00006787616,0.000034797427,0.000058704,0.00013705948,0.092358485,0.00031513534,0.89437246,0.0007930485,0.011453071],"study_design_scores_gemma":[0.00000905719,0.0000050435815,0.00004500524,0.000004405606,0.0000038316816,0.000008475247,0.000011388509,0.18728203,0.00005356021,0.81218624,0.0003862688,0.0000046870873],"about_ca_topic_score_codex":0.0033489433,"about_ca_topic_score_gemma":0.0025912665,"teacher_disagreement_score":0.005318185,"about_ca_system_score_codex":0.00147834,"about_ca_system_score_gemma":0.00077944295,"threshold_uncertainty_score":0.017791152},"labels":[],"label_agreement":null},{"id":"W2127666915","doi":"10.1155/s1110865704402212","title":"Generic Multimedia Multimodal Agents Paradigms and Their Dynamic Reconfiguration at the Architectural Level","year":2004,"lang":"en","type":"article","venue":"EURASIP Journal on Advances in Signal Processing","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control reconfiguration; Computer science; Adaptation (eye); Architecture; Dialog box; Distributed computing; Intelligent agent; Human–computer interaction; Computer architecture; Multimedia; Artificial intelligence; Embedded system; World Wide Web","score_opus":0.028347314156366304,"score_gpt":0.28154152841324137,"score_spread":0.25319421425687505,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2127666915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049966183,0.0007359794,0.9341487,0.00030474688,0.000047963378,0.00013192717,0.000055695506,0.0007445654,0.013864205],"genre_scores_gemma":[0.5034579,0.0009413,0.48636457,0.00018110011,0.000043370943,0.0003806625,0.00019265995,0.00009971726,0.008338676],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995542,0.00015117391,0.00004071092,0.00009128894,0.000107349864,0.000055183667],"domain_scores_gemma":[0.9996165,0.00006304766,0.000058231693,0.0001415406,0.000080590515,0.000040046874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007430543,0.00050862995,0.00025536455,0.00040555716,0.0004983855,0.0012879935,0.0010145038,0.0010210065,0.001331781],"category_scores_gemma":[0.00094791665,0.00025966528,0.00058936526,0.00031772742,0.0011341689,0.0018953445,0.0011601262,0.0008721444,0.00041529894],"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":[0.00016834018,0.00008515565,0.0016882234,0.00031429727,0.00009874309,0.00073119596,0.0014915444,0.12522423,0.06847262,0.67139643,0.0028801945,0.12744905],"study_design_scores_gemma":[0.00004353069,0.00018699735,0.0014406712,0.000086129636,0.00011797971,0.000766568,0.00048481175,0.64835626,0.034807444,0.24031234,0.07332885,0.00006838314],"about_ca_topic_score_codex":0.0009830527,"about_ca_topic_score_gemma":0.0014752025,"teacher_disagreement_score":0.001331781,"about_ca_system_score_codex":0.0007071037,"about_ca_system_score_gemma":0.000476078,"threshold_uncertainty_score":0.00513041},"labels":[],"label_agreement":null},{"id":"W2133225641","doi":"10.14288/1.0086923","title":"The effects of noise on identification of topic changes in discourse","year":2009,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Active listening; Noise (video); Identification (biology); Discourse analysis; Acoustics; Background noise; Psychology; Speech recognition; Computer science; Linguistics; Communication; Artificial intelligence; Physics; Biology","score_opus":0.005014699583258378,"score_gpt":0.18281521461449565,"score_spread":0.17780051503123728,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2133225641","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":[0.9974843,0.00025729244,0.0010791874,0.000018108265,0.000011805702,0.000018581888,0.000024708403,0.000021558904,0.0010843796],"genre_scores_gemma":[0.99784744,0.0002507382,0.0011201212,0.000032302745,0.00003465248,0.000024344774,0.00008344994,0.000023107625,0.0005839108],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991774,0.00035911816,0.00007007391,0.00014787429,0.00017559619,0.00006998469],"domain_scores_gemma":[0.9898617,0.007943554,0.00085078645,0.00029517894,0.00065790786,0.0003909531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011038623,0.00043979412,0.00034963636,0.0005209101,0.00035042738,0.0008069524,0.00017219073,0.0005121134,0.001938967],"category_scores_gemma":[0.0109116845,0.00024475312,0.00018160293,0.00012362577,0.0005771118,0.00060797017,0.0006949003,0.00030933678,0.00054529094],"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":[0.014161642,0.00025319733,0.0942512,0.00058050297,0.000098292505,0.0022051411,0.011011273,0.00070060365,0.80986655,0.00022962116,0.00021692294,0.066425115],"study_design_scores_gemma":[0.00013916347,0.006807341,0.8592408,0.00012188141,0.0003079296,0.0033110538,0.007601688,0.002288143,0.11677208,0.0007924975,0.0025223172,0.000095133306],"about_ca_topic_score_codex":0.00069306395,"about_ca_topic_score_gemma":0.0007114978,"teacher_disagreement_score":0.001938967,"about_ca_system_score_codex":0.00013563456,"about_ca_system_score_gemma":0.00013030216,"threshold_uncertainty_score":0.0064864755},"labels":[],"label_agreement":null},{"id":"W2134345987","doi":"10.1145/2043674.2043704","title":"Mobile based multimodal retrieval and navigation of learning objects using a 3D car metaphor","year":2011,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Ottawa","funders":"","keywords":"Computer science; Metaphor; Human–computer interaction; Entertainment; Multimedia; Mobile device; Gesture; Interface (matter); Resource (disambiguation); Modal; World Wide Web; Artificial intelligence","score_opus":0.030769139905388154,"score_gpt":0.24821782873044285,"score_spread":0.2174486888250547,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2134345987","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19228132,0.001705151,0.75605154,0.0006246544,0.00013163632,0.00032873053,0.00038492837,0.005999568,0.04249247],"genre_scores_gemma":[0.73104125,0.00072965684,0.25360474,0.00031101916,0.00004257481,0.0002737168,0.0002689505,0.00016604805,0.013561967],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997681,0.00008118937,0.000015565867,0.000034670935,0.00007002066,0.000030339263],"domain_scores_gemma":[0.9996971,0.00012325423,0.000023529627,0.00005054162,0.0000687865,0.00003693975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031600308,0.0004752002,0.00032635083,0.0005235646,0.00036174592,0.001299641,0.0006483587,0.0007615373,0.0063025276],"category_scores_gemma":[0.0009835791,0.00017536258,0.00045069886,0.00035137613,0.00039033176,0.001163172,0.0011600113,0.00025726238,0.0013315704],"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":[0.0015256755,0.00032580522,0.0024445357,0.0012929152,0.00013073182,0.0030840193,0.0080195675,0.010592295,0.47666392,0.059889507,0.016976029,0.41905499],"study_design_scores_gemma":[0.0005576363,0.0031945552,0.013097039,0.00059403456,0.00050329766,0.012711376,0.005616378,0.36668193,0.2159286,0.033385802,0.3470818,0.0006475984],"about_ca_topic_score_codex":0.0014333458,"about_ca_topic_score_gemma":0.0024803847,"teacher_disagreement_score":0.0063025276,"about_ca_system_score_codex":0.00021476464,"about_ca_system_score_gemma":0.00023617521,"threshold_uncertainty_score":0.02108407},"labels":[],"label_agreement":null},{"id":"W2136355592","doi":"10.1109/slt.2008.4777868","title":"Identifying salient utterances of online spoken documents using descriptive hypertext","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; Salient; Hypertext; Key (lock); Natural language processing; The Internet; Artificial intelligence; Information retrieval; World Wide Web","score_opus":0.0861815531145473,"score_gpt":0.28962342975028116,"score_spread":0.20344187663573388,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2136355592","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":[0.86195576,0.0012090473,0.13167907,0.0002652879,0.00014083799,0.00027349795,0.0006456762,0.001132613,0.0026980694],"genre_scores_gemma":[0.8936964,0.0006114485,0.10138502,0.000071929906,0.00013134179,0.0000998484,0.0014672644,0.00013857898,0.0023982364],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992655,0.00023292005,0.000055048324,0.00019951665,0.00015508763,0.00009197169],"domain_scores_gemma":[0.9972621,0.0016382724,0.00035168827,0.00013740601,0.0004220662,0.00018845891],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052273576,0.00065288314,0.00063342595,0.00092535047,0.00055020844,0.0010176703,0.00038007472,0.00079488754,0.0015700662],"category_scores_gemma":[0.0040007625,0.00019386958,0.00030258225,0.00049768673,0.00040143033,0.0013151993,0.00077598495,0.00063598633,0.0015017226],"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":[0.00311417,0.0002230134,0.0057556513,0.001099963,0.00005835611,0.001297981,0.0035748663,0.0021309147,0.6699067,0.0013230122,0.001890299,0.3096251],"study_design_scores_gemma":[0.00025867418,0.003940285,0.1420488,0.00029912443,0.0006379818,0.005472572,0.014717132,0.16747311,0.6383169,0.004923596,0.021593597,0.00031819078],"about_ca_topic_score_codex":0.0009969643,"about_ca_topic_score_gemma":0.001539314,"teacher_disagreement_score":0.0015700662,"about_ca_system_score_codex":0.00027352417,"about_ca_system_score_gemma":0.00041985096,"threshold_uncertainty_score":0.005252421},"labels":[],"label_agreement":null},{"id":"W2137540299","doi":"10.1109/icdar.2009.205","title":"A Collaborative Interface for Multimodal Ink and Audio Documents","year":2009,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Western University","funders":"","keywords":"Computer science; Interoperability; Interface (matter); Multimedia; Inkwell; Software; Human–computer interaction; World Wide Web; Programming language; Operating system","score_opus":0.0070551573533363466,"score_gpt":0.2735130288299452,"score_spread":0.2664578714766089,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2137540299","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018162875,0.00017727562,0.9280793,0.00022875477,0.00013221746,0.0003451588,0.0007917218,0.034819536,0.017263182],"genre_scores_gemma":[0.16272144,0.00031540438,0.7706678,0.0003351365,0.00012731754,0.0010410247,0.0020985792,0.0028308835,0.05986238],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99900466,0.00034092148,0.00009121926,0.00016214345,0.0003337706,0.00006727152],"domain_scores_gemma":[0.99795437,0.0011690054,0.000062436324,0.00037241905,0.00025968137,0.00018201649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018441281,0.0008402658,0.00059401436,0.00093777553,0.00070475246,0.002099754,0.0012405785,0.0017172735,0.037151672],"category_scores_gemma":[0.004790898,0.00028729913,0.00060529663,0.0007076501,0.0005056298,0.0027276068,0.0036043802,0.0006052693,0.00771902],"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":[0.0024722056,0.0005325869,0.0014288203,0.00093831035,0.00008669089,0.0020834703,0.007247845,0.005717925,0.15372334,0.05647456,0.09358749,0.6757066],"study_design_scores_gemma":[0.0007983113,0.0011272238,0.0035300052,0.00029007674,0.0001982108,0.0039126244,0.0013804662,0.14148022,0.0929236,0.025209801,0.72883,0.0003194038],"about_ca_topic_score_codex":0.00094440713,"about_ca_topic_score_gemma":0.0010207604,"teacher_disagreement_score":0.037151672,"about_ca_system_score_codex":0.00035434664,"about_ca_system_score_gemma":0.00051474286,"threshold_uncertainty_score":0.124284685},"labels":[],"label_agreement":null},{"id":"W2140866712","doi":"10.1109/iciet.2007.4381322","title":"Hybrid Feature Selection Approach for Natural Language Call Routing Systems","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Routing (electronic design automation); Feature (linguistics); Feature selection; Identification (biology); Natural language; Focus (optics); Set (abstract data type); Artificial intelligence; Natural language processing; Computer network; Programming language","score_opus":0.00998623738972575,"score_gpt":0.2394004547156615,"score_spread":0.22941421732593573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2140866712","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04481,0.00032203476,0.9500934,0.00018042965,0.00005390707,0.00012878074,0.00024507748,0.0031824715,0.0009839131],"genre_scores_gemma":[0.5666312,0.00018740217,0.42721003,0.00023626928,0.00013366323,0.0005472058,0.0014176982,0.000193067,0.0034434712],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988856,0.00040474537,0.00009248987,0.0001922776,0.00032143926,0.00010348777],"domain_scores_gemma":[0.9987299,0.0006656094,0.00006901577,0.00008736683,0.00041785833,0.000030157544],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012401857,0.0008397555,0.0009235892,0.0012575549,0.00043541924,0.00089048,0.0010388853,0.0008784479,0.0019711065],"category_scores_gemma":[0.0023279684,0.00023826894,0.0007698276,0.00088098896,0.00028481378,0.0007444385,0.00054025406,0.00058194186,0.000727122],"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":[0.00057623425,0.0003787548,0.0022523142,0.00018499287,0.00019707059,0.00033746602,0.00012237967,0.09235988,0.048587464,0.00203254,0.0048373053,0.8481336],"study_design_scores_gemma":[0.00005849132,0.00014963656,0.0023035677,0.000007978162,0.000060918817,0.0001775855,0.0000426369,0.97748876,0.014842835,0.0023155024,0.0025113635,0.000040728904],"about_ca_topic_score_codex":0.0028677012,"about_ca_topic_score_gemma":0.003140427,"teacher_disagreement_score":0.0028677012,"about_ca_system_score_codex":0.0004537208,"about_ca_system_score_gemma":0.0005586913,"threshold_uncertainty_score":0.0065939426},"labels":[],"label_agreement":null},{"id":"W2142785422","doi":"10.1093/llc/fqr025","title":"Introducing DH 2010","year":2011,"lang":"fr","type":"article","venue":"Literary and Linguistic Computing","topic":"Speech and dialogue systems","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":"","keywords":"Library science; Classics; Digital library; Media studies; History; Art; Humanities; Art history; Sociology; Computer science; Literature","score_opus":0.03633735293295033,"score_gpt":0.2377181184964745,"score_spread":0.2013807655635242,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2142785422","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":[0.001005034,0.00630858,0.00730539,0.07741243,0.09642965,0.0005493609,0.004428953,0.0035918627,0.8029687],"genre_scores_gemma":[0.003536226,0.0046359366,0.003543028,0.0124384975,0.010644935,0.00027912596,0.0034228745,0.0012730504,0.9602263],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99735105,0.00041436614,0.00011906485,0.00041352113,0.0012359897,0.0004659917],"domain_scores_gemma":[0.99412006,0.0004356015,0.000107402266,0.00038280452,0.0018300198,0.003124099],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0041410197,0.0007493561,0.00036679945,0.0020632423,0.0033002603,0.010177941,0.0026912675,0.0030477971,0.3629625],"category_scores_gemma":[0.00825248,0.00044804474,0.0005864822,0.0019235644,0.0011039281,0.008030855,0.004846467,0.005207367,0.21033481],"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":[0.000009173728,0.000022600008,0.000067066554,0.0000540674,0.0000010266032,0.00003619353,0.0000836216,0.000019655876,0.00008390679,0.008674672,0.94543946,0.04550857],"study_design_scores_gemma":[0.0000013956561,0.000003284088,0.000060701863,0.000019305577,1.8798264e-7,0.00002598568,0.000049577586,0.0000053156505,0.000013769038,0.00046491917,0.9993531,0.0000023711632],"about_ca_topic_score_codex":0.008843567,"about_ca_topic_score_gemma":0.021579236,"teacher_disagreement_score":0.3629625,"about_ca_system_score_codex":0.0058595412,"about_ca_system_score_gemma":0.0062217317,"threshold_uncertainty_score":0.90865666},"labels":[],"label_agreement":null},{"id":"W2144702205","doi":"10.1109/cmpsac.1988.17220","title":"Coherent analysis of argumentative discourse","year":2003,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Argumentative; Computer science; Argument (complex analysis); Interpretation (philosophy); Linguistics; Computational linguistics; Natural language processing; Artificial intelligence; Philosophy","score_opus":0.016554442846422133,"score_gpt":0.28910051982428325,"score_spread":0.2725460769778611,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2144702205","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0148008475,0.0058532595,0.9151112,0.0062007676,0.00031672823,0.00019945343,0.0003664499,0.00034024956,0.05681114],"genre_scores_gemma":[0.531363,0.002376588,0.45376474,0.0005940829,0.0005104152,0.00054650364,0.0007692236,0.00021864222,0.009856788],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9885966,0.0069749583,0.00063025276,0.0011905676,0.0022053309,0.0004022642],"domain_scores_gemma":[0.9873772,0.008699739,0.0007588264,0.0010699091,0.0018917635,0.00020255933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008683839,0.0008613786,0.0008610717,0.006944002,0.002783751,0.0076646814,0.001307162,0.0018823445,0.0065805227],"category_scores_gemma":[0.024640048,0.00077828177,0.0017472593,0.004676131,0.0077747256,0.012392501,0.00398451,0.0024256804,0.0009225721],"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":[0.000010443128,0.000006180078,0.00010198419,0.000064894986,0.000018015911,0.000049456114,0.0011199116,0.0007490153,0.00020360619,0.9866659,0.0013351432,0.00967544],"study_design_scores_gemma":[0.000009524282,0.0000072773114,0.000104149025,0.000043157557,0.000010786086,0.00003478038,0.00036359724,0.006895871,0.00038967395,0.9822574,0.009874145,0.000009699895],"about_ca_topic_score_codex":0.0013648649,"about_ca_topic_score_gemma":0.0011528169,"teacher_disagreement_score":0.008683839,"about_ca_system_score_codex":0.0033556933,"about_ca_system_score_gemma":0.0016564053,"threshold_uncertainty_score":0.04592514},"labels":[],"label_agreement":null},{"id":"W2146741136","doi":"10.1145/1242572.1242823","title":"A browser for a public-domain SpeechWeb","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Domain (mathematical analysis); Software; Public domain; World Wide Web; Multimedia; Operating system","score_opus":0.03197603971871341,"score_gpt":0.26017733425967854,"score_spread":0.22820129454096513,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2146741136","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.02544244,0.0010963684,0.37960663,0.0019090722,0.0009559161,0.0008802623,0.016446754,0.42280447,0.1508582],"genre_scores_gemma":[0.28441784,0.002045707,0.28040162,0.0031340597,0.00084672845,0.001710472,0.04754526,0.05228175,0.32761657],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961627,0.00008979851,0.00004411011,0.000057813846,0.00014360891,0.000048385642],"domain_scores_gemma":[0.9981456,0.0007082782,0.000065978034,0.00031479844,0.00036214493,0.00040323276],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009925266,0.0007927642,0.0005688312,0.0011071702,0.00062800274,0.0016338169,0.00097450893,0.0014724693,0.08647483],"category_scores_gemma":[0.0023288059,0.00057495467,0.00037535504,0.00066375744,0.0004017077,0.0025201533,0.002772057,0.0017039834,0.047467865],"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":[0.0010957562,0.0007456843,0.002756803,0.0007310178,0.00007955047,0.0027212617,0.0027762044,0.0011702405,0.06031806,0.032364573,0.7212253,0.17401548],"study_design_scores_gemma":[0.00019925408,0.00008973406,0.00265156,0.00014209171,0.00003886806,0.0017468807,0.0004897426,0.012735969,0.018156111,0.008069798,0.95557326,0.00010669322],"about_ca_topic_score_codex":0.0018194866,"about_ca_topic_score_gemma":0.003149305,"teacher_disagreement_score":0.08647483,"about_ca_system_score_codex":0.00045025357,"about_ca_system_score_gemma":0.00071863394,"threshold_uncertainty_score":0.28928715},"labels":[],"label_agreement":null},{"id":"W2152631915","doi":"10.1109/icsc.2007.76","title":"Adding Semantics to Formal Data Specifications to Automatically Generate Corresponding Voice Data-Input Applications","year":2007,"lang":"en","type":"article","venue":"International Conference on Semantic Computing (ICSC 2007)","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Computer science; XML; Programming language; Semantics (computer science); Document Structure Description; Formal semantics (linguistics); Natural language processing; Information retrieval; World Wide Web","score_opus":0.17971773490567128,"score_gpt":0.3690396209567837,"score_spread":0.18932188605111244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2152631915","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003740308,0.000061713145,0.9899095,0.000113280206,0.00007245896,0.00013560025,0.0002033166,0.0046564983,0.001107324],"genre_scores_gemma":[0.0553049,0.0001798068,0.9389733,0.00021910475,0.000031592772,0.0002745541,0.001095118,0.002386298,0.0015352783],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99695575,0.0009390667,0.00044095557,0.00041722564,0.0011189907,0.00012806535],"domain_scores_gemma":[0.9917658,0.0051030205,0.00034837314,0.0011804828,0.0014818896,0.000120378005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039170054,0.0009861718,0.00059759617,0.0014843767,0.0005541528,0.0019775454,0.0010635017,0.00096436293,0.0035828962],"category_scores_gemma":[0.011252994,0.00088699075,0.001353691,0.00074845226,0.0011623834,0.0023073722,0.002020845,0.0018761775,0.0018377369],"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":[0.0005304781,0.0003501354,0.0033230647,0.0020929195,0.00016337154,0.0019068484,0.004356041,0.04629024,0.12554854,0.2558172,0.016864644,0.5427565],"study_design_scores_gemma":[0.00024513894,0.00018312155,0.00054189353,0.0005006152,0.00014669448,0.0013293078,0.0006142206,0.35459203,0.2829258,0.12220399,0.23651345,0.00020370029],"about_ca_topic_score_codex":0.001253246,"about_ca_topic_score_gemma":0.0013244351,"teacher_disagreement_score":0.0039170054,"about_ca_system_score_codex":0.00084870524,"about_ca_system_score_gemma":0.0019452446,"threshold_uncertainty_score":0.020715356},"labels":[],"label_agreement":null},{"id":"W2153519585","doi":"10.1080/01650250143000292","title":"Collaborative recall in married and unacquainted dyads","year":2002,"lang":"en","type":"article","venue":"International Journal of Behavioral Development","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Mount Allison University","funders":"","keywords":"Recall; Psychology; Spouse; Developmental psychology; Task (project management); Recall test; Free recall; Cognitive psychology","score_opus":0.02326949053528017,"score_gpt":0.2800593547303633,"score_spread":0.25678986419508315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2153519585","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":[0.9997168,0.0001019062,0.000026682852,0.00000650815,0.000002220836,0.000003242905,0.000013799582,8.5886563e-7,0.00012793278],"genre_scores_gemma":[0.9992623,0.00012854209,0.00007729803,0.000013366815,0.0000043250843,0.000005989954,0.000045635774,0.0000010786838,0.00046150803],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99906975,0.0003082779,0.00010427649,0.00018461983,0.00020119418,0.00013189818],"domain_scores_gemma":[0.996253,0.0013499877,0.0008208519,0.00034421962,0.0005345233,0.0006973037],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019338919,0.00034196093,0.0005828542,0.0011475076,0.0011350947,0.0015355356,0.00032060867,0.00043169732,0.0019532412],"category_scores_gemma":[0.008484469,0.00047043993,0.00023372454,0.00045608042,0.00069450604,0.00067294325,0.0016526113,0.00037217172,0.00045262426],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010893474,0.000418242,0.81566316,0.000079485406,0.000104041916,0.0033909811,0.14425917,0.00008718816,0.0061011123,0.00010769103,0.00020305326,0.028496506],"study_design_scores_gemma":[0.0000697106,0.002645207,0.892081,0.00003955939,0.00013683758,0.005279002,0.09408518,0.00036204813,0.0031866312,0.0002857644,0.001760305,0.00006874087],"about_ca_topic_score_codex":0.0061051208,"about_ca_topic_score_gemma":0.009231469,"teacher_disagreement_score":0.0061051208,"about_ca_system_score_codex":0.000298996,"about_ca_system_score_gemma":0.00025582977,"threshold_uncertainty_score":0.012139201},"labels":[],"label_agreement":null},{"id":"W2155617938","doi":"10.5539/elt.v4n2p107","title":"Logbook Language Characteristics and Recordation Requirement","year":2011,"lang":"en","type":"article","venue":"English Language Teaching","topic":"Speech and dialogue systems","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":"Logbook; Psychology; Computer science; Natural language processing","score_opus":0.019135450746988837,"score_gpt":0.23702925881585207,"score_spread":0.21789380806886324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2155617938","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":[0.9902777,0.000110803274,0.0037168642,0.00011339207,0.000007827373,0.000033588516,0.00026815277,0.00009729036,0.005374304],"genre_scores_gemma":[0.9921589,0.00014788705,0.0023998166,0.000031062882,0.000008292717,0.00004663415,0.00047404435,0.000038637038,0.0046947678],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9983188,0.00029994448,0.00034528106,0.00025154397,0.0006342211,0.00015033905],"domain_scores_gemma":[0.9876896,0.0059453323,0.002524816,0.0006171173,0.0026568272,0.0005661945],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00094689167,0.00023829528,0.00016071736,0.0012501033,0.0005630527,0.001049796,0.0004527587,0.00029653186,0.0038391796],"category_scores_gemma":[0.011953296,0.00016363281,0.00013040943,0.0010437568,0.00051444024,0.0014326731,0.00049782905,0.00033806195,0.00077459234],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0011253821,0.00026268742,0.5968684,0.0011295874,0.000048341764,0.005991127,0.06528055,0.002158807,0.12194357,0.0028496957,0.0034828004,0.19885904],"study_design_scores_gemma":[0.000017715058,0.0004915257,0.8964061,0.0001174509,0.00005138175,0.006360257,0.03460296,0.003720923,0.027009763,0.0005253984,0.03053286,0.0001636783],"about_ca_topic_score_codex":0.005615471,"about_ca_topic_score_gemma":0.007545345,"teacher_disagreement_score":0.005615471,"about_ca_system_score_codex":0.00054570794,"about_ca_system_score_gemma":0.00075741485,"threshold_uncertainty_score":0.012843311},"labels":[],"label_agreement":null},{"id":"W2156153681","doi":"10.7202/014499ar","title":"Un système à base de connaissances pour une communication parlée personne-système multilingue","year":2007,"lang":"fr","type":"article","venue":"Revue de l’Université de Moncton","topic":"Speech and dialogue systems","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 Moncton","funders":"","keywords":"Humanities; Political science; Philosophy","score_opus":0.028583890194663213,"score_gpt":0.2395774572075039,"score_spread":0.2109935670128407,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156153681","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060319163,0.0008618184,0.9177454,0.0004748942,0.00015919552,0.00024078025,0.00041141728,0.006907236,0.012880089],"genre_scores_gemma":[0.5146272,0.0005416877,0.46122205,0.00027623068,0.00009991769,0.00028362722,0.00081762153,0.00042937548,0.021702247],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976191,0.00045418114,0.00017367302,0.0010442475,0.000550113,0.0001586498],"domain_scores_gemma":[0.9968946,0.0012174009,0.00017226893,0.00047169288,0.0011116585,0.00013235678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024013254,0.0012183854,0.0009079527,0.0017067742,0.0010971371,0.0028196657,0.0009934912,0.0013769345,0.010236817],"category_scores_gemma":[0.006473701,0.0006803426,0.00095076166,0.000799821,0.0010573696,0.003391037,0.0019649663,0.0012803058,0.004410494],"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":[0.0006668981,0.00016553816,0.013206316,0.0009082746,0.00045245542,0.00082967454,0.0062426077,0.030822072,0.16473436,0.02677396,0.0050230487,0.7501747],"study_design_scores_gemma":[0.00009780889,0.0011680549,0.047972064,0.0006329876,0.0010317867,0.0022876426,0.0040064426,0.55716175,0.19641522,0.0494385,0.13932422,0.00046365778],"about_ca_topic_score_codex":0.007914132,"about_ca_topic_score_gemma":0.0069153197,"teacher_disagreement_score":0.010236817,"about_ca_system_score_codex":0.00096991175,"about_ca_system_score_gemma":0.0013735762,"threshold_uncertainty_score":0.03424561},"labels":[],"label_agreement":null},{"id":"W2156713894","doi":"10.1109/wi-iatw.2006.28","title":"Adding User-Level SPACe: Security, Privacy, and Context to Intelligent Multimedia Information Architectures","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Saint Mary's University","funders":"","keywords":"Computer science; Architecture; Context (archaeology); Information privacy; Focus (optics); Enterprise information security architecture; Key (lock); World Wide Web; Computer security; Multimedia","score_opus":0.01455085542327593,"score_gpt":0.23371517463261754,"score_spread":0.2191643192093416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156713894","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025616968,0.0008578721,0.9553528,0.001732452,0.000080975704,0.00006811474,0.00003806986,0.0020254827,0.01422733],"genre_scores_gemma":[0.5589649,0.0010263376,0.42825976,0.0007501768,0.00022722191,0.00018902773,0.00013652773,0.00026918462,0.010176938],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99787664,0.00065906346,0.00021141207,0.00027382668,0.0006912975,0.00028787024],"domain_scores_gemma":[0.9981065,0.00039939958,0.00012203586,0.0007663756,0.0003776837,0.00022796234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001998556,0.0006886497,0.00076791266,0.0010921233,0.0016314479,0.0069341124,0.001697248,0.0020374942,0.0030775883],"category_scores_gemma":[0.0037678669,0.0006213934,0.0009482526,0.0010144105,0.002839068,0.012026582,0.0060993545,0.002876731,0.0010516443],"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":[0.00019871423,0.00009772063,0.0015989895,0.00018217937,0.000083280465,0.00040164468,0.0034635987,0.014032225,0.014803005,0.78753984,0.0038366471,0.17376216],"study_design_scores_gemma":[0.00004815817,0.00029535725,0.0010627768,0.00021560241,0.000303683,0.00097444624,0.001156995,0.1819183,0.034392588,0.5636472,0.21580115,0.0001837865],"about_ca_topic_score_codex":0.0022678603,"about_ca_topic_score_gemma":0.0026430567,"teacher_disagreement_score":0.0069341124,"about_ca_system_score_codex":0.0011173519,"about_ca_system_score_gemma":0.0012241091,"threshold_uncertainty_score":0.010569513},"labels":[],"label_agreement":null},{"id":"W215674542","doi":"10.4000/praxematique.1184","title":"La transcription perceptuelle au service du corpus de conversations naturelles","year":2010,"lang":"fr","type":"article","venue":"Cahiers de praxématique","topic":"Speech and dialogue systems","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":"Humanities; Philosophy","score_opus":0.012033657951156683,"score_gpt":0.23335224319025272,"score_spread":0.22131858523909603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W215674542","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15040746,0.0017229983,0.77224267,0.0031477576,0.0021670484,0.001002411,0.01743553,0.012711114,0.039163005],"genre_scores_gemma":[0.41846958,0.0014841605,0.5155293,0.00061007583,0.0008082369,0.0018320855,0.014856971,0.0025591603,0.04385049],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9956061,0.0021060796,0.00027944916,0.0008115634,0.0010335977,0.00016310839],"domain_scores_gemma":[0.99071306,0.0055888523,0.00033247494,0.0011486816,0.0020864892,0.00013050051],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002176814,0.0012650959,0.00071931357,0.0017577073,0.0012441836,0.003160976,0.00068954093,0.0013133422,0.015873568],"category_scores_gemma":[0.016158853,0.00048023104,0.0005156312,0.0021877685,0.0013870674,0.0019600845,0.0012144257,0.0014439126,0.0072510703],"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":[0.0021332016,0.000115279,0.00308822,0.0022345989,0.00011415337,0.0014393984,0.02240072,0.0052370722,0.32108992,0.02368258,0.033152726,0.58531207],"study_design_scores_gemma":[0.00032599582,0.00097586797,0.025996454,0.0008712378,0.00027392653,0.003538761,0.026572544,0.112183236,0.24007148,0.028394828,0.56042117,0.00037456496],"about_ca_topic_score_codex":0.006512924,"about_ca_topic_score_gemma":0.0051226863,"teacher_disagreement_score":0.015873568,"about_ca_system_score_codex":0.00082978053,"about_ca_system_score_gemma":0.0014437936,"threshold_uncertainty_score":0.053102434},"labels":[],"label_agreement":null},{"id":"W2158112478","doi":"10.1007/s10772-008-9007-3","title":"VoiceMarks: restructuring hierarchical voice menus for improving navigation","year":2006,"lang":"en","type":"article","venue":"International Journal of Speech Technology","topic":"Speech and dialogue systems","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 Manitoba","funders":"","keywords":"Computer science; Ticket; Human–computer interaction; Process (computing); Schedule; Interface (matter); User interface; Telephony; Multimedia; Telecommunications; Computer network","score_opus":0.0069514658770851835,"score_gpt":0.25311129350439066,"score_spread":0.24615982762730548,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158112478","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":[0.05636932,0.0005868045,0.7687687,0.00017352114,0.0003813628,0.00024067875,0.0012317412,0.16900915,0.0032388289],"genre_scores_gemma":[0.2920172,0.00039505653,0.67982584,0.00032420363,0.00016344791,0.00033664325,0.0033191214,0.011241783,0.012376735],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9993019,0.00010807965,0.00006246151,0.00015943199,0.00028062132,0.000087450055],"domain_scores_gemma":[0.9969332,0.0014796115,0.00017829258,0.0006700171,0.00054150535,0.00019739933],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006956642,0.0017324019,0.0010788867,0.0010088822,0.00063647865,0.0012063903,0.0027735627,0.0014815419,0.021944407],"category_scores_gemma":[0.0056194826,0.0009698129,0.00072537136,0.00087223254,0.0004842962,0.0028226506,0.0021529314,0.0012246689,0.004559311],"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":[0.0019798826,0.0005064749,0.0021341378,0.00057706103,0.00008072113,0.00042163604,0.00067850214,0.007878907,0.120610185,0.0039268676,0.03607687,0.8251287],"study_design_scores_gemma":[0.0013533634,0.0018013851,0.005676449,0.00028012655,0.000605601,0.0013112813,0.0009884557,0.52010906,0.34477326,0.020800425,0.101878956,0.0004215947],"about_ca_topic_score_codex":0.0031346541,"about_ca_topic_score_gemma":0.004689755,"teacher_disagreement_score":0.021944407,"about_ca_system_score_codex":0.00028515203,"about_ca_system_score_gemma":0.0007522276,"threshold_uncertainty_score":0.073411345},"labels":[],"label_agreement":null},{"id":"W2158317896","doi":"10.7202/004627ar","title":"Computational Discourse Analysis for Interpretation","year":2002,"lang":"fr","type":"article","venue":"Meta Journal des traducteurs","topic":"Speech and dialogue systems","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":"Humanities; Philosophy","score_opus":0.0722304476494293,"score_gpt":0.2989219815210896,"score_spread":0.2266915338716603,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158317896","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005692156,0.030336373,0.7446542,0.023352806,0.0014737635,0.00054167886,0.0046455804,0.0036696824,0.18563381],"genre_scores_gemma":[0.24295889,0.01198369,0.6861815,0.0020196757,0.0012542132,0.0017901196,0.008538778,0.0016149087,0.04365823],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9946702,0.003265034,0.00042754205,0.0009382363,0.0005508284,0.00014818208],"domain_scores_gemma":[0.99060166,0.006713057,0.0004357645,0.0014681995,0.0005710619,0.00021027187],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005348144,0.001892778,0.0014103613,0.0064896373,0.0030616464,0.01376637,0.002972861,0.0026627558,0.04984858],"category_scores_gemma":[0.020956824,0.000877365,0.00279578,0.0056009064,0.0070890915,0.015269351,0.006640594,0.0034982634,0.008938858],"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":[0.00006080571,0.000028601113,0.00039438196,0.00063329714,0.00007612749,0.00014463125,0.0017843889,0.0026580929,0.00021984862,0.88117814,0.021901565,0.09092004],"study_design_scores_gemma":[0.000011692063,0.0000067814217,0.00017093596,0.0002917073,0.000018541718,0.00007467104,0.0006233534,0.010172313,0.0001871137,0.90764034,0.080786884,0.00001559396],"about_ca_topic_score_codex":0.005666933,"about_ca_topic_score_gemma":0.0052266046,"teacher_disagreement_score":0.04984858,"about_ca_system_score_codex":0.00512635,"about_ca_system_score_gemma":0.003896564,"threshold_uncertainty_score":0.16676015},"labels":[],"label_agreement":null},{"id":"W2158903907","doi":"10.1177/0023830908099881","title":"Automatic Syllabification in English: A Comparison of Different Algorithms","year":2009,"lang":"en","type":"article","venue":"Language and Speech","topic":"Speech and dialogue systems","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":"University of New Brunswick; National Research Council Canada; National Research Council Institute for Biodiagnostics; Dalhousie University","funders":"","keywords":"Syllabification; Computer science; Syllable; Lexicon; Algorithm; Artificial intelligence; Natural language processing; Set (abstract data type); Word (group theory); Speech recognition; Mathematics","score_opus":0.013061561501025602,"score_gpt":0.27214307862619924,"score_spread":0.25908151712517363,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2158903907","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22351597,0.004677997,0.7390516,0.0004507654,0.00021012315,0.0005418964,0.0012991884,0.016439553,0.013812919],"genre_scores_gemma":[0.29156277,0.0014850928,0.7005179,0.00013228336,0.000048351838,0.0002722543,0.002718213,0.0010042711,0.0022588968],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971698,0.00095074985,0.00036827588,0.00064103346,0.00068693573,0.00018326068],"domain_scores_gemma":[0.99284244,0.0052783745,0.0001566882,0.00042328617,0.0011795034,0.000119729484],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034479762,0.0008984071,0.0009747907,0.003570775,0.0006874717,0.001907931,0.0017184657,0.0010160151,0.0027453757],"category_scores_gemma":[0.010424968,0.00049591967,0.0009998094,0.0017503267,0.00053769164,0.0021474161,0.0012946653,0.0009487506,0.0014506496],"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":[0.00054670655,0.0002568596,0.0055812537,0.0006274098,0.00021878243,0.000081352795,0.00065709604,0.015075912,0.011315942,0.0064476137,0.0029882388,0.95620286],"study_design_scores_gemma":[0.00042935598,0.0005372409,0.032031283,0.00035194933,0.00048332618,0.00083719793,0.0016558429,0.83961403,0.07649888,0.021852378,0.025434718,0.00027384734],"about_ca_topic_score_codex":0.008483999,"about_ca_topic_score_gemma":0.0069852322,"teacher_disagreement_score":0.008483999,"about_ca_system_score_codex":0.0011498453,"about_ca_system_score_gemma":0.0017092794,"threshold_uncertainty_score":0.018234849},"labels":[],"label_agreement":null},{"id":"W2163085600","doi":"10.1145/1125451.1125677","title":"An interactive speech interface for summarizing agile project planning meetings","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Calgary","funders":"","keywords":"Agile software development; Ambiguity; Computer science; Interface (matter); Natural language; Human–computer interaction; Natural language understanding; Natural (archaeology); User interface; Natural language processing; Software engineering","score_opus":0.022433698207040668,"score_gpt":0.3141600177336455,"score_spread":0.2917263195266048,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163085600","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03560248,0.0005708935,0.91754806,0.00031244964,0.00036779788,0.0004011485,0.0012793159,0.03723818,0.0066796937],"genre_scores_gemma":[0.21735165,0.0004616148,0.7605642,0.0003343493,0.00038769958,0.0010984219,0.0033360731,0.0016373072,0.014828658],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9990036,0.0005254279,0.00006005318,0.00015926408,0.00021454964,0.000037069847],"domain_scores_gemma":[0.99634886,0.0026638766,0.00013905042,0.00019379429,0.00048376067,0.0001706413],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016485647,0.0010849191,0.00048361946,0.0007937998,0.00044732654,0.0012178493,0.0011861789,0.0009945016,0.016389221],"category_scores_gemma":[0.006047121,0.00027513507,0.0003637303,0.00045837823,0.00028683714,0.0012123256,0.0010481197,0.00071484473,0.0050302986],"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":[0.0031865882,0.000260963,0.0012382456,0.0017884494,0.0001411585,0.0009912495,0.007847264,0.0080698915,0.1531969,0.0069739986,0.055281077,0.7610242],"study_design_scores_gemma":[0.0010940223,0.0024750796,0.0063519524,0.0005532647,0.000541411,0.0031032157,0.005175332,0.30953464,0.13527444,0.014790787,0.52067065,0.00043514918],"about_ca_topic_score_codex":0.00054037484,"about_ca_topic_score_gemma":0.00070440996,"teacher_disagreement_score":0.016389221,"about_ca_system_score_codex":0.00023854467,"about_ca_system_score_gemma":0.00029953435,"threshold_uncertainty_score":0.054827392},"labels":[],"label_agreement":null},{"id":"W2163485475","doi":"10.1109/ccnc.2007.74","title":"Combining VoiceXML with CCXML: A Comparative Study","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Session Initiation Protocol; Markup language; Voice over IP; Protocol (science); SIP trunking; Component (thermodynamics); Session (web analytics); Simple (philosophy); Abstraction; World Wide Web; Multimedia; XML; Server; The Internet","score_opus":0.03649970218782573,"score_gpt":0.2924752681110811,"score_spread":0.2559755659232554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2163485475","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":[0.8057911,0.020231722,0.031014295,0.0024552115,0.00014393602,0.0007507578,0.0005888086,0.0005245967,0.13849965],"genre_scores_gemma":[0.95790917,0.007240834,0.027590996,0.0005082598,0.00007976867,0.00024168659,0.0005618529,0.00030121958,0.005566118],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9709858,0.020139005,0.0015103834,0.000875116,0.005921822,0.00056789396],"domain_scores_gemma":[0.93749964,0.0460266,0.0019273029,0.0025205328,0.011487306,0.0005386452],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.034566846,0.00040117782,0.00060038787,0.003844848,0.0014363533,0.004768637,0.0014185848,0.0013173047,0.004180985],"category_scores_gemma":[0.04240871,0.0003457036,0.0003838688,0.0067060804,0.0014889168,0.009149987,0.0024554913,0.0009016529,0.001341793],"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":[0.003115485,0.001095024,0.08578107,0.005887177,0.00023775287,0.0030376376,0.16895701,0.0015460012,0.023928255,0.018868947,0.0063200854,0.6812255],"study_design_scores_gemma":[0.00035015968,0.009074086,0.19469574,0.007009662,0.0008965545,0.010132285,0.3284577,0.013602011,0.04273115,0.0066362033,0.38606775,0.0003466388],"about_ca_topic_score_codex":0.0029950566,"about_ca_topic_score_gemma":0.0043946477,"teacher_disagreement_score":0.034566846,"about_ca_system_score_codex":0.0019213641,"about_ca_system_score_gemma":0.0010875113,"threshold_uncertainty_score":0.18280917},"labels":[],"label_agreement":null},{"id":"W2164739105","doi":"10.1145/1180995.1181012","title":"GSI demo","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gesture; Computer science; Table (database); Human–computer interaction; Input device; Macro; Mobile device; Computer graphics (images); Speech recognition; Computer hardware; Artificial intelligence; World Wide Web; Programming language; Database","score_opus":0.004694268545340269,"score_gpt":0.17959119080330022,"score_spread":0.17489692225795994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2164739105","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":[0.00735592,0.00058892264,0.036198657,0.0013191331,0.00079650164,0.0009921612,0.24309942,0.14309001,0.56655926],"genre_scores_gemma":[0.11049734,0.0012194392,0.07048261,0.0018368663,0.0004349865,0.001810926,0.54909927,0.03686878,0.22774981],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997696,0.000023108638,0.000009405763,0.00003229584,0.000120071105,0.000045591456],"domain_scores_gemma":[0.9994368,0.00006523572,0.000019281619,0.00015792022,0.0002006998,0.00011999485],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003560511,0.0015761775,0.000548606,0.0015961758,0.0007336186,0.0020114637,0.0012789237,0.0007837833,0.2957566],"category_scores_gemma":[0.0012411962,0.000402036,0.0005122764,0.0018554414,0.00032689294,0.001995248,0.0019607916,0.0013826715,0.13007857],"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":[0.0003079309,0.000050618695,0.00050281064,0.0001934884,0.000012651633,0.00020606813,0.0001882008,0.00096953224,0.0016448983,0.0028778224,0.9403399,0.05270603],"study_design_scores_gemma":[0.000116738425,0.00004047664,0.0016102836,0.00008111645,0.000016435108,0.0002570685,0.0001871601,0.0038003928,0.0030576033,0.0032569584,0.98752964,0.000046088477],"about_ca_topic_score_codex":0.009117052,"about_ca_topic_score_gemma":0.010290899,"teacher_disagreement_score":0.7042434,"about_ca_system_score_codex":0.0008280235,"about_ca_system_score_gemma":0.0004428179,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2168737808","doi":"10.1109/icassp.1986.1168806","title":"Plan refinement in a knowledge-based system for automatic speech recognition","year":2005,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Concordia University","funders":"","keywords":"Computer science; Speech recognition; Plan (archaeology); Natural language processing; Artificial intelligence; Action (physics); Speaker recognition","score_opus":0.03912540571397419,"score_gpt":0.26028547557631737,"score_spread":0.22116006986234318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2168737808","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022335796,0.000122014855,0.95642245,0.00010279561,0.000022084101,0.00022515624,0.00016559935,0.018670823,0.0019333476],"genre_scores_gemma":[0.27255172,0.00012813282,0.7224105,0.00016269741,0.000020631738,0.00042432058,0.0008155409,0.0004209922,0.0030654501],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895954,0.00024605222,0.00007816478,0.00035736721,0.0002648038,0.00009409617],"domain_scores_gemma":[0.9980585,0.0012943486,0.0001257029,0.00023837305,0.00021341899,0.000069574504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016025992,0.000657991,0.00060286414,0.00058150775,0.0005646303,0.0010816251,0.0019292937,0.0009184491,0.0061972025],"category_scores_gemma":[0.0042461576,0.00061254174,0.00055826094,0.00037387438,0.0011189529,0.0015216578,0.0010030847,0.0011913343,0.0022399833],"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":[0.0024964612,0.00066811184,0.0022779515,0.00066900346,0.00011561123,0.0008433157,0.0016102232,0.11573447,0.14028701,0.024925541,0.0077977325,0.70257455],"study_design_scores_gemma":[0.00020116965,0.0005227163,0.0013099394,0.000084522064,0.00015373269,0.00031320087,0.00015989314,0.8567244,0.10694355,0.017771237,0.015717445,0.00009821791],"about_ca_topic_score_codex":0.00844359,"about_ca_topic_score_gemma":0.007655692,"teacher_disagreement_score":0.00844359,"about_ca_system_score_codex":0.0009440027,"about_ca_system_score_gemma":0.0014703353,"threshold_uncertainty_score":0.020731747},"labels":[],"label_agreement":null},{"id":"W2170935033","doi":"10.1109/ivtta.1994.341553","title":"Directory assistance automation in Bell Canada: trial results","year":2002,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":true,"ca_institutions":"Bell (Canada)","funders":"","keywords":"Directory; Vocabulary; Dialog box; Computer science; Automation; World Wide Web; Operator (biology); Natural language processing; Artificial intelligence; Linguistics; Engineering; Operating system","score_opus":0.025865270316895974,"score_gpt":0.21590058841314208,"score_spread":0.1900353180962461,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2170935033","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":[0.9710734,0.0010434815,0.005097178,0.0010155842,0.000099297395,0.0015277585,0.0019603753,0.0028698738,0.015312922],"genre_scores_gemma":[0.9642263,0.0006719466,0.014137251,0.00038241825,0.000044900073,0.00051563606,0.002802862,0.00023111465,0.016987514],"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","domain_scores_codex":[0.99595046,0.0010494617,0.00019028875,0.00044048115,0.0015467725,0.00082244765],"domain_scores_gemma":[0.99287295,0.0021452117,0.00023620846,0.00047670826,0.003421924,0.0008469864],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036112915,0.001209452,0.0010163593,0.00067642285,0.0024156854,0.001322397,0.0015481845,0.0018433785,0.0051586977],"category_scores_gemma":[0.0071431333,0.00046468343,0.00043014542,0.001276685,0.001073498,0.00068527093,0.0010865973,0.0010440726,0.0017274414],"study_design_candidate":"nonrandomized_trial","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":[0.03191317,0.022545723,0.036842622,0.0031448395,0.00072426733,0.0029360899,0.015730811,0.041054282,0.050671384,0.0028262392,0.07615607,0.71545446],"study_design_scores_gemma":[0.021390388,0.08635379,0.27787223,0.00045594206,0.0018964497,0.0017227122,0.015540168,0.12761149,0.15488295,0.0016541522,0.309544,0.0010756908],"about_ca_topic_score_codex":0.48792252,"about_ca_topic_score_gemma":0.57260084,"teacher_disagreement_score":0.51207745,"about_ca_system_score_codex":0.005421973,"about_ca_system_score_gemma":0.0059462055,"threshold_uncertainty_score":0.970165},"labels":[],"label_agreement":null},{"id":"W2187941261","doi":"","title":"Give us the tools: a personal view of multi-modal computer-human dialogue","year":2000,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Modal; Human–computer interaction; Artificial intelligence; Communication; Sociology","score_opus":0.036320858871908356,"score_gpt":0.26126791803069055,"score_spread":0.2249470591587822,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2187941261","genre_codex":"methods","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005162286,0.0067675277,0.7011152,0.032531355,0.0014068908,0.000051266354,0.00035001402,0.0015380796,0.2510773],"genre_scores_gemma":[0.6164906,0.008318904,0.2402774,0.010323461,0.004815524,0.00042071217,0.00058866874,0.0015906324,0.11717403],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984043,0.0008998458,0.00005841461,0.000327194,0.00021586414,0.000094277435],"domain_scores_gemma":[0.99821895,0.00089343195,0.000067795314,0.0003874198,0.00016075924,0.000271621],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020264266,0.00104409,0.0006492315,0.0019930995,0.0035394246,0.010779202,0.0022271136,0.006084203,0.018774405],"category_scores_gemma":[0.00332692,0.0006747475,0.0007555575,0.0015759412,0.014425234,0.021334402,0.0052746725,0.0076164003,0.0033092645],"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":[0.000025462528,0.0000092199125,0.000119554024,0.000056423898,0.000009276589,0.00008941058,0.0053862478,0.0006459837,0.0005639772,0.97225857,0.008258433,0.012577388],"study_design_scores_gemma":[0.000009527345,0.000028298806,0.00020714724,0.0001153707,0.00002818633,0.0005599332,0.0021125318,0.008081583,0.0008848744,0.7024748,0.2854641,0.000033635548],"about_ca_topic_score_codex":0.0024028267,"about_ca_topic_score_gemma":0.0021530073,"teacher_disagreement_score":0.018774405,"about_ca_system_score_codex":0.0016571111,"about_ca_system_score_gemma":0.0007839933,"threshold_uncertainty_score":0.062806666},"labels":[],"label_agreement":null},{"id":"W2200810224","doi":"10.1007/978-3-642-11819-7_12","title":"Application of Hidden Topic Markov Models on Spoken Dialogue Systems","year":2010,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Computer science; Partially observable Markov decision process; Sentence; Hidden Markov model; Artificial intelligence; Natural language processing; Latent Dirichlet allocation; Domain (mathematical analysis); Topic model; Speech recognition; Markov chain; Markov model; Machine learning; Mathematics","score_opus":0.030757061914135134,"score_gpt":0.26050149474606143,"score_spread":0.2297444328319263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2200810224","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012624856,0.0024111911,0.97956026,0.00053358317,0.00017984577,0.000033366043,0.00010971054,0.0007520546,0.0037951742],"genre_scores_gemma":[0.61641246,0.0051529123,0.3648907,0.00022778641,0.00063457654,0.00015144183,0.0007112076,0.00048016384,0.01133873],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99797183,0.0013659771,0.00008240355,0.00019182364,0.0003229348,0.00006498398],"domain_scores_gemma":[0.9909451,0.00816917,0.000099197074,0.00029730573,0.00042275296,0.000066450135],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022238428,0.0007208322,0.0011652207,0.0005910058,0.00038902546,0.0016339778,0.0009848403,0.001203678,0.0031976448],"category_scores_gemma":[0.011425753,0.0006538745,0.0007983989,0.0010821105,0.0004690089,0.0019664313,0.001443582,0.0014778762,0.00087662716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0003364668,0.0001261676,0.00084726734,0.000408451,0.00024482727,0.00023098235,0.0006321711,0.49433354,0.0064572645,0.08559355,0.005072016,0.40571725],"study_design_scores_gemma":[0.000009005845,0.000015689944,0.00011430359,0.000010588896,0.000014257819,0.000018727505,0.00002460234,0.97636753,0.00078577583,0.021342788,0.0012877919,0.000009021068],"about_ca_topic_score_codex":0.0047072084,"about_ca_topic_score_gemma":0.0030798877,"teacher_disagreement_score":0.0047072084,"about_ca_system_score_codex":0.0006405422,"about_ca_system_score_gemma":0.00077721267,"threshold_uncertainty_score":0.01176095},"labels":[],"label_agreement":null},{"id":"W2209938461","doi":"10.20380/gi2015.18","title":"TandemTable: supporting conversations and language learning using a multi-touch digital table","year":2015,"lang":"en","type":"article","venue":"e-scholar@UOIT (University of Ontario Institute of Technology)","topic":"Speech and dialogue systems","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":"Ontario Tech University","funders":"","keywords":"Computer science; Conversation; Variety (cybernetics); Human–computer interaction; Focus (optics); Table (database); Exploratory research; Collaborative learning; Multimedia; Language acquisition; World Wide Web; Knowledge management; Artificial intelligence; Mathematics education; Communication; Psychology","score_opus":0.02566398069698202,"score_gpt":0.22884753463073815,"score_spread":0.20318355393375612,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2209938461","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.44383007,0.002278131,0.49554905,0.0009969935,0.00046926874,0.001174257,0.0017186644,0.023048442,0.030935194],"genre_scores_gemma":[0.71759546,0.0007994932,0.24886176,0.00064330257,0.00018597073,0.0011193192,0.0012998305,0.00069260976,0.028802237],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9995135,0.00012343824,0.000026071526,0.00012856718,0.0001396739,0.000068796115],"domain_scores_gemma":[0.9988285,0.0005545869,0.00006220062,0.000112092195,0.00008201099,0.00036071072],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00050312787,0.0007183525,0.00036151282,0.00040979515,0.0005719782,0.0015199886,0.0016919441,0.0012016526,0.021409085],"category_scores_gemma":[0.0019271582,0.00030354064,0.0004591514,0.0002721406,0.00041512933,0.0019702232,0.0032212941,0.0005481719,0.0034812666],"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":[0.0028879645,0.0010204506,0.004941033,0.0014753767,0.0001139624,0.001844637,0.008757452,0.003403991,0.30158058,0.003309746,0.02738663,0.64327824],"study_design_scores_gemma":[0.0020147762,0.012981543,0.038195115,0.0010567077,0.00059996906,0.012093409,0.01323782,0.11232611,0.23795871,0.009031331,0.55948806,0.0010165826],"about_ca_topic_score_codex":0.0008307347,"about_ca_topic_score_gemma":0.0015548844,"teacher_disagreement_score":0.021409085,"about_ca_system_score_codex":0.00020675163,"about_ca_system_score_gemma":0.00045618133,"threshold_uncertainty_score":0.07162058},"labels":[],"label_agreement":null},{"id":"W2219902290","doi":"10.1145/2628363.2645671","title":"Speech-based interaction","year":2014,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Modalities; Computer science; Focus (optics); Modality (human–computer interaction); Natural (archaeology); Natural language; Human–computer interaction; Cognition; Natural language processing; Psychology","score_opus":0.014100813886351808,"score_gpt":0.2365950245201681,"score_spread":0.22249421063381628,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2219902290","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":[0.046793036,0.02376818,0.44317135,0.0046492117,0.0041973935,0.0007389139,0.0032406622,0.008773215,0.46466812],"genre_scores_gemma":[0.6609639,0.012140504,0.12591273,0.0047167446,0.001494152,0.0006007031,0.003937909,0.0012334152,0.189],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99876523,0.00036239185,0.00006906641,0.00021237544,0.0005143308,0.000076667195],"domain_scores_gemma":[0.9986828,0.0006832858,0.00005773574,0.00016023288,0.00033885316,0.000077130564],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008332252,0.00065644825,0.00046888395,0.0007173215,0.0006485609,0.0027425117,0.000813755,0.0015979314,0.044413913],"category_scores_gemma":[0.00391329,0.00016151146,0.000391523,0.00060023,0.0004888195,0.0015088782,0.001942413,0.00062822516,0.020017399],"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":[0.0006937202,0.00016249542,0.0012020034,0.001976796,0.000111639085,0.00086440984,0.002463125,0.0023218817,0.122649714,0.037183117,0.106313996,0.7240571],"study_design_scores_gemma":[0.00014778541,0.00065507746,0.007784632,0.0009989076,0.0002117132,0.0050185644,0.0016120115,0.029826203,0.053524777,0.059130598,0.8408892,0.00020056134],"about_ca_topic_score_codex":0.00076030206,"about_ca_topic_score_gemma":0.00083937723,"teacher_disagreement_score":0.044413913,"about_ca_system_score_codex":0.00035604753,"about_ca_system_score_gemma":0.0004285392,"threshold_uncertainty_score":0.14857936},"labels":[],"label_agreement":null},{"id":"W2222108608","doi":"10.1145/2678025.2716263","title":"Speech-based Interaction","year":2015,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Modalities; Computer science; Modality (human–computer interaction); Focus (optics); Natural (archaeology); Natural language; Human–computer interaction; Contrast (vision); Natural language processing; Artificial intelligence; Sociology","score_opus":0.05868022331432372,"score_gpt":0.27831212364404023,"score_spread":0.21963190032971652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2222108608","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":[0.03773672,0.033198383,0.4268006,0.0052816756,0.0039108745,0.0005057841,0.0025256972,0.007895097,0.4821452],"genre_scores_gemma":[0.6300136,0.015850559,0.12196479,0.0046562483,0.0019351862,0.0005116044,0.0030292273,0.0011128917,0.2209259],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99892455,0.00031595005,0.00005255339,0.0001910307,0.00045513603,0.000060845498],"domain_scores_gemma":[0.9990741,0.0005108255,0.0000438071,0.00010669117,0.00020016312,0.0000642662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007728854,0.00063780765,0.00041683923,0.000703619,0.0006018304,0.0027926285,0.00072546914,0.0015403755,0.04315578],"category_scores_gemma":[0.0027900059,0.00014669543,0.00034062917,0.00059250946,0.0005861539,0.0015509858,0.0018962377,0.0006067465,0.01795167],"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":[0.0004834714,0.00012368709,0.0008393017,0.0019839813,0.00009894673,0.0006662172,0.0023783934,0.001818822,0.10470658,0.05538244,0.10286362,0.7286545],"study_design_scores_gemma":[0.00008452551,0.00043906478,0.004970364,0.000803136,0.00012889536,0.0031575633,0.0012574182,0.018100956,0.03397364,0.06181679,0.8751359,0.00013176013],"about_ca_topic_score_codex":0.00072504894,"about_ca_topic_score_gemma":0.00083808484,"teacher_disagreement_score":0.04315578,"about_ca_system_score_codex":0.00037279935,"about_ca_system_score_gemma":0.00036099402,"threshold_uncertainty_score":0.1443705},"labels":[],"label_agreement":null},{"id":"W2250615590","doi":"10.18653/v1/w15-4724","title":"Narrative Generation from Extracted Associations","year":2015,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 de Montréal; Centre for Disability Prevention and Rehabilitation","funders":"","keywords":"Exploit; Computer science; Coherence (philosophical gambling strategy); Narrative; Rhetorical question; Domain (mathematical analysis); Artificial intelligence; Natural language processing; Data mining; Data science; Linguistics; Mathematics; Computer security; Statistics","score_opus":0.09369787511827872,"score_gpt":0.27880537662306754,"score_spread":0.18510750150478883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2250615590","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026856204,0.0006931908,0.9386152,0.00059551804,0.00052046333,0.00070815923,0.0077806055,0.006624274,0.01760631],"genre_scores_gemma":[0.14995086,0.00069615024,0.81945246,0.00011484431,0.00016711836,0.0008157351,0.016576037,0.0012317983,0.010995045],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9976545,0.00066158554,0.0002380433,0.00064389483,0.00070468377,0.000097287775],"domain_scores_gemma":[0.9932474,0.0040073846,0.00047314074,0.0008087709,0.0013284798,0.0001347585],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025115316,0.001466566,0.0005722212,0.0031004883,0.00088145374,0.0023379994,0.0013768814,0.0007830812,0.01665087],"category_scores_gemma":[0.01467176,0.00067524315,0.0010993796,0.002405195,0.0004295101,0.002384701,0.0028213528,0.0010793838,0.0062028323],"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":[0.0007571339,0.00020958284,0.0062443297,0.0024124172,0.0001959234,0.0026150616,0.0062868926,0.018209767,0.030524101,0.08366437,0.046962444,0.8019179],"study_design_scores_gemma":[0.00029270528,0.00037992533,0.00488177,0.001015233,0.0004896994,0.0021578216,0.004348293,0.31458673,0.08381538,0.14573963,0.4420705,0.00022240021],"about_ca_topic_score_codex":0.0008546912,"about_ca_topic_score_gemma":0.0013413924,"teacher_disagreement_score":0.01665087,"about_ca_system_score_codex":0.0005533443,"about_ca_system_score_gemma":0.0015362003,"threshold_uncertainty_score":0.055702746},"labels":[],"label_agreement":null},{"id":"W2251296238","doi":"10.3115/v1/w14-1903","title":"Dialogue Strategy Learning in Healthcare: A Systematic Approach for Learning Dialogue Models from Data","year":2014,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Computer science; Health care; Knowledge management; Data science; Artificial intelligence; Data modeling; Software engineering; Political science","score_opus":0.08129867465270009,"score_gpt":0.27667302674773014,"score_spread":0.19537435209503007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2251296238","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":[0.002177401,0.00028742597,0.9959111,0.0002758629,0.000014071562,0.00017913904,0.00015988208,0.000732504,0.0002626259],"genre_scores_gemma":[0.08651494,0.00033629846,0.91049606,0.00022668151,0.000044174645,0.00072204246,0.0010165431,0.00015152495,0.0004917449],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.98248726,0.012832312,0.0009526338,0.0021762336,0.0013272953,0.00022412851],"domain_scores_gemma":[0.96828866,0.025235364,0.0012777252,0.0027198608,0.001980081,0.0004983892],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014461404,0.0022139782,0.0017780843,0.0033033234,0.0008577777,0.0031249153,0.0036643874,0.002462439,0.0016183725],"category_scores_gemma":[0.03824185,0.0014546349,0.002314308,0.0015521869,0.0022414587,0.0040248437,0.0038127983,0.004714148,0.0009530912],"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":[0.00036848575,0.0009771255,0.00803417,0.002202526,0.0008747593,0.00024290099,0.0030674115,0.1761616,0.013429083,0.043641232,0.00726868,0.74373204],"study_design_scores_gemma":[0.00006803686,0.00024572597,0.0010429434,0.00024823323,0.00007747516,0.00013752411,0.0003615605,0.91084397,0.0072846627,0.072316326,0.0072849165,0.000088628214],"about_ca_topic_score_codex":0.0029500113,"about_ca_topic_score_gemma":0.0054412954,"teacher_disagreement_score":0.014461404,"about_ca_system_score_codex":0.002015205,"about_ca_system_score_gemma":0.003183497,"threshold_uncertainty_score":0.07648009},"labels":[],"label_agreement":null},{"id":"W2251865034","doi":"10.63317/4mqqmrwjqisu","title":"A multimodal interpreter for 3D visualization and animation of verbal concepts","year":2014,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Polytechnique Montréal","funders":"","keywords":"Computer science; FrameNet; Natural language processing; Verb; Artificial intelligence; Representation (politics); Visualization; Object (grammar); Animation; Path (computing); Parsing; Programming language; Computer graphics (images)","score_opus":0.010429033029610608,"score_gpt":0.28467125064043336,"score_spread":0.27424221761082274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2251865034","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":[0.02442468,0.00024853973,0.92865,0.00024188953,0.00018280944,0.00037297743,0.0010892901,0.0341162,0.010673516],"genre_scores_gemma":[0.1983886,0.00043897433,0.7709445,0.00031652272,0.000087730965,0.000723541,0.0018011468,0.0049810098,0.022318086],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997179,0.00008452109,0.00002506376,0.00005531379,0.000089676185,0.000027618717],"domain_scores_gemma":[0.9992693,0.00041885924,0.000025333762,0.000076563,0.00012268875,0.00008720669],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008728547,0.00090782123,0.00065818697,0.00073181366,0.0005180205,0.0018569698,0.0009967644,0.001203075,0.036513623],"category_scores_gemma":[0.002883829,0.00055642636,0.0006976534,0.0003424085,0.0006100147,0.0013891219,0.0025376363,0.0009835876,0.005616965],"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":[0.0021572364,0.00029062154,0.0012954194,0.0012467125,0.00014658927,0.0022274589,0.0055361376,0.011047627,0.3229617,0.036215965,0.045337018,0.57153755],"study_design_scores_gemma":[0.00059504487,0.0006482941,0.0025102666,0.0004431412,0.0002804586,0.0023390495,0.001517716,0.49594387,0.25259182,0.030137876,0.21267873,0.00031376284],"about_ca_topic_score_codex":0.000848183,"about_ca_topic_score_gemma":0.0012498903,"teacher_disagreement_score":0.036513623,"about_ca_system_score_codex":0.00030927398,"about_ca_system_score_gemma":0.0005738944,"threshold_uncertainty_score":0.12215024},"labels":[],"label_agreement":null},{"id":"W22543326","doi":"10.12927/hcpap.2013.22860","title":"DERIVING THE OPTIMAL MODALITY COMBINATION FOR SEARCHING IN MULTIDIMENSIONAL DATABASES","year":2003,"lang":"en","type":"article","venue":"ICWI","topic":"Speech and dialogue systems","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; Modality (human–computer interaction); Modalities; Set (abstract data type); Haptic technology; Human–computer interaction; Database; Artificial intelligence; Information retrieval","score_opus":0.04985782978830274,"score_gpt":0.304777095552146,"score_spread":0.2549192657638433,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W22543326","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037337568,0.0017252079,0.9482476,0.0013665335,0.00008113025,0.0004474059,0.0013770268,0.0020321123,0.007385322],"genre_scores_gemma":[0.16935582,0.000900354,0.82574314,0.00020712703,0.0000687104,0.00043519595,0.0015548245,0.0002502915,0.0014845227],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9907126,0.0032472238,0.0014822265,0.0019330698,0.00196638,0.00065860717],"domain_scores_gemma":[0.98117197,0.013897011,0.00052079506,0.0020675822,0.0018872177,0.0004553511],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007065702,0.0013305664,0.0030567904,0.008930959,0.0020259705,0.007038423,0.003099713,0.0032266118,0.007777949],"category_scores_gemma":[0.05407272,0.001236044,0.0027957708,0.0072418735,0.0022932058,0.015331032,0.0050677485,0.002293661,0.002793112],"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":[0.0006905728,0.0003871044,0.008395983,0.0012166392,0.00027923318,0.0005123967,0.0017798764,0.053051267,0.007059246,0.063744634,0.010670213,0.85221285],"study_design_scores_gemma":[0.00011542975,0.00036642206,0.0024548396,0.0005397445,0.0003836988,0.0013636751,0.0035918835,0.7342378,0.019739823,0.21922144,0.017820198,0.00016501373],"about_ca_topic_score_codex":0.0062351814,"about_ca_topic_score_gemma":0.008461166,"teacher_disagreement_score":0.008930959,"about_ca_system_score_codex":0.0024174373,"about_ca_system_score_gemma":0.003940521,"threshold_uncertainty_score":0.037367404},"labels":[],"label_agreement":null},{"id":"W2272068344","doi":"10.1016/j.cognition.2015.12.008","title":"Perspective-taking behavior as the probabilistic weighing of multiple domains","year":2016,"lang":"en","type":"article","venue":"Cognition","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":89,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Nuance Communications (Canada); University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology; Perspective (graphical); Cognitive psychology; Common ground; Point (geometry); Probabilistic logic; Process (computing); Perspective-taking; Bayesian probability; Cognitive science; Test (biology); Resolution (logic); Artificial intelligence; Social psychology; Computer science; Mathematics","score_opus":0.02794349954596962,"score_gpt":0.26967123628200684,"score_spread":0.24172773673603723,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2272068344","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4316034,0.00052792195,0.5312374,0.0013868255,0.00008137311,0.000091409835,0.00021119163,0.00033589196,0.034524538],"genre_scores_gemma":[0.96410865,0.00012009789,0.033726614,0.00005891836,0.000025593637,0.000027988686,0.00007153667,0.000043703476,0.0018169434],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99779,0.0009339117,0.000074611504,0.00051897694,0.00053675316,0.0001457124],"domain_scores_gemma":[0.99025387,0.0063031334,0.0010774621,0.0010227542,0.0007305615,0.0006122151],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003319374,0.00045755334,0.00044013045,0.0010176732,0.000586634,0.0037237515,0.0010864784,0.0010909452,0.0056025935],"category_scores_gemma":[0.021706278,0.00073083694,0.0008002052,0.000763293,0.0012005954,0.0052842605,0.0018137374,0.0018171791,0.00045674498],"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":[0.00072800176,0.00029487192,0.05336771,0.0002989513,0.0008555016,0.0009829177,0.006048452,0.07762879,0.04356994,0.6511627,0.0019751035,0.16308703],"study_design_scores_gemma":[0.000051537732,0.00028207334,0.041933138,0.000057831207,0.00028156993,0.00061413203,0.001301965,0.3783255,0.00625057,0.5679921,0.0027506326,0.00015896632],"about_ca_topic_score_codex":0.0024430891,"about_ca_topic_score_gemma":0.0029448743,"teacher_disagreement_score":0.0056025935,"about_ca_system_score_codex":0.00093146734,"about_ca_system_score_gemma":0.000669944,"threshold_uncertainty_score":0.018742561},"labels":[],"label_agreement":null},{"id":"W2278427399","doi":"10.4018/978-1-4666-0137-6.ch011","title":"Sustained Learning in 4th and 5th Graders but not 7th Graders","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Speech and dialogue systems","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":"Bow Valley College; Memorial University of Newfoundland","funders":"","keywords":"Plural; Modality (human–computer interaction); Animation; Mathematics education; Psychology; Computer science; Cognitive psychology; Linguistics; Artificial intelligence; Computer graphics (images)","score_opus":0.02396520182410185,"score_gpt":0.2401506078050172,"score_spread":0.21618540598091535,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2278427399","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":[0.99225736,0.0007060163,0.00016907087,0.00013997553,0.000053698932,0.000022435568,0.00021300915,0.000025737423,0.00641279],"genre_scores_gemma":[0.9667904,0.00051433296,0.000627721,0.00014781376,0.000019314866,0.000055010445,0.00046427664,0.00001791588,0.031363178],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9987104,0.0001305384,0.00011723213,0.00030157718,0.00046615378,0.00027415843],"domain_scores_gemma":[0.99634415,0.0011283742,0.00079764356,0.00033276618,0.0006901608,0.0007067822],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016575758,0.00048957655,0.0013040998,0.0010861399,0.0009691885,0.0056807413,0.0009879562,0.0012953442,0.01765277],"category_scores_gemma":[0.003938919,0.00038886824,0.0005828405,0.000504648,0.0009703726,0.0014740623,0.0012761051,0.0012535063,0.0051747295],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001978954,0.0055189463,0.54363126,0.0011291339,0.0003277995,0.0051280474,0.1043374,0.000581284,0.045976568,0.008386162,0.012919775,0.27008465],"study_design_scores_gemma":[0.000129918,0.00476538,0.9185906,0.0005277532,0.00021912594,0.0018169556,0.035263978,0.00080795534,0.008041342,0.0039984924,0.025730962,0.00010765466],"about_ca_topic_score_codex":0.0060852347,"about_ca_topic_score_gemma":0.012747714,"teacher_disagreement_score":0.01765277,"about_ca_system_score_codex":0.00074351823,"about_ca_system_score_gemma":0.0006710834,"threshold_uncertainty_score":0.059054434},"labels":[],"label_agreement":null},{"id":"W2289240769","doi":"","title":"Rörelseanalys med tillämpning av inversdynamik - en pilotstudie på frisk labrador retriever","year":2010,"lang":"sv","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Labrador Retriever; Medicine; Surgery","score_opus":0.012899080750286184,"score_gpt":0.24071619031675315,"score_spread":0.22781710956646697,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2289240769","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":[0.7184431,0.0032916865,0.19071697,0.0016437091,0.00067371666,0.0009893484,0.0035578825,0.007905213,0.07277834],"genre_scores_gemma":[0.74013984,0.0022673332,0.120130785,0.00044678297,0.00017824791,0.0005818048,0.003866815,0.003202213,0.12918618],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9987147,0.00028123774,0.00007185441,0.00028290445,0.0005341562,0.00011504631],"domain_scores_gemma":[0.9985147,0.00064175634,0.000056438454,0.00032982216,0.00033877674,0.00011854645],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021702203,0.0010644586,0.0007640193,0.0006397049,0.0010169607,0.0029076901,0.0014309373,0.0013375335,0.03686644],"category_scores_gemma":[0.003854836,0.0004303189,0.00067008124,0.00038989258,0.00096406846,0.002329834,0.002021596,0.0013407309,0.01676288],"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":[0.0027380495,0.0014555323,0.0040833796,0.0012373104,0.00014957377,0.0018236871,0.017883927,0.0108742295,0.24348855,0.005026447,0.015004146,0.6962352],"study_design_scores_gemma":[0.0005492928,0.006744652,0.022679938,0.00071529805,0.0005899479,0.005095254,0.022436434,0.037413266,0.41278645,0.0092037665,0.4812341,0.00055156363],"about_ca_topic_score_codex":0.003997815,"about_ca_topic_score_gemma":0.0037146448,"teacher_disagreement_score":0.03686644,"about_ca_system_score_codex":0.00053933694,"about_ca_system_score_gemma":0.0009585836,"threshold_uncertainty_score":0.12333059},"labels":[],"label_agreement":null},{"id":"W2293888193","doi":"","title":"LRRP SpeechWebs","year":2004,"lang":"en","type":"article","venue":"Conference on Communication Networks and Services Research","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Computer science; Hyperlink; Architecture; The Internet; Speech analytics; World Wide Web; Web page; Speech synthesis; Speech recognition; Speech corpus","score_opus":0.0761207002343366,"score_gpt":0.35117303613222295,"score_spread":0.27505233589788636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2293888193","genre_codex":"software","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":[0.009363915,0.0010678349,0.32918945,0.0014075325,0.0007110401,0.0005243561,0.0055026514,0.44014522,0.21208802],"genre_scores_gemma":[0.16864735,0.0021268877,0.24630465,0.0031056681,0.0008124343,0.001156033,0.050041974,0.055103514,0.4727015],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9978235,0.00039642985,0.0001797907,0.00033969048,0.001010615,0.00025010074],"domain_scores_gemma":[0.99747604,0.00041064012,0.00013172158,0.0009902557,0.0006651783,0.00032611476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016312918,0.0010669515,0.0007232943,0.001751954,0.0009446695,0.0042789113,0.0029467035,0.0019045669,0.10015687],"category_scores_gemma":[0.0036202418,0.0010146202,0.0008016717,0.0012079172,0.00082062586,0.005533842,0.0038596694,0.0019654077,0.09522907],"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":[0.0010043337,0.00024553353,0.001333491,0.00073416,0.00007229037,0.0010113381,0.0014249401,0.0027574804,0.022353977,0.06818126,0.47085226,0.43002895],"study_design_scores_gemma":[0.0000676711,0.000075697746,0.0005398605,0.000067510795,0.000023452818,0.0004634255,0.00011747789,0.011703351,0.01155341,0.007293749,0.96804047,0.000054004],"about_ca_topic_score_codex":0.0051342156,"about_ca_topic_score_gemma":0.003665385,"teacher_disagreement_score":0.10015687,"about_ca_system_score_codex":0.0012506166,"about_ca_system_score_gemma":0.0013845969,"threshold_uncertainty_score":0.3350581},"labels":[],"label_agreement":null},{"id":"W2328394646","doi":"10.1097/01.hj.0000292838.52117.b1","title":"SII PREDICTIONS OF AIDED SPEECH RECOGNITION","year":2004,"lang":"en","type":"article","venue":"The Hearing Journal","topic":"Speech and dialogue systems","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":"Centre for Disability Prevention and Rehabilitation","funders":"","keywords":"Audiology; Hearing loss; Consonant; Speech perception; Psychology; QUIET; Hearing aid; Population; Perception; Speech recognition; Medicine; Computer science","score_opus":0.04453933837607941,"score_gpt":0.2514723926271165,"score_spread":0.2069330542510371,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2328394646","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":[0.99172604,0.00011202714,0.0058642547,0.00002744809,0.000011300956,0.000013636016,0.00044918805,0.00016046198,0.001635634],"genre_scores_gemma":[0.99801034,0.000030021247,0.0012039179,0.000006552889,0.0000044342573,0.000007881403,0.00048458006,0.000011744677,0.00024065224],"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996308,0.00007332925,0.00003437122,0.000096648124,0.00011589207,0.000048961236],"domain_scores_gemma":[0.9966786,0.0019593616,0.00041015298,0.00015007329,0.00052318024,0.000278697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010985761,0.0006958824,0.0002827052,0.00087686855,0.00014225011,0.00058737077,0.00021888183,0.00034272234,0.0013553442],"category_scores_gemma":[0.007915713,0.00023381413,0.00037075594,0.00016992958,0.00023692784,0.00048267137,0.00044047608,0.00033565608,0.0012343427],"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":[0.00059445447,0.00007085062,0.9432172,0.000033726865,0.00007860951,0.00020464485,0.0002769743,0.013512687,0.00868386,0.00020275546,0.00045170047,0.032672547],"study_design_scores_gemma":[0.000021769412,0.00045894991,0.85737056,0.000015876192,0.00003940702,0.0007318669,0.00031109017,0.13175887,0.008248051,0.00053018663,0.00048043075,0.00003286099],"about_ca_topic_score_codex":0.0025129737,"about_ca_topic_score_gemma":0.0019914082,"teacher_disagreement_score":0.0025129737,"about_ca_system_score_codex":0.00024466164,"about_ca_system_score_gemma":0.00019474905,"threshold_uncertainty_score":0.005809903},"labels":[],"label_agreement":null},{"id":"W2330702035","doi":"10.1097/01.hj.0000434657.23951.54","title":"In Noise, a Spouseʼs Voice is Better Tracked, and Ignored","year":2013,"lang":"en","type":"article","venue":"The Hearing Journal","topic":"Speech and dialogue systems","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":"Spouse; Active listening; Psychology; Cognition; Cognitive resource theory; Task (project management); Social psychology; Sociology; Communication","score_opus":0.018616684528210692,"score_gpt":0.2306158259231933,"score_spread":0.2119991413949826,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2330702035","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":[0.57499826,0.004591325,0.008647725,0.014698686,0.004493508,0.00007747916,0.00077565556,0.0017089902,0.39000842],"genre_scores_gemma":[0.80061173,0.002673576,0.005873745,0.0064053386,0.0005504772,0.000033994984,0.0004486356,0.00036450726,0.18303803],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99980754,0.00003728255,0.0000109854645,0.000046735153,0.00006555534,0.000031960393],"domain_scores_gemma":[0.9996152,0.000077289944,0.000052945157,0.000046164612,0.0000869747,0.00012137426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003819151,0.00030350938,0.00023903963,0.00039789052,0.0011529356,0.0018799684,0.00021704595,0.0006597139,0.11436142],"category_scores_gemma":[0.0013364574,0.00016677311,0.00033095063,0.00020305839,0.0005649899,0.0014820505,0.0009171898,0.0006187167,0.020987477],"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":[0.0010394196,0.000774448,0.044264127,0.0005906449,0.00012623072,0.0025947762,0.013017411,0.00021535385,0.050920554,0.0033672315,0.18099277,0.702097],"study_design_scores_gemma":[0.0001669056,0.0016314586,0.22636265,0.00067449623,0.00027637614,0.0094058355,0.039953668,0.0011297959,0.026548175,0.005641905,0.68798494,0.00022378741],"about_ca_topic_score_codex":0.0045209853,"about_ca_topic_score_gemma":0.0083077215,"teacher_disagreement_score":0.11436142,"about_ca_system_score_codex":0.00028009585,"about_ca_system_score_gemma":0.00026757363,"threshold_uncertainty_score":0.38257706},"labels":[],"label_agreement":null},{"id":"W2333701406","doi":"10.1061/40794(179)102","title":"Speech — Enabled Handheld Computing for Fieldwork","year":2005,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of New Brunswick","funders":"National Research Council Canada; U.S. Department of Transportation","keywords":"Mobile device; Computer science; Mobile phone; Stylus; Field (mathematics); Human–computer interaction; Mobile computing; Modalities; Multimodal interaction; Mobile telephony; Multimedia; Phone; Mobile radio; Telecommunications; World Wide Web; Computer vision","score_opus":0.018094940748804317,"score_gpt":0.2535905572690664,"score_spread":0.23549561652026205,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2333701406","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.07238459,0.033101488,0.6876605,0.0040285457,0.0020684854,0.00057592586,0.0009520547,0.012879239,0.18634915],"genre_scores_gemma":[0.602496,0.009680627,0.24189363,0.0017838124,0.0005616064,0.00038509298,0.00089208066,0.0004501004,0.14185701],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979514,0.000045855562,0.000011119039,0.000037811056,0.000088946246,0.000021228638],"domain_scores_gemma":[0.99971586,0.000107594366,0.000021691723,0.00004623553,0.00007613113,0.000032418335],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002068226,0.00046502196,0.00022575381,0.00045798358,0.00050677964,0.0008718611,0.0007493222,0.00079807633,0.015945535],"category_scores_gemma":[0.000611495,0.0001590265,0.0001789155,0.00048658435,0.00025352085,0.0007967511,0.000632189,0.00045441338,0.0046534333],"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":[0.00060451956,0.000094340896,0.0007820539,0.0006997305,0.000026564103,0.0011053283,0.00049815036,0.0028585563,0.110517755,0.022261318,0.052156694,0.8083949],"study_design_scores_gemma":[0.00018724457,0.0005044428,0.003663193,0.0004936988,0.00009142837,0.0026469948,0.0006306656,0.04746277,0.09914429,0.024176111,0.8208807,0.0001184597],"about_ca_topic_score_codex":0.0010960439,"about_ca_topic_score_gemma":0.0016581133,"teacher_disagreement_score":0.015945535,"about_ca_system_score_codex":0.00038300268,"about_ca_system_score_gemma":0.00034558546,"threshold_uncertainty_score":0.053343117},"labels":[],"label_agreement":null},{"id":"W2340026042","doi":"10.14288/1.0051885","title":"A prolog implementation of a subset of Marcus’ parser and its relation to the handling of extragrammatical input","year":2010,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Relation (database); Parsing; Prolog; Programming language; Computer science; Natural language processing; Database","score_opus":0.010349824232588269,"score_gpt":0.20056211153574854,"score_spread":0.19021228730316028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2340026042","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":[0.028534466,0.0001270255,0.92025626,0.00066616543,0.00008827695,0.00020117885,0.0005709258,0.03346755,0.016088162],"genre_scores_gemma":[0.19931524,0.00017642195,0.7880709,0.00053605315,0.000050250146,0.00016170178,0.0007446117,0.0016630797,0.009281746],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99889827,0.00026275904,0.00009635026,0.00027924366,0.00032535495,0.00013807332],"domain_scores_gemma":[0.99869484,0.0004981478,0.00013954114,0.0003363113,0.0002758231,0.000055289765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014648484,0.00045241113,0.0003848464,0.00057244266,0.0009254219,0.0017862135,0.0014151332,0.00059868273,0.0046701315],"category_scores_gemma":[0.0035778913,0.0009812472,0.0007256776,0.0005642591,0.0009316399,0.0022196558,0.00082488055,0.0015362706,0.0016902616],"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":[0.0013234186,0.00041121643,0.004075178,0.000571677,0.000104126695,0.0011688175,0.0023067715,0.033998493,0.059888545,0.33581698,0.03834724,0.5219876],"study_design_scores_gemma":[0.00035647023,0.0006978403,0.0034139734,0.00020688762,0.0002287394,0.0019451891,0.00046374692,0.55434984,0.120723374,0.09535458,0.22195423,0.0003051114],"about_ca_topic_score_codex":0.0062567876,"about_ca_topic_score_gemma":0.0062998314,"teacher_disagreement_score":0.0062567876,"about_ca_system_score_codex":0.0008837045,"about_ca_system_score_gemma":0.0029884272,"threshold_uncertainty_score":0.015623212},"labels":[],"label_agreement":null},{"id":"W2342984595","doi":"10.3166/ria.29.655-683","title":"Extraction de motifs dialogiques bidimensionnels","year":2015,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":5,"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":"Institut National des Sciences Appliquées Rouen; Agence Nationale de la Recherche; Indian National Science Academy","keywords":"Computer science","score_opus":0.12012536034511397,"score_gpt":0.31547526913226365,"score_spread":0.1953499087871497,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2342984595","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.217427,0.0033910864,0.7502701,0.00044429794,0.00042071784,0.0005145033,0.007094193,0.010268098,0.010169913],"genre_scores_gemma":[0.49244452,0.0011607821,0.4748327,0.00012783284,0.00031507108,0.00048116976,0.011804417,0.0008288132,0.018004669],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992667,0.0001511271,0.00007676738,0.00028775207,0.00014537203,0.0000723418],"domain_scores_gemma":[0.99890614,0.0005563008,0.00006890581,0.00008321747,0.00029458257,0.00009082054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000515676,0.0011862235,0.0011088996,0.003395952,0.0009498866,0.0018068375,0.00056346797,0.0012224545,0.008977271],"category_scores_gemma":[0.0025687548,0.00042527606,0.0010621394,0.0016668101,0.0003471212,0.0010640206,0.00086598756,0.0008219222,0.0044696652],"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":[0.0018799026,0.0002742421,0.0057536927,0.0011664925,0.00018809526,0.0010558128,0.0005713516,0.005810552,0.3131043,0.007104076,0.009456012,0.6536355],"study_design_scores_gemma":[0.00050949753,0.0011930967,0.048063684,0.0005928967,0.0006853394,0.004791285,0.0026075537,0.6162679,0.20820667,0.024559544,0.09229215,0.00023037339],"about_ca_topic_score_codex":0.00212084,"about_ca_topic_score_gemma":0.0036133411,"teacher_disagreement_score":0.008977271,"about_ca_system_score_codex":0.00038038573,"about_ca_system_score_gemma":0.0008484708,"threshold_uncertainty_score":0.03003192},"labels":[],"label_agreement":null},{"id":"W2346204935","doi":"10.1145/2851581.2856506","title":"Designing Speech and Multimodal Interactions for Mobile, Wearable, and Pervasive Applications","year":2016,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Manitoba; University of Toronto","funders":"","keywords":"Human–computer interaction; Computer science; Multimodal interaction; Modalities; Wearable computer; Gesture; Usability; Wearable technology; Leverage (statistics); Modality (human–computer interaction); Multidisciplinary approach; Mobile device; Ubiquitous computing; Multimedia; Artificial intelligence; World Wide Web; Embedded system","score_opus":0.016803280782133473,"score_gpt":0.26614176890973984,"score_spread":0.24933848812760637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2346204935","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":[0.032932866,0.0023651146,0.953435,0.0013190656,0.00019099208,0.00053448457,0.00006940071,0.0012950777,0.007857891],"genre_scores_gemma":[0.18851551,0.0027845278,0.7971875,0.0005553426,0.00015910399,0.0011454636,0.00019985442,0.00053255435,0.008920079],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.997638,0.001482546,0.00013842959,0.00021764243,0.0003979194,0.00012544726],"domain_scores_gemma":[0.9978377,0.0015123285,0.00007871638,0.000106533334,0.00033031788,0.00013437722],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044602146,0.0013398093,0.0006387046,0.00067363394,0.001075426,0.0027826803,0.0011547089,0.0017482102,0.006066279],"category_scores_gemma":[0.00704867,0.00085643784,0.0009435051,0.000287375,0.0013890682,0.0035177795,0.002094795,0.0011177511,0.001800428],"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":[0.0005408252,0.0003712899,0.002155948,0.003750487,0.0002939269,0.002014955,0.023846528,0.025971834,0.34069693,0.055525254,0.020183854,0.5246482],"study_design_scores_gemma":[0.00040004044,0.002105931,0.006713952,0.0012608635,0.00072293595,0.0034610599,0.015971774,0.26250595,0.16563046,0.06578828,0.47498083,0.00045793492],"about_ca_topic_score_codex":0.00058127637,"about_ca_topic_score_gemma":0.001287389,"teacher_disagreement_score":0.006066279,"about_ca_system_score_codex":0.0005119689,"about_ca_system_score_gemma":0.00083192607,"threshold_uncertainty_score":0.02358818},"labels":[],"label_agreement":null},{"id":"W2358452666","doi":"","title":"Design and Implementation of a Natural Language Chat System Based on Statistical Learning","year":2008,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Speech and dialogue systems","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":"Computer science; Artificial intelligence; Natural language processing; Domain (mathematical analysis); Natural language; Markov chain; Line (geometry); Language model; Machine learning","score_opus":0.009232044120186784,"score_gpt":0.2531031988935618,"score_spread":0.24387115477337504,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2358452666","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":[0.020074774,0.000059971393,0.9324436,0.00014603468,0.00009327084,0.0008080349,0.00025249648,0.044669304,0.0014525015],"genre_scores_gemma":[0.3411501,0.00006595491,0.6475188,0.0002658087,0.0001013035,0.002520177,0.0014100263,0.0012460989,0.005721738],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99855214,0.00031668702,0.00012790639,0.00048087948,0.00037755715,0.00014468945],"domain_scores_gemma":[0.9974438,0.00080403424,0.00011805701,0.0004085437,0.00085483765,0.00037076723],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00221206,0.0008086036,0.0011309986,0.00090883597,0.0006336014,0.0010119911,0.003152431,0.0011360126,0.008041205],"category_scores_gemma":[0.003176757,0.00064554124,0.00055996305,0.00044951573,0.0005178578,0.0011589172,0.0008747573,0.0011432443,0.0043560904],"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":[0.0034458814,0.0028607792,0.009745892,0.0012684774,0.00047458994,0.0024541568,0.0015185328,0.07469865,0.33174378,0.018533578,0.029749114,0.5235066],"study_design_scores_gemma":[0.00053787226,0.00089429563,0.0035179069,0.000038013524,0.00016688429,0.0005374826,0.00011441569,0.85216177,0.117629394,0.00397265,0.020295601,0.00013361734],"about_ca_topic_score_codex":0.0016211786,"about_ca_topic_score_gemma":0.0008458412,"teacher_disagreement_score":0.008041205,"about_ca_system_score_codex":0.0006302473,"about_ca_system_score_gemma":0.0016026275,"threshold_uncertainty_score":0.02690053},"labels":[],"label_agreement":null},{"id":"W2394649188","doi":"","title":"Learning Grounded Communicative Intent from Human-Robot Dialog","year":2010,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Speech and dialogue systems","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 Alberta","funders":"","keywords":"Unobservable; Dialog box; Perception; Computer science; Robot; Human–computer interaction; Artificial intelligence; Cognitive science; Psychology","score_opus":0.17179679521865573,"score_gpt":0.36140449539049324,"score_spread":0.1896077001718375,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2394649188","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34188747,0.00044600636,0.6421614,0.0013586163,0.00006506492,0.00016348148,0.00031912324,0.0011792994,0.012419514],"genre_scores_gemma":[0.9635296,0.000120956734,0.033842787,0.00009732532,0.000016725962,0.00006259362,0.00025716404,0.000031828964,0.002041122],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99941206,0.00032577137,0.000022788347,0.00011072445,0.000078757315,0.00004992465],"domain_scores_gemma":[0.99680114,0.0024067115,0.0002036676,0.00027162555,0.0001737424,0.00014312952],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013977381,0.0006317914,0.00039244563,0.00037631308,0.00045859563,0.0010669901,0.00069784716,0.0008839248,0.002390672],"category_scores_gemma":[0.0088376505,0.0004958003,0.0005019057,0.00019419297,0.0011112563,0.0025298875,0.002088036,0.0016893873,0.0003856779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012979386,0.0005515808,0.015881924,0.00079958036,0.00021900814,0.0011426425,0.008236352,0.47901776,0.028446414,0.109497786,0.005715431,0.34919354],"study_design_scores_gemma":[0.000044222706,0.00025448846,0.0035453043,0.00005105803,0.000029232631,0.000103812185,0.0006579522,0.8762288,0.006250889,0.11026225,0.0025270113,0.000044932825],"about_ca_topic_score_codex":0.0017165215,"about_ca_topic_score_gemma":0.0025945443,"teacher_disagreement_score":0.002390672,"about_ca_system_score_codex":0.0005832198,"about_ca_system_score_gemma":0.00054250495,"threshold_uncertainty_score":0.007997632},"labels":[],"label_agreement":null},{"id":"W2396304330","doi":"","title":"Acquisition of Phrase Structure in an Artificial Visual Grammar","year":2013,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Speech and dialogue systems","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 Institutes of Health","keywords":"Noun phrase; Linguistics; Phrase; Determiner phrase; Phrase structure rules; Grammar; Syntax; Sentence; Word order; Artificial intelligence; Computer science; Learnability; Psychology; Natural language processing; Noun; Philosophy","score_opus":0.011469240347033503,"score_gpt":0.22092579342434182,"score_spread":0.20945655307730832,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2396304330","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":[0.9367951,0.00006039226,0.057579823,0.00017066461,0.00002604034,0.000082299,0.00009031038,0.0003590208,0.0048363325],"genre_scores_gemma":[0.9453284,0.00007811475,0.05272066,0.00013237502,0.000005080118,0.00010681379,0.00012877151,0.000062555766,0.0014372002],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99948525,0.00019625128,0.000035160792,0.0001438191,0.000111263835,0.000028170805],"domain_scores_gemma":[0.99779,0.0013632193,0.00026852675,0.00032579983,0.00015127695,0.00010107411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007587825,0.00025532173,0.00019887285,0.00020219825,0.00010906558,0.0005983282,0.0005008889,0.00042811557,0.0017077682],"category_scores_gemma":[0.0044441815,0.00023122651,0.0002471603,0.000090731766,0.0009928354,0.0012070201,0.0010437687,0.0006662326,0.00029384842],"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":[0.0002654868,0.0003169882,0.006586257,0.0005723724,0.00003602281,0.0006884601,0.004002634,0.005387289,0.88308156,0.019340565,0.000754816,0.07896758],"study_design_scores_gemma":[0.00068830996,0.005457873,0.05511904,0.00029399327,0.00013185751,0.0050785355,0.0030569506,0.15386449,0.5790265,0.1471871,0.04980817,0.0002871691],"about_ca_topic_score_codex":0.00025413677,"about_ca_topic_score_gemma":0.0003554542,"teacher_disagreement_score":0.0017077682,"about_ca_system_score_codex":0.00024119897,"about_ca_system_score_gemma":0.0002755107,"threshold_uncertainty_score":0.0057130456},"labels":[],"label_agreement":null},{"id":"W2396967310","doi":"","title":"A web-based phonetics tutor using generative CALL.","year":2013,"lang":"en","type":"article","venue":"Distributed Multimedia Systems","topic":"Speech and dialogue systems","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":"Queen's University","funders":"","keywords":"TUTOR; Computer science; Phonetics; Generative grammar; Human–computer interaction; Artificial intelligence; Natural language processing; Programming language; Linguistics","score_opus":0.021273016074938065,"score_gpt":0.24021498147721862,"score_spread":0.21894196540228056,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2396967310","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12345361,0.00034255197,0.58565086,0.0006662479,0.0005884789,0.0011022484,0.0014498114,0.22417821,0.062568],"genre_scores_gemma":[0.6317457,0.00019270339,0.25953934,0.0008195398,0.0002711325,0.00085776206,0.002676287,0.004146848,0.09975068],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99936384,0.00018156295,0.000042484982,0.00017030384,0.00017193542,0.00006987603],"domain_scores_gemma":[0.9986964,0.0004825229,0.00003589246,0.0001990371,0.00020858968,0.00037772063],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064262736,0.0007091698,0.00068886107,0.0005498407,0.0004811502,0.0014368999,0.0019526352,0.0017075756,0.04288083],"category_scores_gemma":[0.0035576103,0.00026809942,0.00033062237,0.00028833884,0.0003010322,0.0015391081,0.0027098518,0.0008935895,0.01935549],"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":[0.0037771123,0.0028700482,0.006155514,0.00055953965,0.00011726598,0.0026658552,0.0021843235,0.009653519,0.15684083,0.0060099238,0.055054214,0.7541119],"study_design_scores_gemma":[0.0024375098,0.0047571524,0.014814616,0.00026767977,0.0004746971,0.007254787,0.002490247,0.44425982,0.18153912,0.019319322,0.3218568,0.0005283285],"about_ca_topic_score_codex":0.000840768,"about_ca_topic_score_gemma":0.00080125855,"teacher_disagreement_score":0.04288083,"about_ca_system_score_codex":0.00028883875,"about_ca_system_score_gemma":0.0007545505,"threshold_uncertainty_score":0.14345068},"labels":[],"label_agreement":null},{"id":"W2402410010","doi":"","title":"Generating structure from experience: The role of memory in language.","year":2014,"lang":"en","type":"article","venue":"Cognitive Science","topic":"Speech and dialogue systems","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":"Computer science; Variety (cybernetics); Abstraction; Natural language processing; Universal Networking Language; Language identification; Natural language; Grammar; Linguistics; Artificial intelligence; Language model; Cognitive science; Comprehension approach; Psychology","score_opus":0.007016415500945548,"score_gpt":0.24851666255312582,"score_spread":0.24150024705218026,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402410010","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28543377,0.0332144,0.5347129,0.016143588,0.0008542104,0.0001406406,0.0008369171,0.0008450935,0.12781845],"genre_scores_gemma":[0.9412895,0.0065521193,0.043299496,0.00075053965,0.00027764856,0.00009475182,0.00042953496,0.000084833875,0.00722166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9996681,0.00010037145,0.000017540528,0.00010782003,0.00007357401,0.000032664713],"domain_scores_gemma":[0.9978089,0.0012760415,0.00024812386,0.00039723507,0.0001457039,0.00012408411],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00085832423,0.00039336516,0.00032461932,0.0009646308,0.0006197108,0.004036281,0.0011426868,0.0011846054,0.0046368563],"category_scores_gemma":[0.008128952,0.00031709677,0.0006305481,0.0009652283,0.0043471367,0.00949658,0.0021189575,0.0013310442,0.0006599111],"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":[0.00023831552,0.00008458124,0.0056837285,0.0005556745,0.00010787817,0.000777584,0.007720867,0.005525543,0.008089397,0.71725976,0.0051586702,0.24879812],"study_design_scores_gemma":[0.000020108875,0.000101970945,0.0037498996,0.00012152456,0.0000488886,0.00063169334,0.0010348212,0.011941751,0.0022342375,0.9667749,0.013299658,0.00004062345],"about_ca_topic_score_codex":0.0015831339,"about_ca_topic_score_gemma":0.0012203656,"teacher_disagreement_score":0.0046368563,"about_ca_system_score_codex":0.00083612296,"about_ca_system_score_gemma":0.00064686197,"threshold_uncertainty_score":0.015511811},"labels":[],"label_agreement":null},{"id":"W2402556194","doi":"","title":"Automated Detection of Mentors and Players in an Educational Game.","year":2012,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Ottawa","funders":"","keywords":"Conversation; Computer science; Task (project management); Context (archaeology); Computational linguistics; Dynamics (music); Conversation analysis; Human–computer interaction; Artificial intelligence; Natural language processing; Linguistics; Psychology; Pedagogy; Engineering","score_opus":0.014769492235525223,"score_gpt":0.26824363474866975,"score_spread":0.25347414251314454,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402556194","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":[0.86961573,0.0005312068,0.11740217,0.00061503175,0.00012503954,0.00056972046,0.001027536,0.0018744122,0.00823923],"genre_scores_gemma":[0.95315623,0.000088730274,0.040297978,0.00009705252,0.00003582601,0.00018345144,0.000978804,0.000058005455,0.0051039425],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99678683,0.0013824002,0.00017508771,0.0007160408,0.00060509937,0.00033465875],"domain_scores_gemma":[0.9913805,0.004451749,0.0013481743,0.0004710909,0.0013671162,0.000981301],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021789528,0.0008107187,0.000493417,0.0026007995,0.0012800065,0.0015539756,0.001162926,0.0015635875,0.0016950583],"category_scores_gemma":[0.011827797,0.0003343688,0.0004135488,0.00051190425,0.00069093413,0.0017243655,0.0024542382,0.0010330988,0.0011470021],"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":[0.0031389692,0.0010092587,0.37436956,0.0009828733,0.00027150454,0.0035511258,0.028447634,0.00486905,0.15685453,0.007670943,0.011448927,0.40738565],"study_design_scores_gemma":[0.00010777184,0.0010594826,0.38629842,0.00034099087,0.00027875646,0.0038865113,0.031814244,0.42259768,0.10177951,0.011499703,0.040067777,0.00026910155],"about_ca_topic_score_codex":0.004069755,"about_ca_topic_score_gemma":0.008453597,"teacher_disagreement_score":0.004069755,"about_ca_system_score_codex":0.00072921487,"about_ca_system_score_gemma":0.0006138044,"threshold_uncertainty_score":0.011523545},"labels":[],"label_agreement":null},{"id":"W2402633449","doi":"","title":"Word Learning in the Wild: What Natural Data Can Tell Us","year":2013,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Speech and dialogue systems","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":"University of Toronto","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Lexicon; Situational ethics; Noun; Context (archaeology); Word (group theory); Computer science; Natural language processing; Linguistics; Natural (archaeology); Artificial intelligence; Object (grammar); Natural language; Psychology; Social psychology; History","score_opus":0.01882282251792807,"score_gpt":0.21400750003425875,"score_spread":0.19518467751633067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402633449","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":[0.5293171,0.035679583,0.24006553,0.09540141,0.00097409135,0.00020287988,0.03222436,0.001428903,0.064706184],"genre_scores_gemma":[0.88278073,0.009961622,0.085367925,0.00499245,0.00038849644,0.00027617443,0.01255588,0.00056270335,0.003114049],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99772924,0.0011234466,0.00016949797,0.0005987602,0.00028920785,0.00008986419],"domain_scores_gemma":[0.9707973,0.019938007,0.0013712491,0.006105714,0.0012978911,0.0004898134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004379061,0.0004534383,0.00078799704,0.00243303,0.0016165469,0.006987896,0.0018296273,0.0023425985,0.0048822328],"category_scores_gemma":[0.037826043,0.0009861458,0.0005731095,0.0023134537,0.010138424,0.038415376,0.0027286913,0.003149148,0.0012859472],"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":[0.0008220649,0.0004670725,0.20328721,0.0037226127,0.00066760974,0.0017215165,0.042497866,0.006853717,0.011467039,0.33074486,0.040156033,0.35759246],"study_design_scores_gemma":[0.000046006153,0.00012020018,0.036964007,0.0012624081,0.00010321074,0.0015404299,0.019308664,0.007853102,0.00430546,0.7779508,0.15034248,0.00020325929],"about_ca_topic_score_codex":0.0034555672,"about_ca_topic_score_gemma":0.005359167,"teacher_disagreement_score":0.006987896,"about_ca_system_score_codex":0.0009138023,"about_ca_system_score_gemma":0.0010278837,"threshold_uncertainty_score":0.023158967},"labels":[],"label_agreement":null},{"id":"W2402762377","doi":"","title":"InkChat: a collaboration tool for mathematics.","year":2013,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Western University","funders":"","keywords":"Whiteboard; Multimodality; Computer science; Interactive whiteboard; Human–computer interaction; Multimedia; Mathematics education; World Wide Web; Mathematics","score_opus":0.012122283658374915,"score_gpt":0.23467366822907887,"score_spread":0.22255138457070395,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2402762377","genre_codex":"methods","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":[0.03389398,0.0017311177,0.87774694,0.0010155493,0.0006296231,0.0006050247,0.0009282107,0.047419816,0.036029734],"genre_scores_gemma":[0.27949265,0.0012378467,0.6490108,0.00065874,0.00034250267,0.0016764828,0.002543399,0.0048472164,0.060190443],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99812347,0.00074667705,0.00011832892,0.00028865572,0.0005718693,0.00015111754],"domain_scores_gemma":[0.9958339,0.0024161045,0.00019036666,0.00058531633,0.00033282358,0.000641429],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025203489,0.0015191805,0.0008508608,0.0016417118,0.0013529382,0.003927057,0.0020383515,0.0022264703,0.037691303],"category_scores_gemma":[0.008832773,0.00050946284,0.0009647345,0.0011258706,0.0013464931,0.00633818,0.008919384,0.0017283584,0.007575926],"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":[0.002430426,0.00075275067,0.0018241749,0.0034940674,0.00017657907,0.0022470672,0.009740459,0.007433398,0.08918811,0.10460646,0.09024165,0.68786496],"study_design_scores_gemma":[0.00080957107,0.0013145711,0.0034016217,0.0010905362,0.00020789263,0.0043129115,0.0022159307,0.060233217,0.06453343,0.0818544,0.77964145,0.00038446687],"about_ca_topic_score_codex":0.0003257944,"about_ca_topic_score_gemma":0.0004350674,"teacher_disagreement_score":0.037691303,"about_ca_system_score_codex":0.0004121346,"about_ca_system_score_gemma":0.0007787777,"threshold_uncertainty_score":0.12608993},"labels":[],"label_agreement":null},{"id":"W2404150556","doi":"10.1080/18756891.2015.1113741","title":"Context-Based Method Using Bayesian Network in Multimodal Fission System","year":2015,"lang":"en","type":"article","venue":"International Journal of Computational Intelligence Systems","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":5,"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; Modalities; Task (project management); Context (archaeology); Bayesian network; Machine learning; Artificial intelligence; Human–computer interaction; Systems engineering","score_opus":0.05816904207088643,"score_gpt":0.34887254400958256,"score_spread":0.29070350193869615,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2404150556","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01558005,0.0010988456,0.9779654,0.00028299386,0.00010501405,0.00011191135,0.00019182466,0.0010866973,0.0035772652],"genre_scores_gemma":[0.6315986,0.00134807,0.35767362,0.00036392183,0.00023387215,0.00036925866,0.0008745543,0.00024141044,0.007296631],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99849856,0.00047679097,0.0000942209,0.00046877496,0.0003349645,0.00012660286],"domain_scores_gemma":[0.9994081,0.00029078897,0.000040210452,0.000044051874,0.0001842178,0.000032555374],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015128526,0.00092828047,0.0011829997,0.0015446262,0.001145814,0.0012242986,0.001449475,0.0013614558,0.005296785],"category_scores_gemma":[0.0033374003,0.0004962495,0.00087411236,0.0009486253,0.00047411522,0.0020859474,0.0014057604,0.0013301674,0.0010962401],"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":[0.0010422677,0.0003610775,0.004774237,0.0004127097,0.00028786607,0.00051551335,0.0005192603,0.3011704,0.016976465,0.025204899,0.0074366955,0.6412986],"study_design_scores_gemma":[0.000027707596,0.000050398372,0.000568993,0.000025328241,0.00006559698,0.00008563663,0.00004466232,0.9857771,0.0026612435,0.008843676,0.0018240318,0.000025666792],"about_ca_topic_score_codex":0.014997853,"about_ca_topic_score_gemma":0.011032596,"teacher_disagreement_score":0.014997853,"about_ca_system_score_codex":0.00085926853,"about_ca_system_score_gemma":0.0014235949,"threshold_uncertainty_score":0.029821098},"labels":[],"label_agreement":null},{"id":"W2405076150","doi":"","title":"Problèmes d'évaluation dans la communication orale homme-machine.","year":2001,"lang":"fr","type":"article","venue":"Revue d intelligence artificielle","topic":"Speech and dialogue systems","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":"Humanities; Philosophy","score_opus":0.0751382060932336,"score_gpt":0.2941005511464469,"score_spread":0.2189623450532133,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2405076150","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11760341,0.01304223,0.82992244,0.0022798977,0.0008091913,0.0010308155,0.0006124855,0.0010418437,0.033657745],"genre_scores_gemma":[0.7188157,0.003298748,0.25879344,0.00056142797,0.00032080518,0.0016591309,0.00070658664,0.00048536735,0.015358705],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9388271,0.034235407,0.0034374332,0.005234387,0.017568147,0.00069747964],"domain_scores_gemma":[0.8706655,0.099915564,0.0059868037,0.0041830675,0.018286034,0.00096296734],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.038011573,0.0013333274,0.0017463212,0.0028128428,0.0021057504,0.008862161,0.001956732,0.0031552133,0.004890044],"category_scores_gemma":[0.16887648,0.00052527385,0.00072295865,0.002277468,0.0029359246,0.0057059424,0.0033043423,0.0015531708,0.0014524679],"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":[0.0012661024,0.00035984497,0.021579871,0.00524912,0.00054910505,0.00038196845,0.013581969,0.009955415,0.030121313,0.04037535,0.008259372,0.8683206],"study_design_scores_gemma":[0.00049856916,0.0039289864,0.15222597,0.00494952,0.0016100211,0.00370859,0.040634647,0.24134101,0.18553355,0.17047602,0.1941398,0.00095338764],"about_ca_topic_score_codex":0.0038228582,"about_ca_topic_score_gemma":0.0032340733,"teacher_disagreement_score":0.038011573,"about_ca_system_score_codex":0.0018291195,"about_ca_system_score_gemma":0.0019156374,"threshold_uncertainty_score":0.2010268},"labels":[],"label_agreement":null},{"id":"W2405665360","doi":"10.21437/interspeech.2011-538","title":"On the use of linguistic features in an automatic system for speech analytics of telephone conversations","year":2011,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Computer science; Vocabulary; Natural language processing; Conversation; Sentence; Artificial intelligence; Boosting (machine learning); Set (abstract data type); Speech analytics; Speech recognition; Test set; Analytics; Training set; Speech processing; Voice activity detection; Data mining; Linguistics","score_opus":0.09143124079507628,"score_gpt":0.26401623260575496,"score_spread":0.17258499181067868,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2405665360","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28335315,0.0009571031,0.68794745,0.00032384568,0.00013383565,0.0008016428,0.0013128202,0.022372482,0.002797773],"genre_scores_gemma":[0.4264461,0.00035865747,0.56625795,0.00014773023,0.000082841325,0.0006806334,0.0032900416,0.00032558476,0.0024103627],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99862206,0.0005332232,0.000089293004,0.00043698365,0.0002180548,0.00010038611],"domain_scores_gemma":[0.99701536,0.0020548727,0.00012507699,0.00017504969,0.0005407178,0.000089057234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018873797,0.0008655953,0.0010261255,0.0015994986,0.0007414137,0.0013654643,0.00089521933,0.0010178481,0.0021997322],"category_scores_gemma":[0.00422835,0.00040174252,0.0006129637,0.0011132583,0.00037153787,0.0015878221,0.00070738647,0.00087188015,0.0024053988],"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":[0.0011700075,0.0006002625,0.0044017155,0.0003229903,0.00012550966,0.00026979038,0.00037702898,0.008553532,0.15373643,0.00066768605,0.0030387945,0.8267362],"study_design_scores_gemma":[0.00016842302,0.001542554,0.021410087,0.00011098353,0.00025301866,0.0009331861,0.0005003975,0.80644286,0.15934792,0.0019988145,0.007152902,0.00013888217],"about_ca_topic_score_codex":0.003769301,"about_ca_topic_score_gemma":0.002728786,"teacher_disagreement_score":0.003769301,"about_ca_system_score_codex":0.00047586992,"about_ca_system_score_gemma":0.0005950125,"threshold_uncertainty_score":0.009981573},"labels":[],"label_agreement":null},{"id":"W2426249411","doi":"","title":"On busy loafers.","year":2007,"lang":"en","type":"article","venue":"PubMed","topic":"Speech and dialogue systems","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":"York University","funders":"","keywords":"Business; Computer science","score_opus":0.0184563946869576,"score_gpt":0.20504217227088076,"score_spread":0.18658577758392317,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2426249411","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":[0.14082329,0.080890164,0.06340146,0.040261757,0.009767749,0.00036976012,0.009722276,0.0061221155,0.6486415],"genre_scores_gemma":[0.61679643,0.0416752,0.018950192,0.007629322,0.003381348,0.00022753564,0.007741068,0.0013157937,0.30228314],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989035,0.00046991772,0.00008075029,0.00012933156,0.00026247537,0.00015409854],"domain_scores_gemma":[0.9943877,0.0035992302,0.00039022765,0.00048160448,0.0008078059,0.00033338458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001359419,0.00064258656,0.00049991655,0.0029236653,0.0024841877,0.0025484082,0.00096486195,0.0015873936,0.07229806],"category_scores_gemma":[0.014627231,0.000256857,0.00028672887,0.0016374837,0.0011659474,0.0067518163,0.0025082605,0.0008943425,0.023630112],"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":[0.00082823983,0.00006909776,0.005247283,0.0013394012,0.000043535678,0.001986236,0.0114769675,0.0002747842,0.00392812,0.031462356,0.3526411,0.5907029],"study_design_scores_gemma":[0.000047479258,0.00017386547,0.008001275,0.0013805965,0.00008467201,0.004216028,0.015926508,0.0013252209,0.004512429,0.029059649,0.93519735,0.00007503778],"about_ca_topic_score_codex":0.00479339,"about_ca_topic_score_gemma":0.0077141235,"teacher_disagreement_score":0.07229806,"about_ca_system_score_codex":0.0005925893,"about_ca_system_score_gemma":0.0009399041,"threshold_uncertainty_score":0.24186105},"labels":[],"label_agreement":null},{"id":"W2463221292","doi":"10.21437/interspeech.2016-420","title":"Prosodic and Linguistic Analysis of Semantic Fluency Data: A Window into Speech Production and Cognition","year":2016,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Kootenay Association for Science & Technology","funders":"","keywords":"Window (computing); Fluency; Computer science; Cognition; Natural language processing; Verbal fluency test; Linguistic analysis; Speech recognition; Linguistics; Artificial intelligence; Psychology; Neuropsychology","score_opus":0.022801345724987498,"score_gpt":0.263418876999492,"score_spread":0.24061753127450453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2463221292","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":[0.82393,0.0013547933,0.14497712,0.0005979829,0.00015031954,0.00022317847,0.0024129539,0.00074398355,0.025609583],"genre_scores_gemma":[0.94555354,0.00045651797,0.050602235,0.00011307579,0.00017293212,0.00024349273,0.0012876915,0.00026791712,0.001302543],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9992441,0.00032725287,0.00006780684,0.00015577284,0.00014597696,0.000059167003],"domain_scores_gemma":[0.99421567,0.0041847792,0.0004335061,0.0005221268,0.00052559347,0.00011821699],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015909813,0.000527951,0.00039096037,0.0021765064,0.00050662336,0.0021794734,0.00036154938,0.00056655996,0.0040029064],"category_scores_gemma":[0.009922271,0.00024092502,0.00035550335,0.0016457535,0.0009617067,0.0024837365,0.0010202685,0.0008938867,0.0007961964],"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":[0.0016796137,0.00039971326,0.05269747,0.0011816128,0.00022720566,0.0020267486,0.018426714,0.002206599,0.53289926,0.019158125,0.002139422,0.36695752],"study_design_scores_gemma":[0.00009394071,0.0009508574,0.8332051,0.00033704148,0.00021285423,0.0027858957,0.009628763,0.035759836,0.062869646,0.040770385,0.013028331,0.00035731358],"about_ca_topic_score_codex":0.0008856049,"about_ca_topic_score_gemma":0.0010036711,"teacher_disagreement_score":0.0040029064,"about_ca_system_score_codex":0.00023874125,"about_ca_system_score_gemma":0.00037442046,"threshold_uncertainty_score":0.013391018},"labels":[],"label_agreement":null},{"id":"W2467764055","doi":"10.21437/interspeech.2016-1175","title":"A Sequence-to-Sequence Model for User Simulation in Spoken Dialogue Systems","year":2016,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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 Waterloo","funders":"","keywords":"Computer science; Sequence (biology); Granularity; Action (physics); Encoder; Artificial intelligence; Space (punctuation); Human–computer interaction; Natural language processing","score_opus":0.11329646611924457,"score_gpt":0.33259775846008255,"score_spread":0.21930129234083798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2467764055","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046101358,0.00030452237,0.94868857,0.00046934714,0.00008274449,0.00016552441,0.0006497382,0.0019083313,0.0016298913],"genre_scores_gemma":[0.83633834,0.0003034164,0.15460536,0.0002557238,0.00009008807,0.00072704913,0.0014728329,0.0003166688,0.0058905478],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99717075,0.0015927068,0.0001642547,0.00060596695,0.00032432334,0.00014208256],"domain_scores_gemma":[0.9954074,0.0033521673,0.00021065214,0.0004336997,0.00044629566,0.00014978729],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002889022,0.0009084408,0.0011281251,0.00064856326,0.00052109786,0.0011333638,0.0016989666,0.0018092722,0.0029974368],"category_scores_gemma":[0.0093465205,0.0007854084,0.0012337832,0.00058089953,0.0010521279,0.0022476525,0.0013427115,0.0027176025,0.0016166623],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00051507825,0.00016345466,0.0021974558,0.00013669384,0.0000903816,0.00019735735,0.0007196266,0.91072077,0.0064791697,0.023561193,0.0018667083,0.053352136],"study_design_scores_gemma":[0.000008368104,0.00004299013,0.00011135871,0.000003919539,0.0000060203793,0.000023341297,0.0000086204245,0.99376607,0.0004592529,0.0051520066,0.0004105505,0.0000075487133],"about_ca_topic_score_codex":0.008409008,"about_ca_topic_score_gemma":0.008016919,"teacher_disagreement_score":0.008409008,"about_ca_system_score_codex":0.0012005349,"about_ca_system_score_gemma":0.001372691,"threshold_uncertainty_score":0.016720176},"labels":[],"label_agreement":null},{"id":"W2476107770","doi":"10.1007/978-3-319-26200-0_3","title":"Sequential Decision Making in Spoken Dialog Management","year":2016,"lang":"en","type":"book-chapter","venue":"Springer briefs in electrical and computer engineering","topic":"Speech and dialogue systems","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; University of Toronto","funders":"","keywords":"Dialog box; Partially observable Markov decision process; Computer science; Artificial intelligence; Markov decision process; Process (computing); Natural language processing; Dialog system; Observable; Markov process; Markov chain; Machine learning; Markov model; Programming language; Mathematics; World Wide Web","score_opus":0.007627747629727103,"score_gpt":0.20118461666423776,"score_spread":0.19355686903451066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2476107770","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":[0.02208272,0.009866535,0.9441171,0.0014797981,0.00072398555,0.00009883736,0.0001265646,0.00032343206,0.021180969],"genre_scores_gemma":[0.70103997,0.0066741393,0.25835744,0.00032931878,0.0009905297,0.00035182835,0.0004215976,0.00016038147,0.03167482],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9971226,0.0015699053,0.00019412335,0.00032977437,0.0006198661,0.00016372491],"domain_scores_gemma":[0.99372417,0.0055050845,0.00013950124,0.00019227921,0.00032402514,0.00011495278],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036653539,0.00095391425,0.0011017849,0.0004746276,0.0006266721,0.0022645795,0.0012214535,0.0014177583,0.007424095],"category_scores_gemma":[0.008725791,0.0006835053,0.0005296264,0.0010266814,0.0018407309,0.0033647364,0.001410292,0.0017871573,0.0010436872],"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":[0.0005725337,0.00023381205,0.0006207156,0.0006266917,0.00012034316,0.00022585355,0.0008332601,0.2691116,0.003306131,0.3548879,0.011106948,0.35835427],"study_design_scores_gemma":[0.00004596079,0.00007851031,0.0002012597,0.00006207367,0.000019278754,0.000044065207,0.00011694132,0.5153574,0.0010785682,0.4758984,0.0070637558,0.000033761677],"about_ca_topic_score_codex":0.004135763,"about_ca_topic_score_gemma":0.0032994384,"teacher_disagreement_score":0.007424095,"about_ca_system_score_codex":0.0010677594,"about_ca_system_score_gemma":0.001702969,"threshold_uncertainty_score":0.024836063},"labels":[],"label_agreement":null},{"id":"W2496498790","doi":"","title":"Timetraveller™: first nations nonverbal communication in second life","year":2014,"lang":"en","type":"book","venue":"ETC Press eBooks","topic":"Speech and dialogue systems","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":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Nonverbal communication; Psychology; Communication","score_opus":0.022585887066740376,"score_gpt":0.2231527445786778,"score_spread":0.20056685751193742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2496498790","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":[0.0016893803,0.057261575,0.010383047,0.003329966,0.004980959,0.00003364803,0.00012636515,0.00035440794,0.92184067],"genre_scores_gemma":[0.013547464,0.013344879,0.0020615682,0.0006126201,0.0012309458,0.000046547517,0.00017491856,0.00019340773,0.9687876],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998149,0.000047005615,0.000007209892,0.000019796811,0.000090584355,0.000020531943],"domain_scores_gemma":[0.9998323,0.00007972755,0.0000068347817,0.000016976303,0.000036841935,0.000027414033],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026839224,0.00087928574,0.00038482732,0.0008234995,0.0012299669,0.00311896,0.00054429733,0.0011594269,0.03299474],"category_scores_gemma":[0.0006499209,0.0002160967,0.00016393515,0.00085059047,0.0012641113,0.0031479718,0.0011934027,0.0018257474,0.017263167],"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":[0.000031005202,0.000028664737,0.00013198171,0.00025444847,0.000004920654,0.00009486109,0.0022656869,0.00019635214,0.0010166221,0.15503588,0.49621278,0.3447268],"study_design_scores_gemma":[0.0000027837373,0.000013866962,0.00026582732,0.00012737066,0.0000023190157,0.00019797003,0.0004133817,0.00020096032,0.00033134618,0.012113975,0.9863247,0.0000054639645],"about_ca_topic_score_codex":0.0024965068,"about_ca_topic_score_gemma":0.0055203494,"teacher_disagreement_score":0.03299474,"about_ca_system_score_codex":0.00081613124,"about_ca_system_score_gemma":0.0009377313,"threshold_uncertainty_score":0.110378444},"labels":[],"label_agreement":null},{"id":"W2503922193","doi":"10.1007/978-3-319-26200-0_6","title":"Application on Healthcare Dialog Management","year":2016,"lang":"en","type":"book-chapter","venue":"Springer briefs in electrical and computer engineering","topic":"Speech and dialogue systems","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; University of Toronto","funders":"","keywords":"Dialog box; Health care; Computer science; Political science; World Wide Web","score_opus":0.0065096968967144255,"score_gpt":0.18791628782761022,"score_spread":0.18140659093089578,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2503922193","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":[0.022229757,0.017863313,0.47920308,0.004854754,0.0028504264,0.0008641046,0.0022553634,0.018613506,0.45126557],"genre_scores_gemma":[0.2819254,0.011797674,0.3159127,0.0030519732,0.001519467,0.0007083767,0.0030346797,0.0013123375,0.38073742],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995185,0.00017399338,0.000030646763,0.00008867089,0.00015260017,0.00003557817],"domain_scores_gemma":[0.9993073,0.00036822192,0.00001547448,0.00008612068,0.00015385622,0.00006894979],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006569508,0.0007691929,0.0005910661,0.00095693144,0.00091451046,0.0024700207,0.00095013186,0.0018064352,0.05050092],"category_scores_gemma":[0.0023038886,0.00020583266,0.0005334098,0.0013148667,0.00038329838,0.00096256466,0.0019118667,0.0008001724,0.01315935],"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":[0.0001484134,0.00022160991,0.00074689847,0.0007293298,0.00003805571,0.0008342408,0.0010658214,0.0076280516,0.009942732,0.044483036,0.088051654,0.84611017],"study_design_scores_gemma":[0.00007584964,0.00020984301,0.0019312103,0.0006120073,0.000068062145,0.0016441881,0.0010292575,0.07908985,0.013504083,0.07304899,0.82870954,0.0000770826],"about_ca_topic_score_codex":0.0024196233,"about_ca_topic_score_gemma":0.002214642,"teacher_disagreement_score":0.05050092,"about_ca_system_score_codex":0.000665913,"about_ca_system_score_gemma":0.00069152046,"threshold_uncertainty_score":0.16894239},"labels":[],"label_agreement":null},{"id":"W2506544892","doi":"10.1017/cbo9781139565776.008","title":"Metadialogues and Redefinitions","year":2014,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Computer science","score_opus":0.028795525250659305,"score_gpt":0.1864242161812121,"score_spread":0.1576286909305528,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2506544892","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":[0.009456092,0.013890443,0.21789302,0.0050706677,0.0021155535,0.00021213265,0.00029491007,0.0009101235,0.75015706],"genre_scores_gemma":[0.50620335,0.012209955,0.15454473,0.0035815788,0.0012818349,0.0009509382,0.0007651942,0.0015170334,0.31894532],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9971174,0.0014483245,0.0001737788,0.00049685815,0.0005730021,0.00019053824],"domain_scores_gemma":[0.99862826,0.0007371523,0.00007878611,0.0003310926,0.00014594766,0.00007876628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026274407,0.001248437,0.0006165066,0.001686782,0.0019676539,0.00624309,0.0020107832,0.0019548724,0.010443076],"category_scores_gemma":[0.004583246,0.0008712216,0.0008128301,0.001196588,0.008442333,0.012379743,0.0044223275,0.0061717904,0.0029086622],"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":[0.000009766136,0.0000050498033,0.000015295605,0.000050587663,0.0000021592373,0.00002123145,0.0014176936,0.0001094599,0.00019846238,0.98745465,0.0020287728,0.008686832],"study_design_scores_gemma":[0.000023139663,0.000025685385,0.00011532751,0.0003371915,0.000012468955,0.00025138343,0.00093690265,0.0015569951,0.0013895284,0.5847749,0.41054863,0.000027901224],"about_ca_topic_score_codex":0.0015615759,"about_ca_topic_score_gemma":0.0017263432,"teacher_disagreement_score":0.010443076,"about_ca_system_score_codex":0.0047794892,"about_ca_system_score_gemma":0.0015324946,"threshold_uncertainty_score":0.034935534},"labels":[],"label_agreement":null},{"id":"W2526674945","doi":"10.1080/23273798.2016.1234059","title":"Knowledge likely held by others affects speakers’ choices of referential expressions at different stages of discourse","year":2016,"lang":"en","type":"article","venue":"Language Cognition and Neuroscience","topic":"Speech and dialogue systems","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 Laval; Institut Universitaire en Santé Mentale de Québec; Université du Québec à Montréal","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Referent; Psychology; Linguistics; Character (mathematics); Point (geometry); Cognitive psychology; Mathematics","score_opus":0.022552533422785213,"score_gpt":0.2872901950047138,"score_spread":0.2647376615819286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2526674945","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":[0.9981812,0.000027813812,0.00061610295,0.000015245261,0.0000017768841,0.0000062965805,0.0000052092273,0.0000073682895,0.001138968],"genre_scores_gemma":[0.9990552,0.000039002443,0.0005818831,0.000009931742,0.0000016270217,0.000010160123,0.000011418279,0.0000067498913,0.00028391762],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9981025,0.00081727264,0.00012397394,0.00044455664,0.00035491245,0.00015681192],"domain_scores_gemma":[0.99008745,0.006771292,0.0016333754,0.0006344458,0.00052812806,0.00034529142],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002368784,0.0003206411,0.00028929877,0.0005060112,0.00050249667,0.0023706383,0.0002839846,0.00064854196,0.0015543959],"category_scores_gemma":[0.014089676,0.00039264097,0.00028394346,0.00017452486,0.0013272517,0.0015335155,0.0010589532,0.00065272884,0.00022220163],"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":[0.0021136028,0.0005822916,0.15370232,0.00023440059,0.0002195211,0.0009919327,0.1217647,0.0011157194,0.66697806,0.0014511342,0.00018412583,0.050662205],"study_design_scores_gemma":[0.000068050336,0.0012769746,0.84146774,0.00006783593,0.00031892685,0.00076965854,0.038283963,0.004526361,0.10837985,0.0028455884,0.0017982012,0.00019686138],"about_ca_topic_score_codex":0.0012833935,"about_ca_topic_score_gemma":0.0011646525,"teacher_disagreement_score":0.0023706383,"about_ca_system_score_codex":0.00034792512,"about_ca_system_score_gemma":0.00026406106,"threshold_uncertainty_score":0.012527466},"labels":[],"label_agreement":null},{"id":"W2551051645","doi":"10.3389/fpsyg.2016.01886","title":"Acquiring Complex Focus-Marking: Finnish 4- to 5-Year-Olds Use Prosody and Word Order in Interaction","year":2016,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Speech and dialogue systems","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 Alberta","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Helsingin Yliopisto","keywords":"Psychology; Prosody; Focus (optics); Word order; Word (group theory); Linguistics; Cognitive psychology; Natural language processing; Computer science","score_opus":0.036093988384517495,"score_gpt":0.30561263256271,"score_spread":0.2695186441781925,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2551051645","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":[0.9995641,0.00005239356,0.00009937707,0.000005227714,0.000002217923,0.000004236868,0.000035651865,0.000008340338,0.00022843965],"genre_scores_gemma":[0.99850583,0.000110617926,0.00044558477,0.000013456102,0.0000028730246,0.00001622871,0.00015294518,0.0000045330767,0.00074803835],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9996941,0.000033151093,0.000031328087,0.00007662106,0.00007533725,0.00008954278],"domain_scores_gemma":[0.99916565,0.00029824168,0.00020887646,0.00006033395,0.00010186672,0.00016503582],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007352498,0.0004768874,0.00034526456,0.00062622555,0.00027238848,0.0008490741,0.0003368147,0.0005350036,0.0015060776],"category_scores_gemma":[0.0017419669,0.0002829077,0.00030497272,0.00012740467,0.00059684255,0.0004466618,0.0008069102,0.00043386058,0.0003836363],"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":[0.0013675736,0.00078487437,0.24741445,0.00030458142,0.000094413204,0.005959651,0.018366294,0.00029639003,0.68458915,0.00051759684,0.00030926857,0.039995775],"study_design_scores_gemma":[0.000034221004,0.0023264259,0.93850696,0.000042394055,0.000115887015,0.0026052436,0.004163193,0.00044054788,0.049915064,0.0002785712,0.0015137302,0.000057705365],"about_ca_topic_score_codex":0.0029487398,"about_ca_topic_score_gemma":0.0028612562,"teacher_disagreement_score":0.0029487398,"about_ca_system_score_codex":0.00021757098,"about_ca_system_score_gemma":0.00031047076,"threshold_uncertainty_score":0.00586313},"labels":[],"label_agreement":null},{"id":"W256268639","doi":"","title":"The Light Verb Construction in Japanese: The Role of the Verbal Noun by Tadao Miyamoto (review)","year":2001,"lang":"en","type":"article","venue":"University of Toronto Quarterly","topic":"Speech and dialogue systems","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":"Verb; Noun; Linguistics; Psychology; History; Philosophy","score_opus":0.003066767101484554,"score_gpt":0.1700942789604509,"score_spread":0.16702751185896636,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W256268639","genre_codex":"review","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":[0.00022539726,0.9980611,0.000065318985,0.0010634613,0.0003569537,0.0000012988088,0.000006572825,0.0000015934418,0.0002182006],"genre_scores_gemma":[0.0020675487,0.9956078,0.00016255383,0.0013087365,0.0005527718,0.0000075605394,0.000018948338,0.0000033536064,0.0002706778],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995927,0.000094963274,0.00009151561,0.000097161035,0.000088071836,0.00003562213],"domain_scores_gemma":[0.9992926,0.0002946752,0.00013476257,0.000019529953,0.0001796508,0.00007873446],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017064022,0.0006977451,0.0015889684,0.0013447393,0.00058555946,0.0016826638,0.0010175931,0.0018400047,0.0010679496],"category_scores_gemma":[0.0017762411,0.00044183296,0.00045944253,0.0025452503,0.00215477,0.002848315,0.0015089666,0.0015441299,0.00062594656],"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":[0.0003035979,0.000055480963,0.0014279693,0.035159558,0.00026636146,0.0012461075,0.0014929189,0.00018785961,0.0037951258,0.0052229334,0.11001252,0.8408297],"study_design_scores_gemma":[0.0000668905,0.00015559272,0.0089019425,0.005884442,0.0006615601,0.002788693,0.0007853199,0.000063979845,0.00081185164,0.0018511504,0.97796655,0.00006209122],"about_ca_topic_score_codex":0.0073510227,"about_ca_topic_score_gemma":0.011176081,"teacher_disagreement_score":0.0073510227,"about_ca_system_score_codex":0.00080711546,"about_ca_system_score_gemma":0.0036539289,"threshold_uncertainty_score":0.01461643},"labels":[],"label_agreement":null},{"id":"W2564272265","doi":"10.1075/slcs.178.11wil","title":"The syntax of confirmationals","year":2016,"lang":"en","type":"book-chapter","venue":"Studies in language companion series","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":119,"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":"Syntax; Linguistics; Computer science; Philosophy","score_opus":0.045957472430449384,"score_gpt":0.31005573766766187,"score_spread":0.26409826523721247,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2564272265","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13102165,0.004994564,0.5363499,0.007846463,0.00053007127,0.00009802832,0.00086540845,0.002232091,0.31606194],"genre_scores_gemma":[0.9507136,0.00084840873,0.032529924,0.0005143796,0.00022503051,0.000093750874,0.00024848295,0.0004981712,0.01432827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978739,0.0010421929,0.00013767755,0.00033855028,0.0004212599,0.00018653493],"domain_scores_gemma":[0.9966893,0.0020151807,0.0002727208,0.00048786073,0.0004529856,0.00008184714],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019740625,0.00044849108,0.0003419557,0.0012912638,0.0016961124,0.0056498325,0.0010631654,0.0013030284,0.0065168445],"category_scores_gemma":[0.004864882,0.0005562755,0.0005569214,0.0010717267,0.0076108994,0.009707092,0.0023665708,0.0023130632,0.0013337657],"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":[0.000015081825,0.0000021441492,0.000118967626,0.000029100018,0.0000027886333,0.000041512078,0.0014707972,0.000120059056,0.0007548399,0.9917697,0.00052902976,0.0051460494],"study_design_scores_gemma":[0.00002153196,0.000030898253,0.00083323946,0.000078737736,0.000018238752,0.0003861326,0.00095448043,0.0032492871,0.002462194,0.91740006,0.074528374,0.00003670602],"about_ca_topic_score_codex":0.0015832003,"about_ca_topic_score_gemma":0.0009465321,"teacher_disagreement_score":0.0065168445,"about_ca_system_score_codex":0.0015358559,"about_ca_system_score_gemma":0.00083005935,"threshold_uncertainty_score":0.021800995},"labels":[],"label_agreement":null},{"id":"W2573389143","doi":"","title":"TopoText: Interactive Digital Mapping of Literary Text","year":2016,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; GRASP; Context (archaeology); Information retrieval; World Wide Web; Natural language processing; Artificial intelligence; Human–computer interaction","score_opus":0.011112222448439896,"score_gpt":0.2141472400540086,"score_spread":0.2030350176055687,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2573389143","genre_codex":"methods","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":[0.0352202,0.00067035464,0.6077439,0.00045908804,0.0007544033,0.00045123044,0.036882654,0.23446703,0.08335109],"genre_scores_gemma":[0.2644651,0.001098352,0.5650149,0.0004005976,0.0004148493,0.0014853025,0.052461427,0.03602744,0.078632124],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9994728,0.00012216749,0.00003109947,0.00011329224,0.0002124096,0.00004822461],"domain_scores_gemma":[0.9985788,0.0007592577,0.000055397446,0.0002697834,0.00021084219,0.00012606062],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00060554076,0.0014180081,0.0005694149,0.0029098517,0.0007079388,0.0030416457,0.0014576467,0.00077365764,0.07460429],"category_scores_gemma":[0.0032469772,0.00041128727,0.0008993697,0.0018016591,0.0005131163,0.002702334,0.003689712,0.0007037544,0.01693008],"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":[0.0019202688,0.00022114163,0.0037399936,0.0023886282,0.00027807348,0.0026565217,0.006195482,0.008239191,0.051638808,0.01976345,0.3561183,0.5468402],"study_design_scores_gemma":[0.00022776912,0.0001748638,0.008768194,0.00048855116,0.0001176264,0.002194247,0.002351411,0.07204603,0.053359285,0.025339652,0.8346405,0.00029189515],"about_ca_topic_score_codex":0.0024509344,"about_ca_topic_score_gemma":0.003916585,"teacher_disagreement_score":0.07460429,"about_ca_system_score_codex":0.00042609108,"about_ca_system_score_gemma":0.00043389466,"threshold_uncertainty_score":0.24957621},"labels":[],"label_agreement":null},{"id":"W2573660649","doi":"10.1109/mcsi.2016.042","title":"Speech Intent Recognition for Robots","year":2016,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Dialog box; Computer science; Classifier (UML); Hidden Markov model; Speech recognition; Robot; Artificial intelligence; Dialog system; Natural language processing; Set (abstract data type); Programming language","score_opus":0.04751750274038413,"score_gpt":0.24924961126650383,"score_spread":0.2017321085261197,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2573660649","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022259032,0.0011497622,0.9638555,0.00031182068,0.00011343309,0.00009747018,0.00027260117,0.009054527,0.002885932],"genre_scores_gemma":[0.40084988,0.0006053294,0.58974963,0.00027139345,0.00009909628,0.00023812304,0.0013490279,0.00024088044,0.006596604],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99949694,0.00012405078,0.000040220202,0.00012875744,0.00016407094,0.00004589556],"domain_scores_gemma":[0.99934787,0.00026145994,0.00007269722,0.00010139327,0.00018121165,0.000035453155],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059420493,0.0005438593,0.00043528355,0.00050352607,0.00038990128,0.0007345018,0.00066907844,0.0006418273,0.0027185925],"category_scores_gemma":[0.0018280902,0.00032311134,0.00046088808,0.0002556725,0.00040904677,0.0010325881,0.0006541328,0.00080735394,0.0017998677],"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":[0.0003579928,0.00015386421,0.003850245,0.00040472733,0.00007723207,0.00031281647,0.0005694198,0.062183034,0.12860794,0.020475494,0.016524132,0.7664831],"study_design_scores_gemma":[0.00002849797,0.00024034057,0.0033236737,0.000064897125,0.000049321712,0.00032149974,0.00015961957,0.8697424,0.07484196,0.021889348,0.029271254,0.00006716131],"about_ca_topic_score_codex":0.0036610987,"about_ca_topic_score_gemma":0.004149403,"teacher_disagreement_score":0.0036610987,"about_ca_system_score_codex":0.0005054992,"about_ca_system_score_gemma":0.00074418675,"threshold_uncertainty_score":0.009094596},"labels":[],"label_agreement":null},{"id":"W2581737236","doi":"10.5061/dryad.79310","title":"Data from: What makes a multimodal signal attractive? A preference function approach","year":2017,"lang":"en","type":"article","venue":"Data Archiving and Networked Services (DANS)","topic":"Speech and dialogue systems","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":"Wilfrid Laurier University","funders":"","keywords":"Computer science; Preference; Function (biology); SIGNAL (programming language); Artificial intelligence; Mathematics; Statistics","score_opus":0.10558484899511843,"score_gpt":0.2811252793829993,"score_spread":0.17554043038788086,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2581737236","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5359474,0.0059363744,0.31490847,0.010949353,0.00050068484,0.00096122775,0.04275436,0.0024326206,0.08560947],"genre_scores_gemma":[0.9297181,0.0012213571,0.04960404,0.0010326314,0.00012230799,0.00046368034,0.007026354,0.00027183854,0.010539566],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9977239,0.00089686783,0.00018921032,0.00047942603,0.00053490367,0.00017577017],"domain_scores_gemma":[0.99287486,0.0039217533,0.0005801506,0.0009856203,0.0013945912,0.00024290949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0040309215,0.00074112904,0.0009364184,0.0019553683,0.0004977809,0.0026613823,0.0012354278,0.0015011687,0.026953062],"category_scores_gemma":[0.019056901,0.00026023234,0.0013885635,0.0021411558,0.00070439087,0.002794669,0.0014095677,0.0011076459,0.005773695],"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":[0.0036211272,0.0005662587,0.14432642,0.0051857713,0.0012590463,0.0009986165,0.0017508623,0.027595486,0.05874837,0.10145278,0.033262543,0.62123275],"study_design_scores_gemma":[0.00040665944,0.0030059083,0.29363135,0.0012495829,0.0013358459,0.004612813,0.00496357,0.28492,0.03998146,0.20642449,0.15891549,0.0005528327],"about_ca_topic_score_codex":0.0030037959,"about_ca_topic_score_gemma":0.0030331956,"teacher_disagreement_score":0.026953062,"about_ca_system_score_codex":0.0012282986,"about_ca_system_score_gemma":0.00059900637,"threshold_uncertainty_score":0.090166986},"labels":[],"label_agreement":null},{"id":"W2582864755","doi":"10.1109/fgcns.2008.163","title":"A System Assisting English Oral Reaction &amp;#150; A Case Study of the Junior Level of Taiwan English Qualify","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":2,"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); First language; Computer science; Test (biology); Tongue; Population; Center (category theory); English language; Mathematics education; Natural language processing; Multimedia; Psychology; Medicine; Environmental health; History; Pathology","score_opus":0.14377983786984058,"score_gpt":0.29703351086793156,"score_spread":0.15325367299809098,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2582864755","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":[0.9788356,0.00016174815,0.0114003215,0.0009742548,0.000054041575,0.000376687,0.00025876335,0.0009263155,0.0070123705],"genre_scores_gemma":[0.97485787,0.0001442451,0.012382005,0.00026304796,0.00001861592,0.00017195391,0.0002886769,0.00010769287,0.011765854],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99883264,0.00055912766,0.00013724939,0.00014072932,0.00017733447,0.00015289869],"domain_scores_gemma":[0.9974222,0.0015299259,0.0001402624,0.00020358257,0.00031893342,0.00038510727],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017048881,0.0004634002,0.0003646328,0.000511214,0.0011185148,0.001042032,0.000991674,0.0015950918,0.006858031],"category_scores_gemma":[0.005687169,0.00024396494,0.00036582167,0.00036386715,0.00059581094,0.0009854232,0.0010400484,0.00058560463,0.0024023158],"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":[0.002315239,0.006861151,0.13680528,0.0014634217,0.00013131028,0.16648202,0.08882754,0.004649703,0.07493461,0.0029534234,0.02613406,0.48844233],"study_design_scores_gemma":[0.0010994755,0.019394215,0.19467804,0.0005501015,0.00056189846,0.14468008,0.14778809,0.106896095,0.1879111,0.0024215733,0.19333541,0.00068396964],"about_ca_topic_score_codex":0.0040227496,"about_ca_topic_score_gemma":0.0065736347,"teacher_disagreement_score":0.006858031,"about_ca_system_score_codex":0.0005325076,"about_ca_system_score_gemma":0.0006049307,"threshold_uncertainty_score":0.022942364},"labels":[],"label_agreement":null},{"id":"W2583222546","doi":"","title":"The Diversity of Conceptual Combination","year":2004,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Speech and dialogue systems","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":"","keywords":"Diversity (politics); Sociology; Interpretation (philosophy); Library science; Psychology; Computer science; Anthropology","score_opus":0.015892697153636684,"score_gpt":0.19805663062552661,"score_spread":0.18216393347188992,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2583222546","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":[0.04399744,0.23027308,0.06745531,0.22235604,0.010949949,0.00009231274,0.00052035647,0.00060143386,0.42375413],"genre_scores_gemma":[0.81812185,0.05900874,0.039797533,0.016755035,0.008030135,0.00026280805,0.00087889784,0.0007246335,0.056420423],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9928536,0.0042529223,0.00026368166,0.0011904541,0.0010686733,0.0003707297],"domain_scores_gemma":[0.9874161,0.0074325837,0.00054243853,0.0016303421,0.0017778979,0.0012006941],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007939466,0.0008226164,0.000756031,0.003170117,0.0034171555,0.012172956,0.0015204664,0.002768787,0.019383613],"category_scores_gemma":[0.019058993,0.000685508,0.0008972312,0.0021770585,0.015878068,0.021611875,0.00722054,0.005683109,0.0023681642],"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":[0.00014855994,0.000055207845,0.0026462905,0.00047661905,0.00007196898,0.00028506483,0.02723395,0.00038062222,0.0009988706,0.6137281,0.13708402,0.21689063],"study_design_scores_gemma":[0.000024038498,0.000045452387,0.0037432355,0.00072145014,0.000040135776,0.0009383585,0.008415785,0.0008936741,0.0004319084,0.41422606,0.5704608,0.000059115217],"about_ca_topic_score_codex":0.0026491915,"about_ca_topic_score_gemma":0.0021622654,"teacher_disagreement_score":0.019383613,"about_ca_system_score_codex":0.0055333753,"about_ca_system_score_gemma":0.0028424042,"threshold_uncertainty_score":0.06484461},"labels":[],"label_agreement":null},{"id":"W2584477044","doi":"","title":"Expanding the linguistic coverage of a spoken dialogue system by mining human-human dialogue for new sentences with familiar meanings","year":2004,"lang":"en","type":"article","venue":"eScholarship (California Digital Library)","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":2,"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; Variety (cybernetics); Linguistics; Artificial intelligence; Natural language processing; Domain (mathematical analysis); Phrase; Noun phrase; GRASP; Noun; Programming language","score_opus":0.017125393114405894,"score_gpt":0.22627530623505496,"score_spread":0.20914991312064907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2584477044","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.454412,0.0016489576,0.53355205,0.00096609636,0.00004664391,0.00025300417,0.0014250628,0.0038597463,0.0038364339],"genre_scores_gemma":[0.8100376,0.00033826093,0.18510592,0.00022356979,0.000059187525,0.00024795206,0.0028741914,0.00030625396,0.00080708717],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99405116,0.002982214,0.00041410202,0.0017543306,0.0006363379,0.00016172134],"domain_scores_gemma":[0.9830875,0.013417157,0.0007627955,0.0012440592,0.0011666153,0.0003217958],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003498079,0.0010024867,0.00097452145,0.0033583941,0.0008741082,0.0024587077,0.0013136131,0.0010619543,0.0015539794],"category_scores_gemma":[0.018224739,0.00073434436,0.0014018014,0.0013108591,0.0008633478,0.0050054654,0.0022942098,0.0013925106,0.00077775907],"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":[0.0014288516,0.0009751874,0.07013193,0.0013678706,0.00074167416,0.0013003808,0.0121470345,0.066128455,0.119248696,0.0032722917,0.005066021,0.7181917],"study_design_scores_gemma":[0.000094547504,0.00066849875,0.052989494,0.00018189313,0.000392856,0.0011350111,0.0048089405,0.88034743,0.02860218,0.016128099,0.014447432,0.00020358304],"about_ca_topic_score_codex":0.0030315393,"about_ca_topic_score_gemma":0.0039032972,"teacher_disagreement_score":0.003498079,"about_ca_system_score_codex":0.00060563255,"about_ca_system_score_gemma":0.0007784594,"threshold_uncertainty_score":0.018499851},"labels":[],"label_agreement":null},{"id":"W2585691643","doi":"10.1609/aimag.v37i4.2684","title":"Collaborative Language Grounding Toward Situated Human‐Robot Dialogue","year":2016,"lang":"en","type":"article","venue":"AI Magazine","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":68,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Thomson Reuters (Canada)","funders":"Office of Naval Research; University of California, Los Angeles; National Science Foundation","keywords":"Situated; Computer science; Human–robot interaction; Common ground; Robot; Human–computer interaction; Representation (politics); Joint attention; Bridge (graph theory); Perception; Action (physics); Ground; Artificial intelligence; Engineering; Communication; Psychology","score_opus":0.014371559619714536,"score_gpt":0.2704817801697774,"score_spread":0.2561102205500629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2585691643","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024867576,0.00038540314,0.95696783,0.00096630724,0.00007252057,0.00009558257,0.000017930424,0.00092763983,0.015699277],"genre_scores_gemma":[0.6607942,0.00031364197,0.33468693,0.00020836826,0.00006664558,0.0002174709,0.000063740285,0.00019172348,0.0034572517],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9931958,0.004046636,0.000283039,0.0010943697,0.0009516963,0.0004284404],"domain_scores_gemma":[0.9912286,0.005670598,0.00057665823,0.0014655772,0.00061686593,0.0004417338],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005268596,0.0010309637,0.00080225326,0.0009764243,0.002969784,0.0048646624,0.002661091,0.0031142312,0.004587845],"category_scores_gemma":[0.014982413,0.00095090753,0.0012595148,0.00058953743,0.007262162,0.008255428,0.011002358,0.0027539558,0.0010308847],"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":[0.00061686663,0.00034466368,0.0017889387,0.0006248235,0.00014697152,0.0021515572,0.046683945,0.094918504,0.05247113,0.53499913,0.0057434305,0.25951007],"study_design_scores_gemma":[0.0001843984,0.00033441116,0.0009264215,0.00017660935,0.00011047693,0.0005948799,0.006893085,0.3778834,0.022332205,0.5462256,0.04419532,0.00014323746],"about_ca_topic_score_codex":0.0034652012,"about_ca_topic_score_gemma":0.0027127955,"teacher_disagreement_score":0.005268596,"about_ca_system_score_codex":0.0015650808,"about_ca_system_score_gemma":0.0018657225,"threshold_uncertainty_score":0.027863264},"labels":[],"label_agreement":null},{"id":"W2597698186","doi":"10.5555/3076132.3076143","title":"Investigating the Impact of Cooperative Communication Mechanics on Player Performance in Portal 2","year":2016,"lang":"en","type":"article","venue":"Graphics Interface","topic":"Speech and dialogue systems","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":"Gesture; Computer science; Interdependence; Game mechanics; Human–computer interaction; Artificial intelligence","score_opus":0.03177307556679857,"score_gpt":0.28778267447468975,"score_spread":0.25600959890789116,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2597698186","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":[0.99740404,0.0000107764,0.0012829945,0.000021931923,0.000004543509,0.00003068359,0.000021766227,0.000029175055,0.0011940076],"genre_scores_gemma":[0.99754286,0.000012449529,0.0015296858,0.000014127184,0.000003245548,0.00006519386,0.00004143018,0.000014718273,0.0007763856],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99764794,0.0012486443,0.00013052595,0.0003282298,0.0003501093,0.0002944928],"domain_scores_gemma":[0.98324144,0.011900528,0.0014542115,0.0008250278,0.001032502,0.0015462767],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002906662,0.0007144364,0.00043227818,0.00037848507,0.00050629245,0.002273836,0.000735296,0.00071361987,0.0048735766],"category_scores_gemma":[0.023977088,0.00027341078,0.00019342848,0.00017716324,0.00079744693,0.0014160912,0.002115307,0.0007885976,0.00065842376],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.015857594,0.014411716,0.40050524,0.0011795433,0.0002573366,0.0019298946,0.044617247,0.01094588,0.3179729,0.003505772,0.0019124671,0.18690437],"study_design_scores_gemma":[0.00096227037,0.056935787,0.7593513,0.00021774613,0.00031962804,0.0013085529,0.032685384,0.052287795,0.08433805,0.0033145514,0.008024765,0.00025409294],"about_ca_topic_score_codex":0.0010991509,"about_ca_topic_score_gemma":0.0017531795,"teacher_disagreement_score":0.0048735766,"about_ca_system_score_codex":0.0004316309,"about_ca_system_score_gemma":0.00048061964,"threshold_uncertainty_score":0.016303718},"labels":[],"label_agreement":null},{"id":"W260116920","doi":"10.3217/jucs-005-09-0610","title":"Synchronization Expressions and Languages","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Speech and dialogue systems","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":"Western University; Queen's University","funders":"","keywords":"Synchronization (alternating current); Computer science; Linguistics; Telecommunications; Philosophy","score_opus":0.03194098606433664,"score_gpt":0.23912136998047068,"score_spread":0.20718038391613403,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W260116920","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0062064365,0.0073636235,0.90240633,0.0043012626,0.0028971168,0.00045892125,0.0025462408,0.0038178046,0.07000232],"genre_scores_gemma":[0.18386972,0.010424307,0.7150038,0.005368302,0.004207545,0.0028806063,0.007062593,0.0037295255,0.067453586],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9918909,0.0027254089,0.0013596396,0.0019060272,0.0014027999,0.000715185],"domain_scores_gemma":[0.9952335,0.0019199813,0.00063368655,0.00088396616,0.0011083264,0.00022061524],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048550186,0.0021668908,0.0010439791,0.0031721941,0.0024536196,0.0069707106,0.0022473969,0.0030915607,0.015141775],"category_scores_gemma":[0.008500984,0.0010965745,0.0016469369,0.004140882,0.0067931516,0.015293265,0.0050689774,0.0057306,0.0076189376],"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":[0.000030895633,0.000010727409,0.000095738,0.00023053295,0.000012901835,0.00009898376,0.00067972916,0.0004177455,0.0011273397,0.9683441,0.011007057,0.01794433],"study_design_scores_gemma":[0.000025424459,0.000032910735,0.00012562235,0.0002085959,0.000027191792,0.00051752676,0.00029024735,0.0027846864,0.0023602762,0.46584898,0.5277379,0.00004062174],"about_ca_topic_score_codex":0.0013245455,"about_ca_topic_score_gemma":0.0006274081,"teacher_disagreement_score":0.015141775,"about_ca_system_score_codex":0.0021306917,"about_ca_system_score_gemma":0.002343238,"threshold_uncertainty_score":0.050654292},"labels":[],"label_agreement":null},{"id":"W2601776331","doi":"","title":"Voice and multimodal technology for the mobile worker","year":2004,"lang":"en","type":"article","venue":"NPARC","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Research Council Canada","keywords":"Usability; Mobile device; Enabling; Computer science; Key (lock); Mobile technology; Field (mathematics); Wireless; Mobile telephony; Human–computer interaction; Multimedia; Telecommunications; World Wide Web; Mobile radio; Computer security","score_opus":0.009666328789336535,"score_gpt":0.23971351857964962,"score_spread":0.23004718979031308,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2601776331","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.035199314,0.044464957,0.5221944,0.012906725,0.0023483625,0.00040137692,0.0005550928,0.0048601828,0.37706953],"genre_scores_gemma":[0.44819656,0.028063817,0.20399328,0.0052808486,0.0022095386,0.0006009561,0.0005561222,0.0004728146,0.31062597],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995517,0.00015782334,0.0000234094,0.000062146355,0.00016873651,0.000036266458],"domain_scores_gemma":[0.99960345,0.00018247173,0.000028716098,0.000054148302,0.00009889313,0.00003233479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005760215,0.00034088484,0.00021609402,0.00051322754,0.00056580175,0.0019685416,0.00047437538,0.0015212529,0.017365336],"category_scores_gemma":[0.001449999,0.00012202382,0.00019198188,0.00036014876,0.00082704495,0.0016925499,0.0013301718,0.0006922415,0.0048654936],"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":[0.0002857972,0.00005830687,0.00058109366,0.000871966,0.000018885888,0.0010741645,0.0021396475,0.0007494885,0.083230585,0.13550024,0.0489113,0.72657853],"study_design_scores_gemma":[0.000048472426,0.00038713703,0.0023724202,0.00078682194,0.00005080768,0.005021906,0.0012255283,0.006300918,0.024780551,0.036106277,0.92283094,0.00008821128],"about_ca_topic_score_codex":0.00057919894,"about_ca_topic_score_gemma":0.0007199041,"teacher_disagreement_score":0.017365336,"about_ca_system_score_codex":0.00043273007,"about_ca_system_score_gemma":0.00041872665,"threshold_uncertainty_score":0.058092833},"labels":[],"label_agreement":null},{"id":"W2602593119","doi":"10.21307/ijssis-2017-824","title":"Prototyping using a Pattern Technique and a Context-Based Bayesian Network in Multimodal Systems","year":2015,"lang":"en","type":"article","venue":"International Journal on Smart Sensing and Intelligent Systems","topic":"Speech and dialogue systems","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":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Computer science; Modalities; Gesture; Modality (human–computer interaction); Context (archaeology); Human–computer interaction; Artificial intelligence; Bayesian network; Machine learning; Natural (archaeology); Multimodality","score_opus":0.04570575238656201,"score_gpt":0.2871893492377361,"score_spread":0.2414835968511741,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2602593119","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01240163,0.000028872157,0.9865041,0.00006848984,0.0000060059187,0.000034401597,0.000010001139,0.00014798364,0.00079852575],"genre_scores_gemma":[0.3814528,0.00008088739,0.6171191,0.000031970616,0.000012844402,0.0001761106,0.000029125515,0.000056352455,0.0010408373],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99850214,0.00080538035,0.000067047244,0.00021840674,0.0003309867,0.00007608251],"domain_scores_gemma":[0.99734586,0.0018736748,0.00017931158,0.00027215632,0.0002537838,0.00007516602],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021077131,0.00046884842,0.0005783067,0.0006998732,0.000703005,0.0009555831,0.0010040288,0.0009684764,0.003170361],"category_scores_gemma":[0.00918177,0.00058689964,0.00071007526,0.00068184955,0.0014440413,0.0021946107,0.0015901914,0.00082979165,0.00032190236],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00041906553,0.00013963411,0.003128586,0.00022303009,0.00008677672,0.0007202257,0.001371985,0.50661916,0.026923163,0.21022101,0.0011913987,0.248956],"study_design_scores_gemma":[0.00001625985,0.00003578404,0.00022760053,0.000013216518,0.000010796868,0.00007500024,0.000041900068,0.96869546,0.0034453059,0.026312936,0.0011132794,0.00001251742],"about_ca_topic_score_codex":0.0030788248,"about_ca_topic_score_gemma":0.002358497,"teacher_disagreement_score":0.003170361,"about_ca_system_score_codex":0.0005843379,"about_ca_system_score_gemma":0.00054914696,"threshold_uncertainty_score":0.011146784},"labels":[],"label_agreement":null},{"id":"W2602799059","doi":"10.1162/coli_a_00290","title":"Identifying and Avoiding Confusion in Dialogue with People with Alzheimer's Disease","year":2017,"lang":"en","type":"article","venue":"Computational Linguistics","topic":"Speech and dialogue systems","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":"Toronto Rehabilitation Institute; University of Toronto","funders":"National Institute on Deafness and Other Communication Disorders; National Institutes of Health; Alzheimer Society; AGE-WELL; Carnegie Mellon University; Natural Sciences and Engineering Research Council of Canada; University of Pittsburgh","keywords":"Computer science; Confusion; Dementia; Cognitive psychology; Vocabulary; Function (biology); Cognition; Process (computing); Parsing; Spoken language; Decision tree; Artificial intelligence; Natural language processing; Psychology; Disease; Linguistics; Medicine","score_opus":0.030383408812927348,"score_gpt":0.2762257908780106,"score_spread":0.24584238206508324,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2602799059","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":[0.8380473,0.0010281545,0.15302041,0.0010304819,0.00011061579,0.0002441776,0.00026755765,0.001992485,0.0042588147],"genre_scores_gemma":[0.9259674,0.0002596741,0.07192369,0.00018253618,0.000035524517,0.00008616488,0.0004289525,0.000068946305,0.0010470517],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99390537,0.0044534206,0.00025133416,0.0007625032,0.00036535304,0.00026197478],"domain_scores_gemma":[0.9884255,0.00895701,0.00084944465,0.00028708103,0.0011027212,0.00037827552],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046513267,0.0010975845,0.0008444529,0.0014440118,0.0011624009,0.002510287,0.0007909318,0.0014586069,0.00096514146],"category_scores_gemma":[0.022741817,0.00039155097,0.0005500496,0.00035890186,0.0008199176,0.0026136965,0.002357197,0.0010133494,0.00089603855],"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":[0.0024182484,0.0010410115,0.11044578,0.0010895971,0.00023259273,0.0009254878,0.037997417,0.032169838,0.042816862,0.0029505016,0.0062621012,0.76165056],"study_design_scores_gemma":[0.00010940039,0.0013493744,0.06467492,0.00039260852,0.00028166754,0.0015066063,0.019511025,0.85017604,0.03619826,0.015636947,0.009867811,0.00029538528],"about_ca_topic_score_codex":0.0032756594,"about_ca_topic_score_gemma":0.003939286,"teacher_disagreement_score":0.0046513267,"about_ca_system_score_codex":0.00059847336,"about_ca_system_score_gemma":0.001175967,"threshold_uncertainty_score":0.024598837},"labels":[],"label_agreement":null},{"id":"W2606346295","doi":"10.1080/09588221.2017.1312463","title":"The pedagogical use of mobile speech synthesis (TTS): focus on French liaison","year":2017,"lang":"en","type":"article","venue":"Computer Assisted Language Learning","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":73,"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; Concordia University","funders":"","keywords":"Pronunciation; Psychology; Conversation; Consonant; Vowel; Linguistics; Categorization; Computer science; Mathematics education; Speech recognition; Communication; Artificial intelligence","score_opus":0.0616561466476619,"score_gpt":0.31008609363100426,"score_spread":0.24842994698334236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2606346295","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":[0.99679595,0.0002624712,0.0010688694,0.000088271634,0.000008760303,0.0000974489,0.000021031874,0.000020419679,0.001636776],"genre_scores_gemma":[0.9944754,0.00063840003,0.0032199621,0.00008193845,0.000027316451,0.00020739931,0.0000577521,0.0000102272015,0.001281631],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9983199,0.000974482,0.00007156121,0.0002394018,0.00020508839,0.0001896036],"domain_scores_gemma":[0.99591404,0.0029378438,0.00034126433,0.00022612215,0.0003234124,0.00025731305],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013990339,0.0005965829,0.0004585493,0.00052399817,0.0005068627,0.00070202956,0.00045978095,0.0006992102,0.002363876],"category_scores_gemma":[0.0049349004,0.00014896144,0.0004177984,0.0003588772,0.00059542776,0.00061920483,0.0008464238,0.00038870887,0.00040827913],"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":[0.0031545234,0.015176048,0.0935432,0.0028820327,0.00021537096,0.0025381185,0.07204917,0.0025611497,0.13514929,0.0016344233,0.00092129793,0.67017525],"study_design_scores_gemma":[0.00082822546,0.12488893,0.627015,0.00077028706,0.0010080689,0.0050764284,0.054630063,0.0061139353,0.13938609,0.0014300928,0.038639832,0.00021314857],"about_ca_topic_score_codex":0.0031272275,"about_ca_topic_score_gemma":0.00492284,"teacher_disagreement_score":0.0031272275,"about_ca_system_score_codex":0.00064376445,"about_ca_system_score_gemma":0.000777619,"threshold_uncertainty_score":0.007907987},"labels":[],"label_agreement":null},{"id":"W2618015847","doi":"10.21437/interspeech.2017-1178","title":"ASR Error Management for Improving Spoken Language Understanding","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"McGill University","funders":"Agence Nationale de la Recherche","keywords":"Computer science; Word error rate; Spoken language; Encoder; Word (group theory); Artificial intelligence; Task (project management); Set (abstract data type); Conditional random field; Natural language processing; Speech recognition; State (computer science); Language model; Machine learning; Algorithm","score_opus":0.07849318842714537,"score_gpt":0.3097299478907526,"score_spread":0.23123675946360722,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2618015847","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.048693527,0.0005493473,0.94449764,0.00020620554,0.000065224194,0.00004543311,0.00012224383,0.004814896,0.0010053404],"genre_scores_gemma":[0.646564,0.00033167744,0.34863707,0.0001432313,0.000108873006,0.00008093989,0.00045714685,0.00066758564,0.003009432],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9966402,0.0010186725,0.00022322369,0.0009646901,0.001008091,0.0001450537],"domain_scores_gemma":[0.9928536,0.0040022125,0.0007533113,0.0010221192,0.0012398476,0.00012893992],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026493918,0.0013996456,0.0009949247,0.001175785,0.00044167816,0.0014244275,0.0014631553,0.0012025629,0.0029565052],"category_scores_gemma":[0.011195057,0.00034650505,0.00050158054,0.0005538569,0.0008992879,0.0025556267,0.0017020467,0.0016488928,0.0014342928],"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":[0.0006265275,0.00018941598,0.0027781357,0.00035360068,0.0000813387,0.00020696594,0.00082676794,0.06989741,0.12664312,0.0055411053,0.002453538,0.79040205],"study_design_scores_gemma":[0.000029056966,0.00026012352,0.0023505636,0.00003521782,0.00007189611,0.00029096927,0.000168925,0.8654944,0.120915554,0.00717145,0.003155506,0.000056277222],"about_ca_topic_score_codex":0.001804937,"about_ca_topic_score_gemma":0.001528299,"teacher_disagreement_score":0.0029565052,"about_ca_system_score_codex":0.00054483244,"about_ca_system_score_gemma":0.0007506498,"threshold_uncertainty_score":0.014011502},"labels":[],"label_agreement":null},{"id":"W2620910952","doi":"10.1016/j.cognition.2017.05.026","title":"Compounding as Abstract Operation in Semantic Space: Investigating relational effects through a large-scale, data-driven computational model","year":2017,"lang":"en","type":"article","venue":"Cognition","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":60,"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":"Natural language processing; Priming (agriculture); Relational calculus; Computer science; Semantics (computer science); Artificial intelligence; Distributional semantics; Space (punctuation); Representation (politics); Relational database; Relational model; Semantic similarity; Information retrieval; Programming language","score_opus":0.07953525558684951,"score_gpt":0.32694263879146646,"score_spread":0.24740738320461694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2620910952","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2954411,0.00018805798,0.69720036,0.0008257504,0.000036640566,0.0000659041,0.00036328065,0.000594593,0.005284354],"genre_scores_gemma":[0.9141715,0.00011367957,0.084309064,0.00006402757,0.00001799238,0.00007851266,0.00022827717,0.00018010571,0.0008368811],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990651,0.00038900954,0.000047530335,0.0002771459,0.00015971651,0.0000615168],"domain_scores_gemma":[0.9905738,0.0072042616,0.00038935654,0.0012271355,0.00032328544,0.00028208215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021305254,0.00048436818,0.0012960662,0.0007669064,0.00088534586,0.0044547953,0.002526399,0.0012884187,0.006953166],"category_scores_gemma":[0.012144252,0.00084937795,0.0017697201,0.0010404399,0.0032713434,0.011640332,0.0026734776,0.0025736697,0.00057077414],"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":[0.00059138675,0.00033718027,0.0054585636,0.00036128066,0.000239754,0.00046947773,0.002756762,0.3123425,0.017619548,0.61382854,0.0010364926,0.044958465],"study_design_scores_gemma":[0.000030932326,0.000042084972,0.0006324596,0.000007830895,0.00003690718,0.000043860597,0.0001820506,0.76053303,0.001611399,0.23632899,0.00052693934,0.000023451934],"about_ca_topic_score_codex":0.0058437684,"about_ca_topic_score_gemma":0.004696785,"teacher_disagreement_score":0.006953166,"about_ca_system_score_codex":0.00107972,"about_ca_system_score_gemma":0.0014667581,"threshold_uncertainty_score":0.023260713},"labels":[],"label_agreement":null},{"id":"W2623619896","doi":"","title":"Sculpter les mots, le langage, les mettre en espace / Sculpt Words and Language, Place Words in Space","year":2006,"lang":"fr","type":"article","venue":"Espace Sculpture","topic":"Speech and dialogue systems","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":"Space (punctuation); Computer science; Linguistics; Philosophy","score_opus":0.009556946371023506,"score_gpt":0.23391009039670765,"score_spread":0.22435314402568415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2623619896","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":[0.12607405,0.005299553,0.31694406,0.015683757,0.003678908,0.00021483401,0.0018345128,0.008284888,0.52198553],"genre_scores_gemma":[0.6164438,0.002473763,0.0923223,0.0020349124,0.00086955004,0.00009574784,0.0013734022,0.003648482,0.2807381],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995364,0.00014221591,0.000026706291,0.000082935134,0.00016649939,0.000045375415],"domain_scores_gemma":[0.9988857,0.00037433155,0.00008561922,0.00022264982,0.00030399437,0.00012774307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007564058,0.000818727,0.00031312348,0.00067718717,0.0011527439,0.003698053,0.00050093356,0.0012958414,0.024682255],"category_scores_gemma":[0.0050123623,0.0002584927,0.000273398,0.0005185758,0.002369793,0.0045242184,0.001615226,0.001910847,0.012685532],"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":[0.0004518239,0.00006838991,0.002922219,0.0008457233,0.000048351532,0.0014594723,0.03623547,0.0010481433,0.110059075,0.24306287,0.097793475,0.5060051],"study_design_scores_gemma":[0.000041519932,0.00024577696,0.0061620865,0.00039219682,0.000047749785,0.0044509186,0.025161067,0.006116495,0.048979476,0.074579634,0.8336851,0.00013798226],"about_ca_topic_score_codex":0.004013075,"about_ca_topic_score_gemma":0.0048824693,"teacher_disagreement_score":0.024682255,"about_ca_system_score_codex":0.0005269437,"about_ca_system_score_gemma":0.0007827313,"threshold_uncertainty_score":0.082570374},"labels":[],"label_agreement":null},{"id":"W2624448691","doi":"10.18653/v1/w17-2626","title":"A Frame Tracking Model for Memory-Enhanced Dialogue Systems","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Université de Montréal","funders":"","keywords":"Utterance; Frame (networking); Computer science; Task (project management); Tracking (education); Set (abstract data type); Baseline (sea); State (computer science); Artificial intelligence; Algorithm; Telecommunications; Programming language; Engineering","score_opus":0.07295084213083664,"score_gpt":0.3025950117516825,"score_spread":0.22964416962084588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2624448691","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028725604,0.0013108418,0.9598271,0.0005970937,0.00015404925,0.00019273444,0.001844589,0.004449186,0.0028987138],"genre_scores_gemma":[0.6049403,0.0008917624,0.38001078,0.00036216056,0.00016521348,0.00067319727,0.0036043893,0.0004260158,0.008926128],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99887246,0.00037662816,0.00008648411,0.0004165627,0.00015641219,0.00009147078],"domain_scores_gemma":[0.99815315,0.0010553808,0.00012488067,0.0002596546,0.00031184204,0.0000949848],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020441855,0.0011485941,0.0012082205,0.0008845432,0.0005646774,0.0018514433,0.0025905704,0.001807862,0.004387241],"category_scores_gemma":[0.00619238,0.00056987064,0.0011720513,0.00086256466,0.00052105216,0.0024827467,0.001160476,0.0018342057,0.0023416202],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013456357,0.0003707729,0.0025391625,0.00042556174,0.00019239611,0.00038592852,0.0009601553,0.5829961,0.01009044,0.03889909,0.014968592,0.34682617],"study_design_scores_gemma":[0.00001999858,0.000043227144,0.0001905017,0.000015222305,0.000020448211,0.000033365337,0.000019816214,0.9852459,0.0010888343,0.010874913,0.0024341524,0.000013609394],"about_ca_topic_score_codex":0.014962735,"about_ca_topic_score_gemma":0.014304755,"teacher_disagreement_score":0.014962735,"about_ca_system_score_codex":0.0015216477,"about_ca_system_score_gemma":0.0014141054,"threshold_uncertainty_score":0.0297513},"labels":[],"label_agreement":null},{"id":"W2636190056","doi":"","title":"Towards a Context-Aware and Pervasive Multimodality","year":2007,"lang":"en","type":"article","venue":"Research in computing science","topic":"Speech and dialogue systems","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":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"","keywords":"Multimodality; Context (archaeology); Computer science; World Wide Web; History","score_opus":0.12440777723025787,"score_gpt":0.43283579689206586,"score_spread":0.308428019661808,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2636190056","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":[0.012714165,0.0010234553,0.9709688,0.00078567944,0.00013995208,0.00009689723,0.00007793058,0.0016588566,0.012534228],"genre_scores_gemma":[0.24706319,0.0012994884,0.735717,0.00062034006,0.00017612023,0.000229407,0.00020102074,0.00027559442,0.014417777],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989618,0.00029880993,0.000057755173,0.0002900582,0.00030872237,0.000082920116],"domain_scores_gemma":[0.9991202,0.00023936051,0.00004204108,0.00020906921,0.0002864609,0.00010285474],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012714311,0.00060058304,0.00065459555,0.0006130505,0.00089861336,0.0025679243,0.0014630124,0.0016359845,0.004427359],"category_scores_gemma":[0.0023912578,0.00058471767,0.0006364705,0.0004746124,0.0013790262,0.0046497225,0.005348193,0.0020425897,0.00212323],"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":[0.0003205382,0.00035589773,0.0014582012,0.0008454171,0.00014351934,0.00042621265,0.0037160395,0.016863829,0.23173943,0.28656697,0.00931985,0.44824407],"study_design_scores_gemma":[0.00009196582,0.0006589459,0.0023723682,0.00049795164,0.00033229843,0.0016222053,0.0029486753,0.2790598,0.13716592,0.29901874,0.27602634,0.00020482135],"about_ca_topic_score_codex":0.0010442919,"about_ca_topic_score_gemma":0.0017653235,"teacher_disagreement_score":0.004427359,"about_ca_system_score_codex":0.00036563043,"about_ca_system_score_gemma":0.0007898562,"threshold_uncertainty_score":0.014811039},"labels":[],"label_agreement":null},{"id":"W2734029172","doi":"10.48550/arxiv.1703.05423","title":"End-to-end optimization of goal-driven and visually grounded dialogue systems Harm de Vries","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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 de Montréal","funders":"","keywords":"Computer science; Task (project management); Utterance; Artificial intelligence; Context (archaeology); Reinforcement learning; Sequence (biology); Object (grammar); Human–computer interaction","score_opus":0.05763941532819348,"score_gpt":0.20975745431906306,"score_spread":0.1521180389908696,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2734029172","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04680854,0.0003501105,0.945509,0.00043046914,0.000075203876,0.0001620984,0.00010412517,0.001737579,0.004822918],"genre_scores_gemma":[0.83968437,0.0001352605,0.15337603,0.00021207421,0.000032959364,0.00029537862,0.00024071847,0.00027103888,0.0057521635],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921393,0.0003142884,0.000030834544,0.00023841992,0.00009842084,0.00010406749],"domain_scores_gemma":[0.9984471,0.0010780573,0.0000929445,0.00009472634,0.00016686511,0.00012023589],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016487051,0.0013429008,0.0010380598,0.0004142405,0.0005548981,0.0011565468,0.0011534012,0.0016581732,0.0036723483],"category_scores_gemma":[0.00480139,0.00064273697,0.000570341,0.00021747827,0.0011118541,0.0010438517,0.0018843971,0.0017567337,0.00072617084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015355267,0.00011446094,0.00045945673,0.00009359679,0.000036757974,0.00009333401,0.00016870236,0.9357467,0.0035211514,0.005816572,0.0013818087,0.052414007],"study_design_scores_gemma":[0.000008930911,0.000024673267,0.00004401813,0.000004646278,0.00000270399,0.0000054273264,0.0000106570615,0.9967073,0.0005020754,0.0024641897,0.00022261283,0.0000027388398],"about_ca_topic_score_codex":0.006069632,"about_ca_topic_score_gemma":0.0064616404,"teacher_disagreement_score":0.006069632,"about_ca_system_score_codex":0.0014579605,"about_ca_system_score_gemma":0.0018175626,"threshold_uncertainty_score":0.012285292},"labels":[],"label_agreement":null},{"id":"W2736231204","doi":"10.3390/languages2030011","title":"Mobilizing Instruction in a Second-Language Context: Learners’ Perceptions of Two Speech Technologies","year":2017,"lang":"en","type":"article","venue":"Languages","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":42,"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; Concordia University","funders":"Social Sciences and Humanities Research Council of Canada; Concordia University","keywords":"Pronunciation; Context (archaeology); Perception; Autonomy; Computer science; Vowel; Psychology; Mobile device; Language acquisition; Linguistics; Mathematics education; Speech recognition; World Wide Web","score_opus":0.014527745874947665,"score_gpt":0.29405295466456366,"score_spread":0.279525208789616,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2736231204","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":[0.99724907,0.00012720593,0.00056007504,0.0001409952,0.000006071248,0.00001534605,0.000008510651,0.000007847598,0.0018848926],"genre_scores_gemma":[0.9984333,0.00015607556,0.00042971526,0.00009657757,0.0000060185716,0.000024614868,0.000012642235,0.0000060405832,0.0008349655],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.99700886,0.0016231852,0.00013711523,0.0003240212,0.00057879434,0.00032803678],"domain_scores_gemma":[0.99295205,0.004068754,0.001134858,0.00017755383,0.0006030975,0.001063752],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034624313,0.000645147,0.0005992611,0.0011222247,0.0017117751,0.0063381465,0.00062066683,0.002113147,0.0035397694],"category_scores_gemma":[0.009572491,0.0003617385,0.00043468166,0.00035185748,0.0027216582,0.0030913006,0.003703952,0.0015538039,0.0006494431],"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":[0.00025785997,0.000696851,0.069569886,0.00036333513,0.000045577453,0.0011498601,0.88460785,0.00028986917,0.019718554,0.00094252295,0.00026427317,0.022093555],"study_design_scores_gemma":[0.00004006577,0.0017681784,0.045866888,0.00016621505,0.000067183464,0.0014069064,0.9337088,0.0009149495,0.005189779,0.00066934276,0.010081476,0.000120223056],"about_ca_topic_score_codex":0.0015571824,"about_ca_topic_score_gemma":0.0015443056,"teacher_disagreement_score":0.0063381465,"about_ca_system_score_codex":0.0005365364,"about_ca_system_score_gemma":0.00065925263,"threshold_uncertainty_score":0.018311322},"labels":[],"label_agreement":null},{"id":"W2745236273","doi":"10.1007/978-3-319-02237-6_24","title":"Complexity Approaches to Computer-Assisted Language Learning","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Selection (genetic algorithm); Language acquisition; Cognitive science; Complex adaptive system; Artificial intelligence; Management science; Data science; Mathematics education; Psychology; Engineering","score_opus":0.2284831031196341,"score_gpt":0.26725006197210893,"score_spread":0.03876695885247483,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2745236273","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0057543083,0.015361067,0.74136585,0.002754806,0.00065122824,0.00006444919,0.00015339217,0.00076006906,0.23313475],"genre_scores_gemma":[0.3203755,0.029767167,0.31596464,0.0008780506,0.0033017145,0.0004924058,0.00091057946,0.001052822,0.3272572],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99931526,0.00014560498,0.00003032286,0.0000729736,0.00039990753,0.000035859597],"domain_scores_gemma":[0.9981394,0.001401933,0.00005468329,0.00014927903,0.00020001784,0.00005458773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045249867,0.0009066137,0.0006214414,0.0009890735,0.00066352374,0.002097493,0.0011946219,0.0007250361,0.018288327],"category_scores_gemma":[0.0028880895,0.0003356599,0.00054005923,0.0011185958,0.0020108253,0.0035532268,0.0017137032,0.0022586572,0.0041172937],"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":[0.000018773004,0.00003278676,0.000096291595,0.00023078697,0.000017576569,0.00002948278,0.00023999032,0.011738546,0.0009943894,0.7889047,0.018305866,0.17939079],"study_design_scores_gemma":[0.000004202654,0.000015360461,0.00015959251,0.000068987836,0.0000069203993,0.000057070494,0.00005692091,0.0221479,0.0009166743,0.8978468,0.07870411,0.00001537921],"about_ca_topic_score_codex":0.0014170822,"about_ca_topic_score_gemma":0.0016797388,"teacher_disagreement_score":0.018288327,"about_ca_system_score_codex":0.0017519555,"about_ca_system_score_gemma":0.00079716695,"threshold_uncertainty_score":0.061180532},"labels":[],"label_agreement":null},{"id":"W2751903103","doi":"","title":"Evaluating Software for Affective Education: A Case Study of Affective Heuristics","year":2016,"lang":"en","type":"article","venue":"EdMedia + Innovate Learning","topic":"Speech and dialogue systems","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":"Heuristics; Psychology; Affect (linguistics); Computer science; Social psychology; Software; Cognitive psychology; Applied psychology; Artificial intelligence; Communication","score_opus":0.04468560444287628,"score_gpt":0.35178758965249207,"score_spread":0.3071019852096158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751903103","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":[0.97029054,0.00008719901,0.018159948,0.00036502513,0.00001435569,0.00017122012,0.000034225675,0.00025249395,0.010625026],"genre_scores_gemma":[0.9797331,0.00004228367,0.017963668,0.00009602885,0.0000045505813,0.000048721336,0.000043113698,0.000080169404,0.0019882591],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9937342,0.004455521,0.00028030103,0.00028340452,0.00086731865,0.00037934675],"domain_scores_gemma":[0.9429565,0.04939485,0.0012328519,0.002595322,0.0025009578,0.0013194854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008237153,0.0005264891,0.0003932615,0.0010175422,0.0017552635,0.003735862,0.0017047095,0.0020324849,0.002634895],"category_scores_gemma":[0.045236945,0.0003174646,0.00040113786,0.0008519941,0.0012614928,0.002213915,0.0018563404,0.0012604112,0.0005450815],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0030460565,0.013402521,0.10077138,0.0012564623,0.00022222805,0.010053923,0.16656144,0.03086336,0.046021137,0.037983682,0.009171712,0.58064616],"study_design_scores_gemma":[0.0012351437,0.011292072,0.10443647,0.0008833284,0.0005975591,0.008814796,0.18798922,0.42903757,0.10133559,0.051585857,0.10216528,0.0006270798],"about_ca_topic_score_codex":0.0035697066,"about_ca_topic_score_gemma":0.0059079626,"teacher_disagreement_score":0.008237153,"about_ca_system_score_codex":0.0016835171,"about_ca_system_score_gemma":0.001152279,"threshold_uncertainty_score":0.04356277},"labels":[],"label_agreement":null},{"id":"W2751916917","doi":"10.1145/3098279.3119919","title":"Speech and Hands-free interaction","year":2017,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Modalities; Human–computer interaction; Focus (optics); Modality (human–computer interaction); Usability; Natural (archaeology); Natural language; Field (mathematics); Artificial intelligence","score_opus":0.026582319020731084,"score_gpt":0.2728499934417385,"score_spread":0.24626767442100742,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2751916917","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":[0.055707473,0.13196784,0.29449904,0.01307951,0.0033698692,0.0001524749,0.0007441487,0.0026443822,0.49783522],"genre_scores_gemma":[0.83389884,0.027512746,0.02697841,0.002988578,0.002529302,0.00017623525,0.00040403215,0.00027216776,0.10523954],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984907,0.00051098166,0.00007824038,0.0003556364,0.00044889477,0.000115637966],"domain_scores_gemma":[0.9980635,0.001377885,0.00012366184,0.0001583129,0.00017616991,0.000100517005],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081230083,0.0006277385,0.0004292046,0.00084396056,0.00063348963,0.0033286342,0.00061290356,0.0022903734,0.01963078],"category_scores_gemma":[0.004162127,0.00023535114,0.00028366287,0.00046816785,0.0035355203,0.0027879635,0.0021538886,0.00086885976,0.0046269586],"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":[0.0004286881,0.000090408335,0.001672281,0.0017600927,0.00009376231,0.0014215966,0.004925357,0.0074394867,0.019852005,0.41940388,0.023910195,0.5190022],"study_design_scores_gemma":[0.00007795091,0.00038300635,0.012269243,0.0012121445,0.00009833021,0.0050385557,0.0020441066,0.014815883,0.006819315,0.69140494,0.26562837,0.00020815435],"about_ca_topic_score_codex":0.0014562828,"about_ca_topic_score_gemma":0.00071298354,"teacher_disagreement_score":0.01963078,"about_ca_system_score_codex":0.0005821921,"about_ca_system_score_gemma":0.00041180121,"threshold_uncertainty_score":0.06567156},"labels":[],"label_agreement":null},{"id":"W2753167600","doi":"","title":"Pola: A Language for PTIME Programming.","year":2009,"lang":"en","type":"article","venue":"Fixed Points in Computer Science","topic":"Speech and dialogue systems","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 Calgary","funders":"","keywords":"P; Computer science; Programming language; Algorithm; Time complexity","score_opus":0.012784528557885068,"score_gpt":0.2724395502514123,"score_spread":0.2596550216935272,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2753167600","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":[0.0026729403,0.0005157187,0.9180991,0.000628681,0.00031107353,0.00015214857,0.007981741,0.051565867,0.018072683],"genre_scores_gemma":[0.1279741,0.0016969326,0.76683414,0.0018727061,0.00036285218,0.0020259097,0.027590627,0.028426,0.043216787],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99901557,0.00025646866,0.00018254103,0.00020748243,0.0002188972,0.000119022334],"domain_scores_gemma":[0.99867165,0.0005596963,0.00010825156,0.00037517154,0.00019896953,0.00008636107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014392979,0.00092487107,0.00080683327,0.0008339667,0.0009749185,0.003720245,0.0028291687,0.0010827313,0.033631943],"category_scores_gemma":[0.0045057745,0.001411709,0.0019515565,0.001380398,0.0010682086,0.0065577477,0.0031196466,0.0037964606,0.017195007],"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":[0.0011388583,0.00010465656,0.0011141138,0.0022493112,0.000102095015,0.00036806575,0.001047342,0.0068719415,0.010629273,0.5549625,0.18368825,0.23772351],"study_design_scores_gemma":[0.00017346925,0.000103331724,0.000355702,0.00036340067,0.00006264697,0.0006569414,0.00015815762,0.027355606,0.014455047,0.34159094,0.6146364,0.00008829904],"about_ca_topic_score_codex":0.0013665602,"about_ca_topic_score_gemma":0.0013293853,"teacher_disagreement_score":0.033631943,"about_ca_system_score_codex":0.00079506554,"about_ca_system_score_gemma":0.0016015322,"threshold_uncertainty_score":0.112510085},"labels":[],"label_agreement":null},{"id":"W2770368903","doi":"10.1007/s12652-017-0625-y","title":"Ontology-based framework for a multi-domain spoken dialogue system","year":2017,"lang":"en","type":"article","venue":"Journal of Ambient Intelligence and Humanized Computing","topic":"Speech and dialogue systems","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 de Moncton","funders":"","keywords":"Computer science; Computational intelligence; Ontology; Domain (mathematical analysis); Artificial intelligence; Natural language processing","score_opus":0.08914987816183365,"score_gpt":0.3361820808258902,"score_spread":0.24703220266405654,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770368903","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":[0.0042397254,0.00014612456,0.98884064,0.00031851133,0.000064515654,0.00018215453,0.00028704442,0.0029514441,0.0029697965],"genre_scores_gemma":[0.15848434,0.00037786327,0.8317093,0.00022204772,0.000057571262,0.00040539834,0.0014528213,0.00050108467,0.0067895567],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855715,0.00031447024,0.00023430836,0.00032127992,0.0004415569,0.00013132708],"domain_scores_gemma":[0.99934465,0.00014457192,0.0000453277,0.00012912478,0.00021898664,0.00011743228],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020342448,0.00054991327,0.0010186475,0.001358238,0.0015597949,0.0040022675,0.0021727392,0.0017728109,0.0045687133],"category_scores_gemma":[0.001987795,0.00055120105,0.0017460771,0.0009870778,0.0010956889,0.0035116684,0.003920834,0.0020550615,0.0019551485],"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":[0.00040361803,0.00064822484,0.002401806,0.00079731084,0.0004042263,0.0022584514,0.004760254,0.059890345,0.06638476,0.5785939,0.017498108,0.265959],"study_design_scores_gemma":[0.00007971771,0.00012541332,0.0008791864,0.00019750373,0.00034343087,0.0007725614,0.0011693895,0.6784778,0.02328103,0.14070787,0.15379672,0.00016949305],"about_ca_topic_score_codex":0.01633235,"about_ca_topic_score_gemma":0.01711048,"teacher_disagreement_score":0.01633235,"about_ca_system_score_codex":0.001350785,"about_ca_system_score_gemma":0.0041790656,"threshold_uncertainty_score":0.032474577},"labels":[],"label_agreement":null},{"id":"W2770385877","doi":"","title":"Investigating the structure of semantic memory.","year":2006,"lang":"en","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Speech and dialogue systems","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":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Ontario Innovation Trust","keywords":"Computer science; Natural language processing; Artificial intelligence; Linguistics; Philosophy","score_opus":0.013047899007771367,"score_gpt":0.1958338090095412,"score_spread":0.18278591000176983,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2770385877","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":[0.77251667,0.00968781,0.070635416,0.009152735,0.00042396632,0.00036095502,0.0025807652,0.0005309851,0.13411066],"genre_scores_gemma":[0.9774575,0.0012641803,0.011841799,0.0004962272,0.00011969537,0.00017959188,0.0017148106,0.00013196397,0.0067941938],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994106,0.0001979178,0.000047188463,0.00017982099,0.00008123158,0.000083256884],"domain_scores_gemma":[0.99213773,0.0042609777,0.0009610649,0.0013127972,0.00094898994,0.00037840861],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017351527,0.000342576,0.00043967506,0.001214125,0.0010363932,0.004532961,0.0015446638,0.0013832254,0.011240718],"category_scores_gemma":[0.014597873,0.0005589571,0.0004382237,0.0012382009,0.0024687273,0.014781962,0.0019643444,0.0018652455,0.0015198556],"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":[0.004447996,0.00076283957,0.059469745,0.0021652428,0.0004510009,0.0019302289,0.017236525,0.0030869748,0.097421184,0.4608146,0.011761783,0.34045187],"study_design_scores_gemma":[0.00030693022,0.00081878115,0.07160338,0.0005147489,0.00036759514,0.0017641959,0.006331466,0.01281441,0.025254387,0.852226,0.0278754,0.0001227848],"about_ca_topic_score_codex":0.002871018,"about_ca_topic_score_gemma":0.0040082997,"teacher_disagreement_score":0.011240718,"about_ca_system_score_codex":0.001471212,"about_ca_system_score_gemma":0.0017599603,"threshold_uncertainty_score":0.037603974},"labels":[],"label_agreement":null},{"id":"W2771539094","doi":"10.1504/ijil.2018.10009632","title":"Modelling second language learners for learning task recommendation","year":2017,"lang":"en","type":"article","venue":"International Journal of Innovation and Learning","topic":"Speech and dialogue systems","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":"Douglas College","funders":"","keywords":"Computer science; Task (project management); Knowledge management; Natural language processing","score_opus":0.034386843026981584,"score_gpt":0.31386763256772043,"score_spread":0.27948078954073885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2771539094","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4851673,0.00090820604,0.50863296,0.00086636917,0.000044051343,0.0002624041,0.00042103956,0.0004009259,0.0032967252],"genre_scores_gemma":[0.91727185,0.00034797133,0.07843806,0.000073786854,0.00003474585,0.00019933759,0.00034156803,0.00003750965,0.0032551382],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99898297,0.00051356846,0.00005305365,0.00022159175,0.00012203171,0.00010677019],"domain_scores_gemma":[0.9941554,0.0044299527,0.00045807677,0.00022630373,0.00044361778,0.00028660614],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024696917,0.0007219267,0.0007790215,0.001215187,0.00046643507,0.0018088889,0.0011610333,0.0013287258,0.0020296683],"category_scores_gemma":[0.009931719,0.0003985473,0.00073102495,0.0009166897,0.00040454604,0.0021282174,0.00076283887,0.0012997834,0.0008093999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012599822,0.0012541864,0.1248258,0.00050151267,0.00044958945,0.00081300933,0.006794353,0.5517687,0.0150216585,0.022563754,0.00416328,0.27058426],"study_design_scores_gemma":[0.000026241545,0.00010092738,0.003128004,0.000014355038,0.000032464734,0.000092182796,0.00024295828,0.9911111,0.0008137761,0.0034871637,0.00092736684,0.000023429811],"about_ca_topic_score_codex":0.01461328,"about_ca_topic_score_gemma":0.023899822,"teacher_disagreement_score":0.01461328,"about_ca_system_score_codex":0.00094368716,"about_ca_system_score_gemma":0.0010726475,"threshold_uncertainty_score":0.02905643},"labels":[],"label_agreement":null},{"id":"W2774661387","doi":"10.48550/arxiv.1711.11017","title":"HoME: a Household Multimodal Environment","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":80,"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; Université de Sherbrooke","funders":"","keywords":"Business; Environmental planning; Natural resource economics; Geography; Economics","score_opus":0.08439246256064796,"score_gpt":0.17498129082322902,"score_spread":0.09058882826258106,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2774661387","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":[0.15980327,0.002417196,0.4087138,0.0033758378,0.0009638871,0.0018405541,0.17970361,0.15426226,0.08891959],"genre_scores_gemma":[0.4401653,0.0010012747,0.34005505,0.0014995432,0.00019531329,0.0022236037,0.17478968,0.0035051424,0.036565024],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996315,0.00013526443,0.000015603122,0.00009043103,0.00005853965,0.00006860799],"domain_scores_gemma":[0.9997595,0.00006478045,0.0000108913255,0.00006352215,0.00003224206,0.000069038244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038541216,0.0009694873,0.00048801085,0.00037780823,0.0006128425,0.00082263723,0.001194089,0.0009240646,0.023741737],"category_scores_gemma":[0.0011364975,0.00025348002,0.0005034399,0.00043983813,0.00035592812,0.0017063958,0.0027954837,0.0009130586,0.00749233],"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":[0.0017664403,0.0006106646,0.006184949,0.001126183,0.00016145577,0.0015073674,0.0016539253,0.023792606,0.020575857,0.01766474,0.656785,0.2681708],"study_design_scores_gemma":[0.00032280743,0.0005443489,0.0072467905,0.00019176956,0.00007782323,0.00093906093,0.0015712938,0.12900738,0.015737718,0.02046523,0.823699,0.00019687579],"about_ca_topic_score_codex":0.006307355,"about_ca_topic_score_gemma":0.01743647,"teacher_disagreement_score":0.023741737,"about_ca_system_score_codex":0.0005291097,"about_ca_system_score_gemma":0.0005458736,"threshold_uncertainty_score":0.07942408},"labels":[],"label_agreement":null},{"id":"W2781323946","doi":"10.1109/i2ct.2017.8226104","title":"Cognitive support by language visualization: A case study with hindi language","year":2017,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 New Brunswick","funders":"","keywords":"Hindi; Computer science; Visualization; Comprehension; Natural language processing; Cognition; Reading comprehension; Artificial intelligence; Reading (process); Linguistics; Psychology; Programming language","score_opus":0.01662647904196198,"score_gpt":0.3222265537813919,"score_spread":0.30560007473942996,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2781323946","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":[0.98344153,0.0005017414,0.0051674256,0.0011071094,0.000036200665,0.0001783022,0.00019111017,0.00017940253,0.009197115],"genre_scores_gemma":[0.9795393,0.0006149728,0.01094684,0.00037877547,0.000029326595,0.00010827691,0.0001241678,0.00011933154,0.008139129],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.99853384,0.0009921974,0.000045851993,0.00010150595,0.00015659808,0.0001699582],"domain_scores_gemma":[0.99486464,0.0040405486,0.00022149208,0.00021682432,0.00020952357,0.00044684426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013382126,0.0009694725,0.0003867235,0.000938015,0.003071536,0.002335836,0.0014451204,0.0030127517,0.004539276],"category_scores_gemma":[0.0066493913,0.0003398552,0.00048986386,0.0010972824,0.002042679,0.0017208888,0.0016391979,0.0016494886,0.0008228198],"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":[0.0006202971,0.004269628,0.017947998,0.0014961221,0.00008064805,0.17405577,0.6641127,0.0034039728,0.01584826,0.0054218695,0.010372317,0.10237049],"study_design_scores_gemma":[0.00032562044,0.003567888,0.033607416,0.00057533005,0.00012957209,0.13482293,0.6450798,0.013731334,0.023767304,0.007968296,0.1361379,0.00028658658],"about_ca_topic_score_codex":0.004944252,"about_ca_topic_score_gemma":0.014164634,"teacher_disagreement_score":0.004944252,"about_ca_system_score_codex":0.0012803278,"about_ca_system_score_gemma":0.00064865727,"threshold_uncertainty_score":0.015185416},"labels":[],"label_agreement":null},{"id":"W2782779765","doi":"","title":"Using IBM watson cloud services to build natural language processing solutions to leverage chat tools","year":2017,"lang":"en","type":"article","venue":"Computer Science and Software Engineering","topic":"Speech and dialogue systems","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":"IBM (Canada)","funders":"","keywords":"IBM; Watson; Computer science; Leverage (statistics); Cloud computing; World Wide Web; Cognitive computing; Multimedia; Data science; Artificial intelligence; Cognition; Operating system","score_opus":0.026872679216647006,"score_gpt":0.26504747164291903,"score_spread":0.23817479242627201,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782779765","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":[0.06511587,0.0006013223,0.8601909,0.00674561,0.00046410033,0.0007152005,0.0004016168,0.032631427,0.03313387],"genre_scores_gemma":[0.1612732,0.00069437816,0.8172165,0.0008898782,0.00017662902,0.0003104689,0.00090560544,0.0031332215,0.015400119],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99790835,0.00053285324,0.00016236653,0.00039010952,0.0007749443,0.00023143583],"domain_scores_gemma":[0.9965012,0.0010714208,0.000183903,0.0007536069,0.0010787499,0.00041108707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003072887,0.001101492,0.00038945215,0.0012138878,0.0016107728,0.0032900886,0.0017994692,0.0010057986,0.0045641786],"category_scores_gemma":[0.0056660892,0.000521832,0.00085169665,0.0012670326,0.001356688,0.005193035,0.002223645,0.0025832104,0.0028154321],"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":[0.00063807477,0.00054617366,0.006439428,0.0007161476,0.00013966512,0.0031695883,0.015007689,0.014456299,0.12325592,0.13560231,0.079676434,0.62035227],"study_design_scores_gemma":[0.00016924842,0.00032029065,0.0036814336,0.00033105392,0.00014611779,0.0015668572,0.005584165,0.2036803,0.09012382,0.09147416,0.60265094,0.00027168303],"about_ca_topic_score_codex":0.014456668,"about_ca_topic_score_gemma":0.015618651,"teacher_disagreement_score":0.014456668,"about_ca_system_score_codex":0.0015234402,"about_ca_system_score_gemma":0.003382235,"threshold_uncertainty_score":0.028744996},"labels":[],"label_agreement":null},{"id":"W2790657516","doi":"10.1111/cogs.12582","title":"Modeling Reference Production as the Probabilistic Combination of Multiple Perspectives","year":2018,"lang":"en","type":"article","venue":"Cognitive Science","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":22,"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; Cancer Care Ontario","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Perspective (graphical); Probabilistic logic; Computer science; Object (grammar); Context (archaeology); Production (economics); Function (biology); Psychology; Language production; Expression (computer science); Cognitive psychology; Natural language processing; Cognitive science; Artificial intelligence; Cognition","score_opus":0.04739336178546983,"score_gpt":0.29402771568778535,"score_spread":0.24663435390231553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2790657516","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19799583,0.0002715929,0.7781076,0.0010724338,0.000056908502,0.00014813883,0.00030213574,0.0006702286,0.021375205],"genre_scores_gemma":[0.9276505,0.00022048855,0.06580573,0.00007977794,0.000043113054,0.00018471222,0.00017912127,0.00012060376,0.0057160477],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984906,0.00067876565,0.000068443216,0.0003950413,0.0002390562,0.00012811458],"domain_scores_gemma":[0.9948264,0.0032923562,0.00075687614,0.00041404393,0.00049639517,0.00021387963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029600032,0.00070009974,0.0004727321,0.00096267834,0.00053517905,0.0024727536,0.0013667574,0.0014371817,0.005419094],"category_scores_gemma":[0.01089787,0.000982495,0.0012161331,0.00076204294,0.0012492934,0.003059621,0.0015515412,0.001006496,0.0010668448],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008010419,0.00023982856,0.026316617,0.00034040902,0.00026602662,0.0030652462,0.008239447,0.5397181,0.04048752,0.29448026,0.002238087,0.08380742],"study_design_scores_gemma":[0.00006850823,0.00012428826,0.0035638725,0.000026519241,0.00009580303,0.00045205944,0.00033467988,0.9370648,0.0017293096,0.054865584,0.0016034498,0.00007115282],"about_ca_topic_score_codex":0.005410368,"about_ca_topic_score_gemma":0.0046165744,"teacher_disagreement_score":0.005419094,"about_ca_system_score_codex":0.0009774449,"about_ca_system_score_gemma":0.00090669526,"threshold_uncertainty_score":0.018128693},"labels":[],"label_agreement":null},{"id":"W2791604299","doi":"10.3389/fpsyg.2018.00176","title":"Referential Choices in a Collaborative Storytelling Task: Discourse Stages and Referential Complexity Matter","year":2018,"lang":"en","type":"article","venue":"Frontiers in Psychology","topic":"Speech and dialogue systems","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 Laval","funders":"Social Sciences and Humanities Research Council of Canada; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Referent; Ambiguity; Narrative; Psychology; Linguistics; Expression (computer science); Focus (optics); Storytelling; Character (mathematics); Task (project management); Pronoun; Discourse marker; Variation (astronomy); Cognitive psychology; Computer science; Mathematics","score_opus":0.02668246885587954,"score_gpt":0.3218669820278965,"score_spread":0.29518451317201694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2791604299","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":[0.99777657,0.00004382713,0.0012775776,0.0000154479,0.0000037179625,0.00006392398,0.000031087457,0.000013566348,0.00077436445],"genre_scores_gemma":[0.9947155,0.00004818908,0.004342265,0.00002653352,0.000008974432,0.0001882974,0.000106658365,0.000025861564,0.0005376726],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99484915,0.0020307822,0.0005411911,0.0014349226,0.00090564013,0.00023838072],"domain_scores_gemma":[0.9511041,0.037189797,0.0070367535,0.002258402,0.0009796845,0.0014311795],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038699256,0.00076406373,0.0008067714,0.00065521005,0.0006778806,0.00357102,0.0011811559,0.0013807656,0.0021754755],"category_scores_gemma":[0.04993158,0.00085948186,0.0003684472,0.00050361775,0.0012591586,0.003239164,0.0022296559,0.0009958721,0.00031705567],"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":[0.012681682,0.0040092967,0.104520425,0.0016666139,0.0004971949,0.0007313372,0.14338493,0.0033978338,0.6293084,0.002364079,0.00041539202,0.09702278],"study_design_scores_gemma":[0.0014003564,0.007678137,0.86086214,0.00025318362,0.0006345471,0.00092644285,0.019104624,0.025317017,0.07278692,0.0062394934,0.0042186566,0.00057846133],"about_ca_topic_score_codex":0.0013146119,"about_ca_topic_score_gemma":0.0014743275,"teacher_disagreement_score":0.0038699256,"about_ca_system_score_codex":0.0004916525,"about_ca_system_score_gemma":0.00044822905,"threshold_uncertainty_score":0.020466328},"labels":[],"label_agreement":null},{"id":"W2795497578","doi":"10.1145/3173574.3173930","title":"Designing Pronunciation Learning Tools","year":2018,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"Computer science; Pronunciation; Heuristics; Context (archaeology); Task (project management); Multimedia; Process (computing); Human–computer interaction; Natural language processing; Artificial intelligence; Linguistics; Programming language","score_opus":0.03275707711397405,"score_gpt":0.2453917804156261,"score_spread":0.21263470330165204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795497578","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":[0.08544393,0.0005280848,0.9043924,0.00020034397,0.000080408165,0.0008778503,0.000107048494,0.0061721,0.0021977655],"genre_scores_gemma":[0.19218417,0.00023483433,0.8050268,0.000063438936,0.000019560655,0.0006483526,0.00018392375,0.00049254735,0.0011462995],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99503124,0.0021596842,0.0006328905,0.0010194452,0.00083916524,0.00031751295],"domain_scores_gemma":[0.9802208,0.015241135,0.00079638377,0.0010673448,0.002124314,0.00055005087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077617294,0.0017940702,0.0008704449,0.001703847,0.0006038435,0.005184322,0.0039516967,0.0021356947,0.0030875863],"category_scores_gemma":[0.031612907,0.0008471128,0.00056658726,0.00070888596,0.0012914385,0.006285671,0.0027009593,0.001233274,0.0015158296],"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":[0.00061204756,0.00075814745,0.012728423,0.003544522,0.00018341755,0.0021375243,0.014862271,0.036669258,0.1443544,0.016328642,0.0031742423,0.7646471],"study_design_scores_gemma":[0.000803527,0.0037222258,0.014876695,0.0012613153,0.00053607253,0.0072617857,0.013531942,0.45455712,0.33561668,0.038512297,0.12865697,0.0006633218],"about_ca_topic_score_codex":0.0004394618,"about_ca_topic_score_gemma":0.0004365395,"teacher_disagreement_score":0.0077617294,"about_ca_system_score_codex":0.0005686228,"about_ca_system_score_gemma":0.0012135035,"threshold_uncertainty_score":0.041048467},"labels":[],"label_agreement":null},{"id":"W2795880093","doi":"10.1145/3170427.3170660","title":"Speech and Hands-free Interaction","year":2018,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Toronto","funders":"","keywords":"Computer science; Modalities; Natural language; Usability; Human–computer interaction; Speech community; Natural (archaeology); Modality (human–computer interaction); Artificial intelligence; Linguistics","score_opus":0.017566912053613985,"score_gpt":0.25179052913325717,"score_spread":0.23422361707964318,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795880093","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":[0.047134846,0.12790449,0.22070165,0.02037186,0.0041383067,0.00013447837,0.00060311344,0.0026800262,0.5763312],"genre_scores_gemma":[0.765733,0.03157767,0.02842317,0.0052886284,0.0030095426,0.00023396123,0.0004205635,0.0003632499,0.16495018],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99819106,0.00060950225,0.00008684226,0.00042445166,0.0005454744,0.00014270729],"domain_scores_gemma":[0.99796224,0.0014254864,0.00011404934,0.0001730815,0.00019017697,0.00013487882],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008990925,0.0006705496,0.00046681112,0.0009121521,0.00075360236,0.004012503,0.0006743164,0.0027292909,0.023089882],"category_scores_gemma":[0.0043438626,0.00026233433,0.00035610134,0.00048088268,0.0041309027,0.0032101292,0.0026975307,0.0011870482,0.0059576454],"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":[0.00040927122,0.000099633464,0.0016701538,0.0015764575,0.00010435207,0.0013048126,0.006163161,0.0058177267,0.016115168,0.42281643,0.03826094,0.50566196],"study_design_scores_gemma":[0.000091704955,0.00035532314,0.012361894,0.0013210092,0.00009762593,0.00460344,0.0025900984,0.0119206915,0.005204118,0.6353636,0.32587007,0.00022050252],"about_ca_topic_score_codex":0.001795891,"about_ca_topic_score_gemma":0.00093765627,"teacher_disagreement_score":0.023089882,"about_ca_system_score_codex":0.000814964,"about_ca_system_score_gemma":0.00050774764,"threshold_uncertainty_score":0.07724339},"labels":[],"label_agreement":null},{"id":"W2805480372","doi":"10.63317/3tat2guzqfur","title":"A New Annotated Portuguese/Spanish Corpus for the Multi-Sentence Compression Task","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Polytechnique Montréal","funders":"","keywords":"Computer science; Portuguese; Natural language processing; Sentence; Task (project management); Artificial intelligence; Compression (physics); Speech recognition; Linguistics; Engineering","score_opus":0.05372594388695155,"score_gpt":0.2942539148323845,"score_spread":0.24052797094543293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2805480372","genre_codex":"dataset","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":[0.246253,0.0070118816,0.092341416,0.0026844204,0.004476388,0.0024650053,0.52527344,0.014130572,0.1053639],"genre_scores_gemma":[0.14648011,0.0017142015,0.09534812,0.0006011113,0.0009585959,0.0027447396,0.7165045,0.0052782823,0.030370232],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998428,0.0004176004,0.00017296587,0.0004502935,0.00039314645,0.00013812563],"domain_scores_gemma":[0.9954823,0.0009787639,0.00015686124,0.0006953049,0.0023971908,0.00028952796],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019049349,0.0022207892,0.0013419356,0.004035085,0.0017226762,0.00153739,0.001411717,0.0014208651,0.03168593],"category_scores_gemma":[0.005591171,0.0005049259,0.0005735234,0.0033513855,0.00070641097,0.0011808522,0.002079469,0.001512854,0.013581339],"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":[0.0018110726,0.0010815171,0.004595343,0.005577395,0.00019087983,0.0042066392,0.003074746,0.0034600066,0.124581814,0.005232033,0.464131,0.3820576],"study_design_scores_gemma":[0.00083916436,0.0003483091,0.048144683,0.0006381664,0.00034657549,0.003915583,0.002589932,0.010543498,0.039516833,0.0032316237,0.889663,0.00022280772],"about_ca_topic_score_codex":0.012438222,"about_ca_topic_score_gemma":0.015916016,"teacher_disagreement_score":0.03168593,"about_ca_system_score_codex":0.0007094297,"about_ca_system_score_gemma":0.0028409613,"threshold_uncertainty_score":0.10599995},"labels":[],"label_agreement":null},{"id":"W2806434414","doi":"10.22215/etd/2013-10030","title":"Distributed Multimodal Interaction Protocol: Enabling Transport of Distributed Interactions","year":2013,"lang":"en","type":"dissertation","venue":"","topic":"Speech and dialogue systems","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":"Protocol (science); Software; Computer science; Variety (cybernetics); Mobile device; Embedded system; Software engineering; Human–computer interaction; World Wide Web; Operating system","score_opus":0.019738414749953137,"score_gpt":0.3015900351702936,"score_spread":0.28185162042034045,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2806434414","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":[0.021632483,0.00050993165,0.9387429,0.0005682113,0.000568136,0.0025948617,0.0006111889,0.010036133,0.024736097],"genre_scores_gemma":[0.3715109,0.001846493,0.54204214,0.0010367295,0.00042683058,0.009842438,0.0048197093,0.0024587868,0.066016026],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99530315,0.0011913266,0.00063942454,0.00036273224,0.0021410736,0.00036240427],"domain_scores_gemma":[0.99571,0.00095924974,0.00032057354,0.00091430265,0.0018641067,0.00023163976],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005288927,0.0008027347,0.00051924866,0.0011650604,0.0013101664,0.003023619,0.0018194494,0.0015060396,0.0044281655],"category_scores_gemma":[0.008729026,0.0005421834,0.00045940134,0.00076855,0.0013075399,0.003299804,0.0032142345,0.0026801252,0.0027664378],"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":[0.0013184528,0.0009278933,0.0034897195,0.0014619719,0.00018782227,0.002302569,0.004165474,0.010300636,0.16290008,0.34574404,0.083209306,0.38399205],"study_design_scores_gemma":[0.00045461333,0.0010932076,0.002849186,0.00052355544,0.00023986156,0.0025850853,0.00078920013,0.11843423,0.21099956,0.039450414,0.62222046,0.00036065842],"about_ca_topic_score_codex":0.002066053,"about_ca_topic_score_gemma":0.0019698003,"teacher_disagreement_score":0.005288927,"about_ca_system_score_codex":0.0012725972,"about_ca_system_score_gemma":0.0027109461,"threshold_uncertainty_score":0.02797085},"labels":[],"label_agreement":null},{"id":"W2808007596","doi":"10.65109/miek6215","title":"Training Dialogue Systems With Human Advice","year":2018,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Microsoft (Canada)","funders":"Horizon 2020 Framework Programme; European Commission","keywords":"Reinforcement learning; Computer science; Perspective (graphical); Bridge (graph theory); Encoding (memory); Point (geometry); Reinforcement; Artificial intelligence; Advice (programming); Human–computer interaction; Engineering","score_opus":0.053336867514931184,"score_gpt":0.2733405274845878,"score_spread":0.22000365996965662,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2808007596","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0916096,0.00041507286,0.8949174,0.0002753998,0.00009874385,0.00015260266,0.0000450792,0.007847193,0.0046388507],"genre_scores_gemma":[0.7603661,0.00013698013,0.23542903,0.00019158376,0.000045246616,0.00019509168,0.000118835844,0.00022721213,0.0032899962],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99845576,0.0007191705,0.00007391683,0.00039028868,0.00025910613,0.000101719335],"domain_scores_gemma":[0.99499136,0.0038827113,0.00017842076,0.00045128335,0.00032416402,0.00017207391],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001959424,0.0008619681,0.0008723102,0.00030545954,0.0003339572,0.00083522004,0.0010946447,0.0011651131,0.0035803297],"category_scores_gemma":[0.010212437,0.00049405714,0.0002825508,0.00017166858,0.00059591146,0.0012154451,0.0013725321,0.0017421484,0.0011746488],"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":[0.00080182526,0.0007693662,0.0017569475,0.00042844514,0.000090441026,0.00023137814,0.0010040305,0.41703355,0.036742304,0.0065768203,0.0042192945,0.5303456],"study_design_scores_gemma":[0.00007797276,0.00013753348,0.00020655655,0.000015302949,0.000013858275,0.000035546098,0.000041317497,0.9869071,0.007588747,0.0028865822,0.0020767304,0.0000127243475],"about_ca_topic_score_codex":0.0017400343,"about_ca_topic_score_gemma":0.0017589469,"teacher_disagreement_score":0.0035803297,"about_ca_system_score_codex":0.00044598593,"about_ca_system_score_gemma":0.00078658474,"threshold_uncertainty_score":0.011977375},"labels":[],"label_agreement":null},{"id":"W2809215328","doi":"10.1109/compsac.2018.00113","title":"Long Short-Term Memory Neural Networks for Artificial Dialogue Generation","year":2018,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 de Moncton","funders":"","keywords":"Computer science; Hidden Markov model; Encoder; Artificial neural network; Artificial intelligence; Sequence (biology); Recurrent neural network; Term (time); Decoding methods; Long short term memory; Architecture; Speech recognition; Natural language processing; Algorithm","score_opus":0.05047732032030343,"score_gpt":0.27423334571095737,"score_spread":0.22375602539065392,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809215328","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049809597,0.002742836,0.94029367,0.00048897834,0.00018107769,0.000106431195,0.00032599908,0.0026247988,0.0034266918],"genre_scores_gemma":[0.7002001,0.001036768,0.29268378,0.00022041543,0.00007686599,0.00031715946,0.00072968734,0.00017247313,0.0045627495],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995347,0.0002198826,0.00003074292,0.00010523143,0.00007191266,0.000037442456],"domain_scores_gemma":[0.9985813,0.0010588525,0.000062730236,0.00008854467,0.00018221197,0.000026350124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001400711,0.0007009252,0.00043755854,0.00042050125,0.0003055755,0.00076311885,0.00087232725,0.0009231441,0.002573283],"category_scores_gemma":[0.0040612384,0.0003343659,0.00041403735,0.00060043024,0.00039209466,0.0013772997,0.00051984173,0.0014483698,0.00064382947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0002440027,0.00013647933,0.00094465865,0.0003125667,0.00012196453,0.00016186068,0.00023678665,0.6671262,0.012142104,0.010312819,0.0023648469,0.30589572],"study_design_scores_gemma":[0.000004589494,0.00002807572,0.00014051079,0.0000118307,0.000008775486,0.000012902895,0.000010474105,0.9943282,0.0017574506,0.0031088567,0.00058202824,0.0000063855327],"about_ca_topic_score_codex":0.0067918585,"about_ca_topic_score_gemma":0.009113762,"teacher_disagreement_score":0.0067918585,"about_ca_system_score_codex":0.0009703084,"about_ca_system_score_gemma":0.0006189092,"threshold_uncertainty_score":0.013504624},"labels":[],"label_agreement":null},{"id":"W2809981936","doi":"10.3758/s13423-018-1501-2","title":"Using experiential optimization to build lexical representations","year":2018,"lang":"en","type":"review","venue":"Psychonomic Bulletin & Review","topic":"Speech and dialogue systems","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":"Queen's University","funders":"Institute of Education Sciences","keywords":"Experiential learning; Representation (politics); Benchmark (surveying); Task (project management); Psychology; Cognitive psychology; Cognition; Natural language processing; Artificial intelligence; External Data Representation; Machine learning; Cognitive science; Computer science; Mathematics education","score_opus":0.11459426148815886,"score_gpt":0.4075506724924571,"score_spread":0.2929564110042982,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2809981936","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":[0.034879196,0.20608336,0.7187009,0.003391362,0.0013161098,0.0004438942,0.001842831,0.0035215819,0.029820772],"genre_scores_gemma":[0.2823415,0.16896188,0.5191799,0.0011209204,0.0006899853,0.00058715895,0.007159586,0.0008877639,0.019071411],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99943835,0.00017604568,0.00007439826,0.00013665325,0.00014096138,0.000033606375],"domain_scores_gemma":[0.9987909,0.00079578575,0.000059978986,0.00014289426,0.00018551611,0.000024858547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011095871,0.0011149867,0.00081340346,0.0015670573,0.00024919523,0.0021852914,0.0015394966,0.0006106348,0.009273751],"category_scores_gemma":[0.004636031,0.0003091428,0.00082302134,0.0018625337,0.0007241185,0.0030675728,0.0014839458,0.0012156647,0.0034637775],"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":[0.000056788394,0.000057046447,0.00054583367,0.0014053427,0.00013086187,0.00006357046,0.0001079228,0.0026907097,0.0028660214,0.012746944,0.0039405436,0.97538835],"study_design_scores_gemma":[0.0003463035,0.0007848962,0.012658959,0.0043969415,0.0012467651,0.002248659,0.001562143,0.13270897,0.029571278,0.29872683,0.515409,0.00033925593],"about_ca_topic_score_codex":0.0017014302,"about_ca_topic_score_gemma":0.0021332654,"teacher_disagreement_score":0.009273751,"about_ca_system_score_codex":0.0004492469,"about_ca_system_score_gemma":0.0012941504,"threshold_uncertainty_score":0.03102374},"labels":[],"label_agreement":null},{"id":"W2810821963","doi":"10.5087/dad.2018.101","title":"A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version","year":2018,"lang":"en","type":"article","venue":"Dialogue & Discourse","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":148,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal; McGill University; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Samsung; Compute Canada; Samsung Advanced Institute of Technology; Canadian Institute for Advanced Research","keywords":"Computer science; Data science; Artificial intelligence; Transfer of learning; Data-driven; Machine learning","score_opus":0.0922818192006133,"score_gpt":0.31227047407818315,"score_spread":0.21998865487756986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2810821963","genre_codex":"dataset","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":[0.027428767,0.0972506,0.35259995,0.0093567325,0.0051573403,0.0026494383,0.39700708,0.030430652,0.07811948],"genre_scores_gemma":[0.040811338,0.026079722,0.3749047,0.0014956318,0.00091678725,0.003671796,0.53496164,0.007889258,0.00926917],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9837266,0.0061429306,0.0028860078,0.0024456596,0.004495636,0.00030313394],"domain_scores_gemma":[0.9107084,0.054251827,0.0025617129,0.01602809,0.014969531,0.0014804143],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019048471,0.0016005185,0.0018115704,0.013314576,0.002428056,0.0054785446,0.0047375513,0.0023235295,0.022513304],"category_scores_gemma":[0.07938923,0.0017669037,0.0012527639,0.020189002,0.0020876692,0.008500996,0.004769988,0.0031532731,0.019471241],"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":[0.00034369677,0.0003408582,0.005636648,0.01343121,0.00017856824,0.00024919127,0.0014802443,0.004159671,0.005432594,0.018907623,0.28477,0.6650697],"study_design_scores_gemma":[0.000059316317,0.00010531777,0.008137676,0.0033536537,0.0000783337,0.0004989677,0.000664529,0.0047855484,0.008292857,0.010690205,0.963172,0.00016152351],"about_ca_topic_score_codex":0.0043368624,"about_ca_topic_score_gemma":0.0069821696,"teacher_disagreement_score":0.022513304,"about_ca_system_score_codex":0.0021738114,"about_ca_system_score_gemma":0.0056986483,"threshold_uncertainty_score":0.10073912},"labels":[],"label_agreement":null},{"id":"W2886595524","doi":"10.1145/3233756.3233951","title":"A Localization Theory","year":2018,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Sample (material); Perception; Computer science; Quality (philosophy); Empirical research; Survey research; Psychology; Survey sampling; Applied psychology; Statistics; Sociology; Mathematics; Demography","score_opus":0.010947468553510446,"score_gpt":0.2302649607725081,"score_spread":0.21931749221899766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2886595524","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01330788,0.0039295107,0.51905596,0.0145275025,0.0005129414,0.00009192184,0.0005022873,0.00037854983,0.44769344],"genre_scores_gemma":[0.76064557,0.0063189603,0.1110332,0.0053384686,0.0014986056,0.00040251575,0.0008293998,0.00038766934,0.11354564],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9978764,0.0006983357,0.00009969754,0.0005805326,0.00043487662,0.0003101436],"domain_scores_gemma":[0.9952447,0.0025846544,0.0002545873,0.00075587956,0.00094016915,0.0002200829],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025171104,0.00075962243,0.0007062353,0.002816229,0.0031816622,0.004392645,0.0022021218,0.002651073,0.03169838],"category_scores_gemma":[0.007674578,0.00047831028,0.00150441,0.002317159,0.009723442,0.012766818,0.0038395973,0.0024818187,0.007123624],"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":[0.0000051994134,0.000006262718,0.00023256677,0.000028785847,0.0000044433004,0.00003091795,0.000274097,0.00043672108,0.000057492824,0.98921424,0.0025116806,0.0071976534],"study_design_scores_gemma":[0.000012872227,0.00001968787,0.00033116486,0.000058882368,0.000009888349,0.00022601818,0.00038203876,0.002780827,0.000091134294,0.95323944,0.042836316,0.000011732799],"about_ca_topic_score_codex":0.00820596,"about_ca_topic_score_gemma":0.0030352413,"teacher_disagreement_score":0.03169838,"about_ca_system_score_codex":0.0032529628,"about_ca_system_score_gemma":0.0021052484,"threshold_uncertainty_score":0.10604161},"labels":[],"label_agreement":null},{"id":"W2888854509","doi":"10.1007/978-3-319-99972-2_2","title":"Metis: A Scalable Natural-Language-Based Intelligent Personal Assistant for Maritime Services","year":2018,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Speech and dialogue systems","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":"Computer science; Scalability; Natural language; Parsing; Task (project management); Domain (mathematical analysis); Field (mathematics); Question answering; Artificial intelligence; Natural language processing; Information retrieval; Database","score_opus":0.024888619594436653,"score_gpt":0.2822263595750337,"score_spread":0.25733773998059706,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2888854509","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06239842,0.0019653225,0.6125627,0.00058525655,0.0006538629,0.0006547106,0.0076613277,0.26343504,0.0500834],"genre_scores_gemma":[0.30082694,0.0010014245,0.56581223,0.00091190566,0.00021620032,0.00072383316,0.022694236,0.003750394,0.10406281],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997495,0.000025480711,0.000011920323,0.000074603195,0.000105162326,0.000033432458],"domain_scores_gemma":[0.9998741,0.000030061454,0.00000876501,0.000022093307,0.000040964518,0.000023839219],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022277377,0.00094605115,0.00078385917,0.0003823577,0.0004990042,0.00087882124,0.0017933949,0.0005801078,0.014282592],"category_scores_gemma":[0.00049039884,0.0002856045,0.00039319025,0.00040002263,0.0002254243,0.0014045374,0.0014382072,0.0008351336,0.0096310135],"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":[0.0017949981,0.00039948706,0.00097635906,0.00062348286,0.000106383835,0.00073590456,0.00045969672,0.006932666,0.12814792,0.00751241,0.23902553,0.6132852],"study_design_scores_gemma":[0.00039981707,0.0006847005,0.0026901134,0.00009362473,0.00017802419,0.0016144868,0.0007576718,0.39972782,0.1411262,0.010306665,0.4422752,0.00014569206],"about_ca_topic_score_codex":0.004093165,"about_ca_topic_score_gemma":0.007464122,"teacher_disagreement_score":0.014282592,"about_ca_system_score_codex":0.00041296106,"about_ca_system_score_gemma":0.0007829376,"threshold_uncertainty_score":0.047779977},"labels":[],"label_agreement":null},{"id":"W2894060764","doi":"10.1145/3258675","title":"Session details: Session 2D: Conversational Systems","year":2018,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Montréal","funders":"","keywords":"Session (web analytics); Computer science; Multimedia; World Wide Web","score_opus":0.023983428864093385,"score_gpt":0.2578688380708324,"score_spread":0.233885409206739,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2894060764","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":[0.0066964417,0.0060362765,0.020928744,0.013835458,0.05915667,0.0027133715,0.029474227,0.010897343,0.85026133],"genre_scores_gemma":[0.031637486,0.0029816313,0.0038974683,0.0022941267,0.009803791,0.00120608,0.015823565,0.0025916526,0.9297641],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989912,0.00019631951,0.000052555893,0.00026396677,0.00027455218,0.00022151518],"domain_scores_gemma":[0.9961294,0.00084708375,0.000065977336,0.0005522463,0.000918421,0.0014868703],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002261298,0.0017378728,0.0021596013,0.0007561186,0.0029629415,0.0063728816,0.0013472365,0.004157906,0.8176546],"category_scores_gemma":[0.003889308,0.00040809528,0.0016712849,0.00085016666,0.00052011776,0.0026950764,0.0042038267,0.0029914293,0.62524927],"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":[0.0006071965,0.00019361218,0.00016486544,0.00042018923,0.000023986144,0.00006296215,0.00011058223,0.00009325235,0.0036798085,0.0010245914,0.9489004,0.04471849],"study_design_scores_gemma":[0.00014545204,0.00028826104,0.0011642086,0.00012968593,0.000025284093,0.0001013685,0.00012681376,0.00046520223,0.001680708,0.0015823394,0.99426466,0.000026039794],"about_ca_topic_score_codex":0.0013222679,"about_ca_topic_score_gemma":0.0026732932,"teacher_disagreement_score":0.18234539,"about_ca_system_score_codex":0.00088449847,"about_ca_system_score_gemma":0.0016569574,"threshold_uncertainty_score":0.2600935},"labels":[],"label_agreement":null},{"id":"W2897182429","doi":"10.1121/1.5067627","title":"Bilingual word familiarity in Cantonese and English","year":2018,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Vocabulary; Linguistics; Lexicon; American English; Context (archaeology); Computer science; Second language; Psychology; Word (group theory); Task (project management); Natural language processing; History","score_opus":0.011349085942174184,"score_gpt":0.24677533504423815,"score_spread":0.23542624910206397,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2897182429","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":[0.9943304,0.000098317905,0.000352995,0.000021549555,0.000009194941,0.000027785894,0.0000793504,0.000010767572,0.0050695175],"genre_scores_gemma":[0.99742836,0.00007770194,0.000642535,0.000039039587,0.00000889204,0.00007613316,0.00024352204,0.0000132273735,0.0014705916],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9990946,0.00024953063,0.000120914294,0.00023684326,0.00019503164,0.00010303353],"domain_scores_gemma":[0.9965412,0.0015589914,0.00049019716,0.00038236548,0.00058537914,0.00044179132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001591726,0.00048164284,0.00036220436,0.0005899334,0.00094044907,0.001214616,0.000231264,0.00032925847,0.008561499],"category_scores_gemma":[0.00575559,0.00027391853,0.00017743306,0.0003275837,0.0006390361,0.0011327076,0.0011429187,0.00025233897,0.0009323263],"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":[0.004800343,0.0009138068,0.33071488,0.00092826714,0.00012062001,0.0030059882,0.064305745,0.00042039758,0.4683582,0.0018131601,0.0026920848,0.121926524],"study_design_scores_gemma":[0.00011339434,0.001115222,0.9686821,0.000066161694,0.000048007132,0.0010568564,0.012932601,0.00071420305,0.011524757,0.00052605406,0.0031470326,0.000073527975],"about_ca_topic_score_codex":0.013070798,"about_ca_topic_score_gemma":0.03779434,"teacher_disagreement_score":0.013070798,"about_ca_system_score_codex":0.00036215325,"about_ca_system_score_gemma":0.00038056707,"threshold_uncertainty_score":0.028641045},"labels":[],"label_agreement":null},{"id":"W2902338434","doi":"","title":"Crowdsourcing the Pronunciation of Out-of-Vocabulary Words.","year":2017,"lang":"en","type":"article","venue":"National Conference on Artificial Intelligence","topic":"Speech and dialogue systems","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; University of Toronto","funders":"","keywords":"Crowdsourcing; Pronunciation; Computer science; Vocabulary; Natural language processing; Artificial intelligence; Speech recognition; Linguistics; World Wide Web","score_opus":0.17418239703140648,"score_gpt":0.35554039245367786,"score_spread":0.18135799542227138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2902338434","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":[0.5754707,0.0092219105,0.18374352,0.0057187756,0.0123028485,0.0012238316,0.10401953,0.010189736,0.098109186],"genre_scores_gemma":[0.87730426,0.0008714499,0.043900497,0.00086725486,0.0010676937,0.00043010127,0.050225645,0.0012384283,0.024094732],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99196327,0.0034074856,0.00036770935,0.0017261629,0.0021513607,0.00038389914],"domain_scores_gemma":[0.9851777,0.0070139626,0.00057060126,0.0024771434,0.0043328386,0.0004277168],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038877493,0.0012255698,0.0010260997,0.0029389749,0.0013853163,0.0022533552,0.0017029048,0.0016798674,0.005936171],"category_scores_gemma":[0.031877935,0.00030119816,0.0005470333,0.0032312956,0.00085040403,0.0020323028,0.0042852913,0.0014052377,0.009166851],"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":[0.0025691045,0.00034615534,0.027359402,0.0025326198,0.0006617178,0.0018313084,0.008707027,0.013854456,0.0633556,0.008266616,0.2252797,0.6452363],"study_design_scores_gemma":[0.00062039273,0.00057204673,0.09809135,0.0009068085,0.0004971891,0.0023977603,0.022802783,0.24278924,0.06706173,0.05409965,0.5095341,0.000626925],"about_ca_topic_score_codex":0.01688663,"about_ca_topic_score_gemma":0.024155693,"teacher_disagreement_score":0.01688663,"about_ca_system_score_codex":0.0008173372,"about_ca_system_score_gemma":0.0018024995,"threshold_uncertainty_score":0.033576667},"labels":[],"label_agreement":null},{"id":"W2907177214","doi":"10.4000/books.aaccademia.4661","title":"A Markovian Kernel-based Approach for itaLIan Speech acT labEliNg","year":2018,"lang":"en","type":"book-chapter","venue":"Accademia University Press eBooks","topic":"Speech and dialogue systems","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":false,"ca_institutions":"","funders":"National Research Council Canada; Università degli Studi di Napoli Federico II","keywords":"Utterance; Computer science; Task (project management); Artificial intelligence; Kernel (algebra); Context (archaeology); Support vector machine; Hidden Markov model; Natural language processing; Speech recognition; Markov process; Feature (linguistics); Linguistics; Mathematics; Engineering","score_opus":0.035385615284863815,"score_gpt":0.22317557775402205,"score_spread":0.18778996246915824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907177214","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0059125526,0.0002811824,0.98815095,0.00017139655,0.00006169952,0.000041706917,0.00011308198,0.0020535267,0.0032139448],"genre_scores_gemma":[0.35922605,0.00050111307,0.62169796,0.00015302817,0.000142654,0.00017177222,0.0011516663,0.00067822775,0.016277526],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.998814,0.00049276935,0.000053585358,0.00030063407,0.0002451054,0.00009384473],"domain_scores_gemma":[0.999094,0.0004036082,0.00006348907,0.00018007903,0.00021716107,0.000041772215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001139223,0.0005910773,0.0004979591,0.00072187674,0.00049583125,0.0012715716,0.0012322336,0.00081335305,0.004511463],"category_scores_gemma":[0.0030658846,0.00037051976,0.0006919681,0.00069213856,0.00050808385,0.0015853401,0.0011379957,0.0015306452,0.0029440876],"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":[0.0003487489,0.00021261154,0.0011788779,0.00026715393,0.00008887802,0.00018112622,0.0007558011,0.101534374,0.018623322,0.084374875,0.016410971,0.77602315],"study_design_scores_gemma":[0.000005036708,0.000036783174,0.0005114278,0.000013843544,0.000012011707,0.00009639687,0.000040662682,0.9682902,0.00446935,0.018939383,0.007564092,0.000020751282],"about_ca_topic_score_codex":0.003865032,"about_ca_topic_score_gemma":0.004582115,"teacher_disagreement_score":0.004511463,"about_ca_system_score_codex":0.00093220506,"about_ca_system_score_gemma":0.00092564186,"threshold_uncertainty_score":0.015092373},"labels":[],"label_agreement":null},{"id":"W2907819441","doi":"10.4000/books.aaccademia.4487","title":"Overview of the EVALITA 2018 Evaluation of Italian DIALogue systems (IDIAL) Task","year":2018,"lang":"en","type":"book-chapter","venue":"Accademia University Press eBooks","topic":"Speech and dialogue systems","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":"National Research Council Canada; Università degli Studi di Napoli Federico II","keywords":"Task (project management); Perspective (graphical); Computer science; Human–computer interaction; Protocol (science); Artificial intelligence; Engineering; Systems engineering","score_opus":0.10770469381953118,"score_gpt":0.27084457940236395,"score_spread":0.16313988558283277,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2907819441","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":[0.057867285,0.070031986,0.31138018,0.007825891,0.003021513,0.023761066,0.039996643,0.02458595,0.46152946],"genre_scores_gemma":[0.16658919,0.019422455,0.46103656,0.0034317307,0.0021873391,0.03327737,0.13608934,0.009415209,0.16855083],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9856188,0.0063065393,0.00095640874,0.0013083372,0.0051587964,0.00065101316],"domain_scores_gemma":[0.9914751,0.002402559,0.0004037929,0.00112356,0.0038524931,0.0007425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.019462172,0.0020398449,0.0015627444,0.0046553467,0.0016538862,0.005835234,0.0030863802,0.001800301,0.016079757],"category_scores_gemma":[0.011298019,0.0007524345,0.000931925,0.0028889587,0.0009815941,0.002613335,0.0046756202,0.002280375,0.016330114],"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":[0.00080847956,0.0013824365,0.0017886979,0.005510079,0.00013939702,0.00021284413,0.0034489436,0.0040879967,0.021898445,0.0093329875,0.27870697,0.6726827],"study_design_scores_gemma":[0.0002652667,0.001244836,0.008418882,0.0014938217,0.000090025846,0.00038287212,0.00088709366,0.0055443384,0.017007811,0.005678997,0.95882136,0.00016466103],"about_ca_topic_score_codex":0.005287613,"about_ca_topic_score_gemma":0.0066337846,"teacher_disagreement_score":0.019462172,"about_ca_system_score_codex":0.0031358865,"about_ca_system_score_gemma":0.00472749,"threshold_uncertainty_score":0.10292703},"labels":[],"label_agreement":null},{"id":"W2913646321","doi":"","title":"Proceedings of the 15th international conference on Intelligent user interfaces","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Rebuttal; Computer science; Transparency (behavior); Relevance (law); Presentation (obstetrics); User interface; World Wide Web; Political science","score_opus":0.02644669993015749,"score_gpt":0.2584280887113636,"score_spread":0.23198138878120608,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2913646321","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":[0.02783199,0.18385005,0.20494334,0.016245674,0.13357693,0.0028226036,0.005840915,0.014530268,0.4103582],"genre_scores_gemma":[0.12542471,0.08792486,0.11848591,0.007792512,0.02230183,0.0029045714,0.019572776,0.0028271002,0.61276585],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99611926,0.0012589796,0.0003966759,0.0005788451,0.0013758529,0.00027044443],"domain_scores_gemma":[0.9949244,0.0018658309,0.00017050172,0.00048780642,0.0021492834,0.0004021504],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037325907,0.0025106622,0.0024940157,0.0016842666,0.0008908304,0.0071504656,0.0019144653,0.0025659013,0.09863113],"category_scores_gemma":[0.009111769,0.00047435297,0.0011515789,0.0011197025,0.0011375156,0.0044476595,0.0026194882,0.0033016345,0.052481685],"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":[0.00034649784,0.0002018008,0.0010928465,0.001223678,0.00016105226,0.00030566196,0.0005707251,0.0004703225,0.005665843,0.0045158626,0.5707271,0.41471857],"study_design_scores_gemma":[0.00004862543,0.00025803465,0.0036082445,0.0008800072,0.00010824887,0.0005556862,0.00046970343,0.0073711444,0.0018109777,0.00521831,0.97960037,0.00007071869],"about_ca_topic_score_codex":0.0016867266,"about_ca_topic_score_gemma":0.0014671345,"teacher_disagreement_score":0.09863113,"about_ca_system_score_codex":0.00076250645,"about_ca_system_score_gemma":0.0013568043,"threshold_uncertainty_score":0.32995397},"labels":[],"label_agreement":null},{"id":"W2914429049","doi":"","title":"Conceptual combination: Models, theories, and controversies","year":2009,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Waterloo","funders":"","keywords":"Epistemology; Computer science; Philosophy","score_opus":0.013303342727204417,"score_gpt":0.2078729315952566,"score_spread":0.1945695888680522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2914429049","genre_codex":"commentary","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":[0.061194714,0.18174313,0.16107978,0.4128679,0.004011751,0.00026871805,0.0006806108,0.0004033832,0.17775],"genre_scores_gemma":[0.90991575,0.032949336,0.039598465,0.009740623,0.003312566,0.0004321909,0.00061366055,0.00027449228,0.0031628646],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.97021186,0.018351614,0.0014616065,0.0034475103,0.0051742285,0.0013532613],"domain_scores_gemma":[0.9259641,0.053142287,0.0039745457,0.008059643,0.006729378,0.0021299447],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03367344,0.0019939202,0.0037672871,0.0098962225,0.0070729214,0.022118818,0.010448853,0.009795205,0.016492693],"category_scores_gemma":[0.08788328,0.0019471565,0.002077305,0.010291481,0.044495616,0.059577532,0.011435862,0.010877058,0.002382049],"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":[0.00007839152,0.00004659481,0.00095174735,0.00044636606,0.00007989245,0.00010959293,0.0038659156,0.0005349348,0.000043723045,0.9653778,0.0044068214,0.024058279],"study_design_scores_gemma":[0.000034491262,0.000012154704,0.00041564883,0.00040828463,0.00003376967,0.0001632254,0.0033132015,0.0017685632,0.00007209701,0.984221,0.009533329,0.000024205248],"about_ca_topic_score_codex":0.006501737,"about_ca_topic_score_gemma":0.003714186,"teacher_disagreement_score":0.03367344,"about_ca_system_score_codex":0.011263147,"about_ca_system_score_gemma":0.0074870945,"threshold_uncertainty_score":0.17808425},"labels":[],"label_agreement":null},{"id":"W2918897245","doi":"10.1145/3308557.3308730","title":"A modular framework for collaborative multimodal annotation and visualization","year":2019,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Ontario Institute of Technology","funders":"","keywords":"Computer science; Annotation; Modular design; Software deployment; Pipeline (software); Visualization; World Wide Web; Artificial intelligence; Software engineering; Human–computer interaction; Data science; Programming language","score_opus":0.011899398052172576,"score_gpt":0.2754207207165744,"score_spread":0.26352132266440187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2918897245","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":[0.00041771505,0.00008026101,0.9833627,0.00022965566,0.000050121405,0.00018262121,0.0002459221,0.012640577,0.0027904427],"genre_scores_gemma":[0.023892231,0.00021474603,0.96572536,0.00023127007,0.000088018285,0.0007280974,0.0013659653,0.0022561592,0.0054982714],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9967349,0.0010234235,0.00026911887,0.00076874957,0.0009200052,0.00028371997],"domain_scores_gemma":[0.99676067,0.0008400135,0.00013148207,0.0011362175,0.0006370272,0.00049457396],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006377582,0.0016989788,0.001300644,0.0028628567,0.002593973,0.007929194,0.0058942246,0.0027649847,0.020285286],"category_scores_gemma":[0.008241802,0.0015394819,0.0028181148,0.0018989334,0.0026431056,0.007083116,0.010838025,0.00410516,0.010332666],"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":[0.00057957566,0.00033761226,0.0013841864,0.0008056428,0.000256611,0.00086969236,0.0053252564,0.023506867,0.03164732,0.41510385,0.08576772,0.43441558],"study_design_scores_gemma":[0.00012797501,0.00013739598,0.000767544,0.0003578401,0.00011475074,0.0007666593,0.00095096073,0.23955916,0.015604113,0.34580216,0.3955686,0.00024282544],"about_ca_topic_score_codex":0.009330265,"about_ca_topic_score_gemma":0.0118050575,"teacher_disagreement_score":0.020285286,"about_ca_system_score_codex":0.0018070757,"about_ca_system_score_gemma":0.0037571446,"threshold_uncertainty_score":0.06786102},"labels":[],"label_agreement":null},{"id":"W2919005408","doi":"","title":"Tracking Visible Features of Speech for Computer-Based Speech Therapy for Childhood Apraxia of Speech","year":2017,"lang":"en","type":"dissertation","venue":"YorkSpace (York University)","topic":"Speech and dialogue systems","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":"University of Toronto","keywords":"Speech recognition; Speech therapy; Apraxia; Psychology; Audiology; Computer science; Cognitive psychology; Medicine; Aphasia","score_opus":0.020732772544961406,"score_gpt":0.2505456154781702,"score_spread":0.2298128429332088,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919005408","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":[0.29772776,0.0050122146,0.61063176,0.0020966767,0.00040659308,0.00085961766,0.00041311944,0.0024308204,0.08042146],"genre_scores_gemma":[0.6181953,0.005515773,0.34100375,0.0001605513,0.0000494583,0.00045114764,0.00044365154,0.0001742467,0.034006145],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99985516,0.000032668362,0.000008461427,0.00003529201,0.00005253953,0.000015840144],"domain_scores_gemma":[0.99981207,0.00010063992,0.00001687678,0.0000149765465,0.000036628855,0.000018780212],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033522418,0.0003207062,0.00017037576,0.0002056114,0.0002840301,0.0009604691,0.00031149987,0.000394309,0.009344834],"category_scores_gemma":[0.0009919783,0.00015651483,0.00027767758,0.00017274905,0.00029311283,0.0006133465,0.00071587344,0.00052051205,0.002041386],"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":[0.00023532151,0.00024099989,0.002981124,0.00056702725,0.00003632296,0.00015801917,0.0023274147,0.011052805,0.16438143,0.016341014,0.007832863,0.79384565],"study_design_scores_gemma":[0.00027013203,0.0023228258,0.052140795,0.0013992636,0.0003286234,0.001817563,0.0039901,0.30244592,0.28861994,0.028231872,0.3182093,0.00022361278],"about_ca_topic_score_codex":0.0022444285,"about_ca_topic_score_gemma":0.005232454,"teacher_disagreement_score":0.009344834,"about_ca_system_score_codex":0.0004558681,"about_ca_system_score_gemma":0.0011729248,"threshold_uncertainty_score":0.031261623},"labels":[],"label_agreement":null},{"id":"W2919501557","doi":"","title":"A survey of ahead-of-time technologies in dynamic language environments.","year":2018,"lang":"en","type":"article","venue":"Conference of the Centre for Advanced Studies on Collaborative Research","topic":"Speech and dialogue systems","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","score_opus":0.07863584815054377,"score_gpt":0.39342217207511476,"score_spread":0.314786323924571,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2919501557","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.024814622,0.38127062,0.44155422,0.0031084537,0.0017577416,0.00034816648,0.0009094865,0.004712411,0.14152434],"genre_scores_gemma":[0.25108734,0.39001423,0.29906076,0.0021672228,0.0016588813,0.0007050141,0.0032959082,0.0012707713,0.050739832],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9981311,0.0004095366,0.00016037913,0.0003639004,0.0007437685,0.00019132218],"domain_scores_gemma":[0.99597836,0.0022422732,0.00023198742,0.00052393816,0.0007740506,0.00024937323],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021350586,0.0008044472,0.00082054496,0.0024734135,0.0006368673,0.004205643,0.0023883916,0.001586987,0.008405312],"category_scores_gemma":[0.0075775427,0.0006250571,0.00041788325,0.0045561204,0.0007879197,0.010317173,0.0020482165,0.001558001,0.006087404],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022084372,0.00013844913,0.0014070525,0.0018162315,0.000029832188,0.00025064306,0.00090407167,0.0012195224,0.005456838,0.03651969,0.013839237,0.93819755],"study_design_scores_gemma":[0.000022766944,0.00036053438,0.0020745262,0.0017704066,0.00009083688,0.0027308965,0.0015747878,0.0101503,0.011389788,0.029866377,0.9398701,0.000098683035],"about_ca_topic_score_codex":0.0009608663,"about_ca_topic_score_gemma":0.0009148695,"teacher_disagreement_score":0.008405312,"about_ca_system_score_codex":0.00061442045,"about_ca_system_score_gemma":0.0011375681,"threshold_uncertainty_score":0.02811855},"labels":[],"label_agreement":null},{"id":"W2920220837","doi":"10.1145/3308557.3308693","title":"Universal voice-enabled user interfaces using JavaScript","year":2019,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Keyword spotting; Computer science; JavaScript; Spotting; User interface; Human–computer interaction; Software deployment; Voice command device; World Wide Web; Operating system; Speech recognition; Artificial intelligence","score_opus":0.016682767503540166,"score_gpt":0.22494487494772303,"score_spread":0.20826210744418286,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2920220837","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.016433733,0.00029811877,0.7165279,0.00019957358,0.00013586639,0.00045402767,0.0012455216,0.24853364,0.016171575],"genre_scores_gemma":[0.32191467,0.00076755864,0.56018895,0.0012756594,0.00019224227,0.0015750835,0.00400815,0.06408235,0.04599539],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987576,0.0001953567,0.0001752095,0.00032832174,0.0003911759,0.00015226909],"domain_scores_gemma":[0.99636996,0.001657271,0.00023585005,0.00084626355,0.0006086311,0.00028204545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013277725,0.0016242554,0.000651723,0.00058175775,0.00029930857,0.0017639113,0.0017165412,0.0010301586,0.015384709],"category_scores_gemma":[0.0062285727,0.0007559518,0.00054765365,0.00035634756,0.0006359681,0.0021856595,0.0020039196,0.0016076548,0.009126296],"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":[0.002650028,0.00063646125,0.004082162,0.001676334,0.0001902014,0.0021538476,0.003032821,0.004449447,0.3991108,0.025772091,0.076807536,0.47943828],"study_design_scores_gemma":[0.0006202077,0.00062696036,0.006941792,0.00043105442,0.00016820859,0.002784112,0.00024438542,0.14380525,0.4143385,0.0218222,0.4078274,0.0003897752],"about_ca_topic_score_codex":0.0006339753,"about_ca_topic_score_gemma":0.00079303805,"teacher_disagreement_score":0.015384709,"about_ca_system_score_codex":0.00032985982,"about_ca_system_score_gemma":0.000608149,"threshold_uncertainty_score":0.05146694},"labels":[],"label_agreement":null},{"id":"W2924752388","doi":"10.1007/978-3-030-16667-0_9","title":"Automatically Generating Engaging Presentation Slide Decks","year":2019,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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 Alberta","funders":"","keywords":"Presentation (obstetrics); Word (group theory); Public speaking; Quality (philosophy); Deck; Image editing","score_opus":0.018336807715412514,"score_gpt":0.2536974304813124,"score_spread":0.23536062276589986,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2924752388","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08727467,0.0008286602,0.7282978,0.00048303162,0.0016148047,0.0011777299,0.004957691,0.13591288,0.0394527],"genre_scores_gemma":[0.29315022,0.00059540634,0.6304403,0.00023942837,0.00035233216,0.0010875742,0.014439961,0.007413065,0.052281782],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994398,0.00009964977,0.000029012048,0.00018255254,0.00019011811,0.00005873968],"domain_scores_gemma":[0.9985592,0.0007210551,0.000056733137,0.00015417856,0.00038025912,0.00012866141],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004569168,0.001953508,0.0010184048,0.0011773261,0.00048817604,0.0018480354,0.0018553176,0.0012357044,0.054994717],"category_scores_gemma":[0.0034936918,0.0006501343,0.0007186212,0.00063531596,0.0002680897,0.0014334372,0.0023117187,0.0010196471,0.022075629],"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":[0.001223461,0.00025300728,0.0012664198,0.0009744352,0.00006831135,0.0008915956,0.00046075872,0.010974221,0.10225995,0.0042667384,0.08469052,0.79267055],"study_design_scores_gemma":[0.00046739067,0.0008140488,0.003495402,0.0003193871,0.00020034655,0.0011004993,0.0014706287,0.5977027,0.23437978,0.015150002,0.14474727,0.00015259917],"about_ca_topic_score_codex":0.00062769424,"about_ca_topic_score_gemma":0.0011944392,"teacher_disagreement_score":0.054994717,"about_ca_system_score_codex":0.0004586179,"about_ca_system_score_gemma":0.00044967944,"threshold_uncertainty_score":0.18397564},"labels":[],"label_agreement":null},{"id":"W2937542180","doi":"10.1007/s40037-019-0507-4","title":"From semi-conscious to strategic paragraphing","year":2019,"lang":"en","type":"editorial","venue":"Perspectives on Medical Education","topic":"Speech and dialogue systems","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":"Western University","funders":"","keywords":"Computer science; Medical education; Psychology; Data science; Management science; Medicine; Engineering","score_opus":0.009871041660635568,"score_gpt":0.30075713605788157,"score_spread":0.290886094397246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2937542180","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":[0.000017545366,0.008335981,0.00023701001,0.06915827,0.9205048,0.000006630661,0.000025034858,0.000030265586,0.0016845729],"genre_scores_gemma":[0.0007675214,0.007154062,0.00020648476,0.044348165,0.9377187,0.000028177094,0.000020165375,0.000052959826,0.009703861],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9907024,0.0028038726,0.0012632223,0.0010178621,0.0037594603,0.00045312798],"domain_scores_gemma":[0.94935304,0.032769345,0.0018432025,0.0012708289,0.011847253,0.0029162506],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.011362689,0.002634102,0.0029471014,0.0052687083,0.004592294,0.012185617,0.0046809963,0.030387342,0.0110361865],"category_scores_gemma":[0.04644941,0.0011098747,0.0021567354,0.002440737,0.006262396,0.0058840467,0.0025233184,0.032420486,0.0083050225],"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":[0.00003166372,0.000008654934,0.000006683406,0.0002593558,0.000015899062,0.0000816719,0.000026630642,0.000020960362,0.000034224602,0.0016852486,0.9917121,0.0061168727],"study_design_scores_gemma":[0.000062007726,0.000018250974,0.00010020189,0.00093936233,0.000052371288,0.00017462541,0.00006655149,0.00018265436,0.00010566778,0.005634511,0.9926363,0.000027427133],"about_ca_topic_score_codex":0.0033483657,"about_ca_topic_score_gemma":0.009325388,"teacher_disagreement_score":0.030387342,"about_ca_system_score_codex":0.0049970257,"about_ca_system_score_gemma":0.0043012113,"threshold_uncertainty_score":0.06009233},"labels":[],"label_agreement":null},{"id":"W2940790929","doi":"10.1145/3290605.3300719","title":"\"Can you believe [1:21]?!\"","year":2019,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":22,"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; University of British Columbia; Microsoft","keywords":"Timestamp; Computer science; Referent; Taxonomy (biology); Multimedia; World Wide Web; Information retrieval; Human–computer interaction; Linguistics; Computer security","score_opus":0.008984802646720476,"score_gpt":0.205333920574324,"score_spread":0.19634911792760354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2940790929","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":[0.19377813,0.010354402,0.032007843,0.11016128,0.01568112,0.00054153515,0.015117875,0.004135907,0.6182218],"genre_scores_gemma":[0.5701558,0.0066490495,0.014089019,0.023027172,0.0032427108,0.00039251585,0.008710518,0.0017382649,0.37199497],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99891436,0.00049778377,0.000043619857,0.00010897016,0.00030923958,0.00012601161],"domain_scores_gemma":[0.996305,0.0010465194,0.00036031398,0.00017268436,0.0016727401,0.00044267462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011437398,0.00069699046,0.00030281258,0.00093783275,0.0024209241,0.0019922736,0.000558993,0.0011907008,0.059338212],"category_scores_gemma":[0.013443778,0.00014729027,0.00026304892,0.0009536726,0.0008889786,0.0037913963,0.0018731313,0.0015155842,0.028276604],"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":[0.00015636763,0.00003339218,0.014023973,0.00062122894,0.00003307032,0.0011900077,0.056649975,0.0000735147,0.0023311388,0.012659638,0.78457767,0.12764987],"study_design_scores_gemma":[0.0000071387108,0.000060026414,0.010769218,0.00055467436,0.000016806294,0.0009151041,0.043766584,0.00040500078,0.0006198708,0.0022860004,0.94054097,0.000058510996],"about_ca_topic_score_codex":0.009679409,"about_ca_topic_score_gemma":0.01401578,"teacher_disagreement_score":0.059338212,"about_ca_system_score_codex":0.001033206,"about_ca_system_score_gemma":0.0005824632,"threshold_uncertainty_score":0.19850612},"labels":[],"label_agreement":null},{"id":"W2946864768","doi":"10.1002/wcs.1505","title":"U‐shaped development in error‐driven child phonology","year":2019,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Cognitive Science","topic":"Speech and dialogue systems","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":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada; University of Massachusetts Amherst","keywords":"Phonology; Grammar; Linguistics; Phonological development; Constraint (computer-aided design); Computer science; Language acquisition; Phonological rule; Variation (astronomy); Markedness; Cognitive psychology; Psychology; Artificial intelligence; Natural language processing; Mathematics","score_opus":0.10235273217535215,"score_gpt":0.38801532595505034,"score_spread":0.28566259377969816,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2946864768","genre_codex":"empirical","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":[0.9753107,0.00136622,0.011908197,0.00037999096,0.000025617112,0.00002631409,0.00045178505,0.0004003888,0.010130827],"genre_scores_gemma":[0.9931839,0.0006015648,0.004156844,0.000069778114,0.0000071272902,0.00003337104,0.0001725958,0.000096752854,0.0016781561],"study_design_codex":"observational","study_design_gemma":"not_applicable","domain_scores_codex":[0.99817824,0.00036592915,0.00016719908,0.0005449989,0.0005366237,0.00020697726],"domain_scores_gemma":[0.98873514,0.005026569,0.0024206503,0.0019766951,0.001492808,0.00034817465],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027044448,0.00034325942,0.0004210885,0.001429887,0.00032194535,0.0019989288,0.0006304955,0.00077800924,0.003983944],"category_scores_gemma":[0.013782447,0.00036016267,0.000429963,0.0008899583,0.0019285566,0.0019770365,0.0016045085,0.0010311184,0.00091706443],"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":[0.0005651792,0.00029993264,0.56585264,0.00041533445,0.00014631425,0.0053692097,0.018873097,0.004340106,0.04527431,0.040928,0.00194131,0.31599465],"study_design_scores_gemma":[0.000020711135,0.0008581957,0.9159507,0.00019264375,0.000071831964,0.009545138,0.0034739017,0.006057887,0.023269951,0.030437827,0.010023817,0.00009744405],"about_ca_topic_score_codex":0.0013579788,"about_ca_topic_score_gemma":0.0010626125,"teacher_disagreement_score":0.003983944,"about_ca_system_score_codex":0.00044347032,"about_ca_system_score_gemma":0.00079774344,"threshold_uncertainty_score":0.014302611},"labels":[],"label_agreement":null},{"id":"W2951577137","doi":"10.48550/arxiv.1704.00057","title":"Frames: A Corpus for Adding Memory to Goal-Oriented Dialogue Systems","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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; Université de Montréal","funders":"","keywords":"Computer science; Task (project management); Baseline (sea); Frame (networking); Presentation (obstetrics); Tracking (education); Artificial intelligence; Natural language processing; State (computer science); Human–computer interaction; Programming language; Psychology; Engineering","score_opus":0.06518538499493316,"score_gpt":0.2105848772668836,"score_spread":0.14539949227195043,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2951577137","genre_codex":"dataset","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":[0.14587045,0.0100801205,0.050094195,0.0019389375,0.0018129409,0.0016703156,0.74574095,0.012026811,0.03076536],"genre_scores_gemma":[0.1531292,0.0010744878,0.04595461,0.0003774182,0.00034074692,0.0025356559,0.78806466,0.0011156157,0.0074075493],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962962,0.0015999494,0.00039016275,0.0008903616,0.0005904793,0.00023280668],"domain_scores_gemma":[0.9927786,0.0038903875,0.00047220988,0.001180822,0.0012087921,0.00046915346],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019677775,0.0017439465,0.00079489785,0.004828051,0.0020552718,0.0017968991,0.0020219397,0.0025407788,0.011294596],"category_scores_gemma":[0.013592932,0.00056198955,0.00094232545,0.0035235223,0.0009982616,0.0021877082,0.0029185116,0.0016925508,0.0082043875],"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":[0.0016848866,0.00091747864,0.0119530335,0.005767051,0.0003844569,0.001331619,0.0069054505,0.0077013383,0.014308173,0.01346226,0.7433099,0.19227426],"study_design_scores_gemma":[0.0005996924,0.00040780383,0.047878552,0.0008667906,0.00020049723,0.0012874634,0.0043687546,0.02617499,0.011673908,0.013637317,0.8925977,0.00030667975],"about_ca_topic_score_codex":0.014216384,"about_ca_topic_score_gemma":0.028365934,"teacher_disagreement_score":0.014216384,"about_ca_system_score_codex":0.0014226191,"about_ca_system_score_gemma":0.0015239473,"threshold_uncertainty_score":0.03778422},"labels":[],"label_agreement":null},{"id":"W2953660811","doi":"10.21437/interspeech.2019-3062","title":"Analyzing Verbal and Nonverbal Features for Predicting Group Performance","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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 the Fraser Valley","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonverbal communication; Task (project management); Conversation; Computer science; Feature (linguistics); Natural language processing; Artificial intelligence; Psychology; Cognitive psychology; Speech recognition; Communication; Linguistics","score_opus":0.01410929847238717,"score_gpt":0.23622065730283118,"score_spread":0.222111358830444,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2953660811","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":[0.9378687,0.0026575453,0.029957276,0.0005486458,0.00039191538,0.00020581706,0.016552895,0.0016636567,0.010153744],"genre_scores_gemma":[0.96009994,0.00035645778,0.014127063,0.00010505457,0.00024175952,0.0001532793,0.023059014,0.000101020254,0.0017565365],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9977736,0.0009040298,0.0001125541,0.00054091803,0.00045300252,0.00021585866],"domain_scores_gemma":[0.98872757,0.0074678627,0.0010704858,0.00083853846,0.0011342341,0.0007613029],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027224128,0.0015972438,0.00070449186,0.0023517646,0.0004490386,0.0011930077,0.0005862357,0.0011773787,0.00219619],"category_scores_gemma":[0.012394689,0.00016917153,0.000606245,0.0009797161,0.0003354,0.0012984426,0.0009590197,0.0012336839,0.0023818405],"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":[0.0040777544,0.0018153009,0.41724738,0.0013161841,0.00089090597,0.0003648392,0.0012295756,0.017179765,0.03613404,0.0009568195,0.032307692,0.4864797],"study_design_scores_gemma":[0.00016160597,0.0024449297,0.6521713,0.00024617824,0.0006074555,0.00089372083,0.0022328536,0.29170865,0.025089176,0.0046452465,0.019516628,0.0002822383],"about_ca_topic_score_codex":0.0023612136,"about_ca_topic_score_gemma":0.0038909046,"teacher_disagreement_score":0.0027224128,"about_ca_system_score_codex":0.00033196152,"about_ca_system_score_gemma":0.0003995588,"threshold_uncertainty_score":0.014397681},"labels":[],"label_agreement":null},{"id":"W2955286979","doi":"10.1145/3331184.3331271","title":"Yelling at Your TV","year":2019,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Entertainment; Computer science; Speech recognition; Natural (archaeology); Action (physics); Forcing (mathematics); Natural language; Natural language processing; Human–computer interaction","score_opus":0.019969551642044912,"score_gpt":0.22816123912242395,"score_spread":0.20819168748037903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2955286979","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":[0.22316138,0.0049843467,0.009985739,0.019787388,0.0035630334,0.0002051637,0.008703324,0.008790518,0.7208191],"genre_scores_gemma":[0.36403778,0.0021515633,0.0059148665,0.0064917943,0.0010068797,0.00005783858,0.0055185193,0.0014214226,0.6133994],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99979824,0.000038492897,0.00000775316,0.0000328279,0.00007981711,0.000042906602],"domain_scores_gemma":[0.99933773,0.00015384756,0.000060555107,0.00005921218,0.00022459378,0.00016410038],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027098454,0.0004164899,0.0002534771,0.0004471807,0.0009330462,0.0018250984,0.00033825068,0.0008497261,0.12621188],"category_scores_gemma":[0.0017864268,0.00014528872,0.00019227296,0.0004300165,0.00025317617,0.0016747357,0.0008472198,0.0006560229,0.044759646],"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":[0.0005656165,0.00010770495,0.012528188,0.0002742121,0.000051040137,0.0009139245,0.003060903,0.00012891824,0.011370227,0.0032839838,0.7722812,0.195434],"study_design_scores_gemma":[0.000021782473,0.00018425302,0.025142115,0.00012517053,0.000050656196,0.0016827729,0.007012978,0.0012740294,0.004145331,0.0016089183,0.95869684,0.000054984266],"about_ca_topic_score_codex":0.0027559772,"about_ca_topic_score_gemma":0.006280232,"teacher_disagreement_score":0.12621188,"about_ca_system_score_codex":0.00025095054,"about_ca_system_score_gemma":0.00015146408,"threshold_uncertainty_score":0.42222083},"labels":[],"label_agreement":null},{"id":"W2956357266","doi":"10.3390/mti3030054","title":"Graph-Based Prediction of Meeting Participation","year":2019,"lang":"en","type":"article","venue":"Multimodal Technologies and Interaction","topic":"Speech and dialogue systems","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 the Fraser Valley","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nonverbal communication; Baseline (sea); Computer science; Task (project management); Feature (linguistics); Point (geometry); Predictive modelling; Artificial intelligence; Machine learning; Graph; Cognitive psychology; Natural language processing; Psychology; Developmental psychology; Mathematics; Linguistics; Engineering; Theoretical computer science","score_opus":0.019578239322930725,"score_gpt":0.256861156871655,"score_spread":0.23728291754872427,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2956357266","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":[0.93090653,0.00037487986,0.059038248,0.00042792768,0.000043961456,0.00006730488,0.004197489,0.0009196412,0.00402409],"genre_scores_gemma":[0.9937464,0.000056010984,0.0037465233,0.000012899023,0.000014500161,0.00002378329,0.0016796277,0.000018954477,0.00070147496],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997136,0.00010341751,0.000010981017,0.000089583395,0.000043162418,0.000039244773],"domain_scores_gemma":[0.997837,0.0015003452,0.00021911885,0.00009569435,0.00022216041,0.00012566244],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056964613,0.0005401838,0.00030182683,0.0012942461,0.0001642708,0.00042617985,0.00041072382,0.00045997364,0.0021354945],"category_scores_gemma":[0.0037818663,0.00013260447,0.00039750064,0.0006987932,0.00015737413,0.00052513217,0.0002859429,0.0004274287,0.0010222513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015096713,0.000441536,0.21213713,0.00026939393,0.00027356032,0.0003342761,0.00044857964,0.5926114,0.008632069,0.0026028077,0.00671023,0.17402942],"study_design_scores_gemma":[0.000009520117,0.0000547224,0.024839241,0.0000066443,0.000016600194,0.000031433152,0.000045784454,0.97255343,0.00063332403,0.0013811417,0.000419987,0.000008198249],"about_ca_topic_score_codex":0.0086092865,"about_ca_topic_score_gemma":0.011254113,"teacher_disagreement_score":0.0086092865,"about_ca_system_score_codex":0.00039151142,"about_ca_system_score_gemma":0.00026305794,"threshold_uncertainty_score":0.017118394},"labels":[],"label_agreement":null},{"id":"W29579747","doi":"10.1055/s-0044-102308","title":"Hemispheric asymmetries for accessing the phonological representation of single printed words.","year":2005,"lang":"de","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Representation (politics); Computer science; Linguistics; Communication; Natural language processing; Psychology","score_opus":0.05867029426940099,"score_gpt":0.30217023763856393,"score_spread":0.24349994336916295,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W29579747","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":[0.99011457,0.00044550325,0.0020364954,0.00012245218,0.000036872403,0.000024474071,0.0002557549,0.000058838377,0.00690501],"genre_scores_gemma":[0.9975993,0.00017721484,0.00078134576,0.00007656302,0.000017675397,0.0000331329,0.0001425502,0.00002962026,0.0011424917],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999728,0.00004050336,0.00001817881,0.00009071168,0.00007575681,0.000046746274],"domain_scores_gemma":[0.99833626,0.00074127765,0.00040810436,0.00021980671,0.00011114919,0.00018345668],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051734515,0.00023372544,0.0002134933,0.0005988434,0.00013386655,0.0005556271,0.00019134516,0.00026614525,0.0057052416],"category_scores_gemma":[0.0020655901,0.0001383022,0.00013449015,0.0001082678,0.000790306,0.0005027841,0.00034561957,0.0003847059,0.00064076355],"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":[0.0013805222,0.00011023695,0.008793795,0.00012995084,0.00003323854,0.0006997003,0.0004699903,0.00009355349,0.950739,0.0020368055,0.00042472273,0.035088535],"study_design_scores_gemma":[0.00039143563,0.0016514502,0.70151615,0.000075395015,0.0001733066,0.008702445,0.0009824637,0.0015203096,0.2712965,0.007717752,0.005893807,0.00007905822],"about_ca_topic_score_codex":0.0004521337,"about_ca_topic_score_gemma":0.00073311996,"teacher_disagreement_score":0.0057052416,"about_ca_system_score_codex":0.00017514384,"about_ca_system_score_gemma":0.000206108,"threshold_uncertainty_score":0.019085944},"labels":[],"label_agreement":null},{"id":"W2962475843","doi":"10.5334/pb.491","title":"Recognition Times for 54 Thousand Dutch Words: Data from the Dutch Crowdsourcing Project","year":2019,"lang":"en","type":"article","venue":"Psychologica Belgica","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":18,"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":"Lexicon; Crowdsourcing; Vocabulary; Psychology; Word (group theory); Test (biology); Word lists by frequency; Linguistics; Word recognition; Natural language processing; Computer science; World Wide Web","score_opus":0.12009769058073629,"score_gpt":0.3337351743750391,"score_spread":0.2136374837943028,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2962475843","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":[0.9241929,0.0011385677,0.003615879,0.00021888549,0.00009344066,0.00020442529,0.06365021,0.0003866723,0.006499049],"genre_scores_gemma":[0.8551001,0.0006066082,0.0059605916,0.000118225806,0.00008448983,0.0010451541,0.12842503,0.00036354692,0.008296232],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9954457,0.0009856388,0.0006749787,0.0010342052,0.0015779628,0.00028159286],"domain_scores_gemma":[0.9896219,0.0043704,0.0014860706,0.0015197681,0.0023664902,0.00063532847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016569872,0.00070636626,0.0010918498,0.0025368917,0.0005454411,0.00083341176,0.0006041359,0.00097166124,0.0032447127],"category_scores_gemma":[0.010675678,0.00028030237,0.0006578439,0.003401426,0.0004859769,0.00086574256,0.0013517805,0.00044761974,0.0047500217],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0051874174,0.0010410852,0.40305716,0.0035551758,0.0011749323,0.0032210313,0.01466994,0.010680587,0.06669947,0.001337207,0.0922475,0.3971285],"study_design_scores_gemma":[0.0002002384,0.00052280317,0.8749647,0.0001498351,0.00018829305,0.0018174167,0.004391043,0.012226131,0.017325753,0.0015116764,0.08636344,0.0003386572],"about_ca_topic_score_codex":0.013790481,"about_ca_topic_score_gemma":0.013413141,"teacher_disagreement_score":0.013790481,"about_ca_system_score_codex":0.00061392755,"about_ca_system_score_gemma":0.00047349356,"threshold_uncertainty_score":0.027420461},"labels":[],"label_agreement":null},{"id":"W2963924362","doi":"","title":"Natural Language Generation in Dialogue using Lexicalized and Delexicalized Data","year":2017,"lang":"en","type":"article","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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":"Computer science; Natural language generation; Natural language processing; Artificial intelligence; Natural language; Sentence; Grammar; Language model; Encoder; Task (project management); Value (mathematics); Recurrent neural network; Speech recognition; Artificial neural network; Linguistics; Machine learning","score_opus":0.1867842812394854,"score_gpt":0.24707124342766226,"score_spread":0.06028696218817686,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2963924362","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08891662,0.00030865686,0.9027523,0.0006116493,0.00014243029,0.00012145286,0.00032889456,0.0039081173,0.0029099134],"genre_scores_gemma":[0.7899582,0.00016780269,0.20458664,0.0003132122,0.000062262574,0.00018771354,0.000992969,0.00038448058,0.0033467084],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99890554,0.0005595851,0.000052453397,0.0003043189,0.00011639914,0.00006183256],"domain_scores_gemma":[0.9967384,0.0023319852,0.0001642137,0.00033950913,0.00033601501,0.00008994196],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017194181,0.00063140196,0.00048930646,0.0003985359,0.00034539987,0.0009860717,0.0010457787,0.0009416304,0.0019380382],"category_scores_gemma":[0.007882839,0.0004490459,0.0007044308,0.00025161152,0.00067399454,0.0017759138,0.0012461523,0.0016603091,0.0008432817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008769452,0.00052776677,0.0051757023,0.00045123542,0.00018008452,0.0010572845,0.0022264335,0.4663402,0.06907188,0.040299702,0.006632984,0.40715986],"study_design_scores_gemma":[0.000021227606,0.00006502049,0.00028162848,0.000014070911,0.00001587049,0.00007903788,0.000053451306,0.98019,0.0068806903,0.010988892,0.0013931426,0.000016996002],"about_ca_topic_score_codex":0.0026026182,"about_ca_topic_score_gemma":0.0037911853,"teacher_disagreement_score":0.0026026182,"about_ca_system_score_codex":0.00057150796,"about_ca_system_score_gemma":0.00072940567,"threshold_uncertainty_score":0.009093225},"labels":[],"label_agreement":null},{"id":"W2976987298","doi":"10.1007/s10339-019-00933-y","title":"Mapping semantic space: property norms and semantic richness","year":2019,"lang":"en","type":"article","venue":"Cognitive Processing","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":30,"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 Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Semantic space; Property (philosophy); Space (punctuation); Species richness; Computer science; Natural language processing; Psychology; Linguistics; Epistemology; Ecology; Philosophy; Biology","score_opus":0.01647602388086964,"score_gpt":0.23559085799785384,"score_spread":0.2191148341169842,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2976987298","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18201262,0.000751811,0.7940076,0.0018748649,0.00010192467,0.00007648278,0.00041976082,0.0003643125,0.020390457],"genre_scores_gemma":[0.9171492,0.00028046992,0.08092778,0.00010330525,0.000055273693,0.00009115352,0.00026887006,0.00010067072,0.0010231698],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9972631,0.0012413866,0.00024018122,0.000665068,0.00045631512,0.00013409404],"domain_scores_gemma":[0.9897882,0.0066317925,0.00079475745,0.001511732,0.00085079623,0.00042270398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003725675,0.00041877016,0.0005376842,0.0025954193,0.00097312365,0.005788067,0.0009334058,0.0008618597,0.0042647943],"category_scores_gemma":[0.0199679,0.00046444716,0.00089755864,0.001725267,0.005091128,0.022268187,0.0036254746,0.0013884506,0.00027987294],"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":[0.00019358721,0.000070267335,0.004453117,0.00019568822,0.000076717646,0.00017511143,0.005384034,0.004071929,0.0047414894,0.91091627,0.0007241149,0.068997614],"study_design_scores_gemma":[0.000016281929,0.000034997458,0.001345066,0.000039306433,0.000036238318,0.00019312665,0.0019279487,0.013930332,0.0018379122,0.97745174,0.0031657321,0.000021464739],"about_ca_topic_score_codex":0.0012251483,"about_ca_topic_score_gemma":0.000759435,"teacher_disagreement_score":0.005788067,"about_ca_system_score_codex":0.00080432347,"about_ca_system_score_gemma":0.00073822873,"threshold_uncertainty_score":0.019703507},"labels":[],"label_agreement":null},{"id":"W2977768457","doi":"","title":"Applications of Environment Canada's Text-to-Voice System","year":2000,"lang":"en","type":"article","venue":"80th AMS Annual  Meeting","topic":"Speech and dialogue systems","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":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Computer science; Speech recognition; Telecommunications; Business","score_opus":0.004000582279409966,"score_gpt":0.18710058899864446,"score_spread":0.1831000067192345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2977768457","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":[0.38674936,0.0050027794,0.17806864,0.008530264,0.003023151,0.0018870067,0.018707898,0.038956326,0.35907462],"genre_scores_gemma":[0.72352463,0.0026388343,0.12946455,0.0010902984,0.0003896511,0.00025031035,0.009940132,0.0016572494,0.13104437],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99897075,0.00014502439,0.000028699867,0.000120552526,0.0005786841,0.00015637791],"domain_scores_gemma":[0.99825925,0.00028170124,0.000020740456,0.00007215867,0.0012208499,0.000145384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009172129,0.0006105266,0.0003727123,0.0009793008,0.0019711198,0.0014159374,0.0009677094,0.0007570022,0.009728971],"category_scores_gemma":[0.0028675813,0.00018128581,0.0002034324,0.0015061264,0.00047677325,0.0005861659,0.00092636456,0.00038384137,0.0024327647],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0015662161,0.00027337184,0.00993588,0.000384116,0.00009252042,0.0009933194,0.0013131223,0.020022355,0.054069154,0.009900547,0.16369043,0.73775893],"study_design_scores_gemma":[0.00054559595,0.00034349022,0.025261834,0.00013303627,0.00023568686,0.0006989618,0.0023805778,0.2213572,0.057076387,0.0042310483,0.6874564,0.00027963961],"about_ca_topic_score_codex":0.89077157,"about_ca_topic_score_gemma":0.92321444,"teacher_disagreement_score":0.10922843,"about_ca_system_score_codex":0.0060926457,"about_ca_system_score_gemma":0.013597178,"threshold_uncertainty_score":0.21974337},"labels":[],"label_agreement":null},{"id":"W2980912952","doi":"10.1145/3332167.3356884","title":"ReMap","year":2019,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Adobe Systems","keywords":"Computer science; Task (project management); Modalities; Deixis; Human–computer interaction; Interface (matter); Artificial intelligence; Multimodal interaction; Modality (human–computer interaction); Natural language processing; Information retrieval","score_opus":0.004797645563983404,"score_gpt":0.18709615142662386,"score_spread":0.18229850586264046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2980912952","genre_codex":"software","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":[0.009700406,0.0015924561,0.2871753,0.0011982684,0.001457516,0.0011755726,0.07354507,0.3996976,0.2244578],"genre_scores_gemma":[0.13600357,0.0022943595,0.26100373,0.0041760746,0.0004184959,0.0032085024,0.22459146,0.076755255,0.29154858],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989969,0.00012721115,0.00007470332,0.00024298609,0.0004354862,0.00012277467],"domain_scores_gemma":[0.9985353,0.00027161327,0.000044229004,0.00047732625,0.0005626091,0.000108959975],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010891525,0.0015118315,0.0008959472,0.0012243126,0.0009268881,0.0023302787,0.0030629712,0.0014867818,0.11716742],"category_scores_gemma":[0.0051405425,0.0006143651,0.00091057434,0.0009506811,0.0004040778,0.003525805,0.0042178864,0.0014471862,0.10333519],"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":[0.00096596,0.000126571,0.0010980432,0.00095629273,0.00008758851,0.0004316408,0.00046846078,0.0018475105,0.008645822,0.009706271,0.7644038,0.21126208],"study_design_scores_gemma":[0.00009671311,0.00011091947,0.001476839,0.00016619462,0.000047342834,0.00054387026,0.00025439746,0.010320469,0.011839684,0.010102411,0.96493226,0.00010879847],"about_ca_topic_score_codex":0.0033226695,"about_ca_topic_score_gemma":0.0036983853,"teacher_disagreement_score":0.11716742,"about_ca_system_score_codex":0.0004312225,"about_ca_system_score_gemma":0.0010696893,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W2985162128","doi":"10.1121/1.5136964","title":"Overview of Speech Communication Research","year":2019,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Computer science; Work (physics); Speech communication; Field (mathematics); Range (aeronautics); Linguistics; Engineering","score_opus":0.06504034882820929,"score_gpt":0.34266294175318746,"score_spread":0.27762259292497815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2985162128","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":[0.0015503818,0.9207202,0.011911595,0.007681006,0.0024533481,0.00009139104,0.00047939533,0.00027041498,0.05484224],"genre_scores_gemma":[0.013990567,0.95778066,0.009827769,0.0024242871,0.004277816,0.000115159775,0.00087874994,0.000098296616,0.010606624],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975121,0.00063179876,0.00034267784,0.00047807247,0.0008879355,0.00014741061],"domain_scores_gemma":[0.9933648,0.004092814,0.0002651482,0.00026494346,0.001751384,0.00026089535],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032122675,0.0011856818,0.0010284332,0.008968625,0.0014296855,0.0046653887,0.0013119665,0.0031961787,0.01797247],"category_scores_gemma":[0.006552804,0.0006537174,0.0007983837,0.007059028,0.0015242195,0.0046761823,0.0015384202,0.0021701592,0.011459751],"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":[0.00010980636,0.00010084906,0.0013508867,0.007410506,0.000065032065,0.00023866797,0.0009423572,0.0005996442,0.0014323395,0.034885142,0.051245138,0.90161955],"study_design_scores_gemma":[0.000009875997,0.000102889935,0.003802659,0.007607538,0.00006438325,0.0014474745,0.0006715005,0.00045982611,0.00072320516,0.020385241,0.964673,0.000052432646],"about_ca_topic_score_codex":0.004645496,"about_ca_topic_score_gemma":0.0029847554,"teacher_disagreement_score":0.01797247,"about_ca_system_score_codex":0.00236794,"about_ca_system_score_gemma":0.00359187,"threshold_uncertainty_score":0.06012392},"labels":[],"label_agreement":null},{"id":"W2992279460","doi":"10.22215/etd/2019-13680","title":"Willingness to Communicate and Second Language Speech Fluency: A Complex Dynamic Systems Perspective","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Speech and dialogue systems","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":"","keywords":"Fluency; Perspective (graphical); Computer science; Attractor; Cognitive psychology; Psychology; Artificial intelligence; Mathematics; Mathematics education","score_opus":0.013374859619972777,"score_gpt":0.28545823761687084,"score_spread":0.2720833779968981,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2992279460","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":[0.96762633,0.00063395716,0.018733459,0.0004919741,0.00001124722,0.00005995306,0.00007243419,0.000023944216,0.012346732],"genre_scores_gemma":[0.9978453,0.00011233334,0.001752159,0.00002602528,0.0000056482513,0.000025013329,0.000017590417,0.0000030658182,0.00021297249],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9990609,0.0004976014,0.000049534505,0.00016891537,0.00015111371,0.0000719418],"domain_scores_gemma":[0.993932,0.0047815857,0.00071805983,0.0001816286,0.00020144814,0.00018535634],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015754647,0.0002995338,0.00028092467,0.0014735557,0.00043374003,0.0031123888,0.00026386123,0.00052398717,0.0024888453],"category_scores_gemma":[0.006869973,0.00018214036,0.0003040162,0.0008418177,0.0019640492,0.0016236509,0.0012373592,0.0006325341,0.00011152976],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0006387824,0.00061840564,0.51625925,0.000881471,0.00038546845,0.0027347652,0.094874874,0.01664926,0.026855895,0.15593931,0.0006784908,0.18348397],"study_design_scores_gemma":[0.000033837467,0.0007893168,0.81525177,0.00016917959,0.00010992579,0.0017381628,0.03625158,0.030403018,0.0031605538,0.10519721,0.006735531,0.00015992447],"about_ca_topic_score_codex":0.0016951729,"about_ca_topic_score_gemma":0.0011890262,"teacher_disagreement_score":0.0031123888,"about_ca_system_score_codex":0.000911138,"about_ca_system_score_gemma":0.0004894916,"threshold_uncertainty_score":0.0083319545},"labels":[],"label_agreement":null},{"id":"W2995567445","doi":"10.1098/rstb.2018.0531","title":"Studying language in context using the temporal generalization method","year":2019,"lang":"en","type":"review","venue":"Philosophical Transactions of the Royal Society B Biological Sciences","topic":"Speech and dialogue systems","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":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Generalization; Context (archaeology); Computer science; Natural language processing; Artificial intelligence; Linguistics; Mathematics; Geography; Philosophy; Archaeology","score_opus":0.22437931111628429,"score_gpt":0.38739923758601563,"score_spread":0.16301992646973135,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2995567445","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":[0.083223976,0.0005457316,0.90934986,0.00044304854,0.000067796536,0.00010191015,0.00029580953,0.0005636927,0.0054081995],"genre_scores_gemma":[0.72064275,0.0005026736,0.27640948,0.00017950268,0.000100090634,0.00031497696,0.0003572431,0.00023181351,0.0012614437],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99878544,0.0005950013,0.000051612165,0.00030586563,0.0001947611,0.00006736138],"domain_scores_gemma":[0.9957165,0.0027973827,0.00046114268,0.0007494835,0.00016294736,0.00011246772],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030591397,0.0006461682,0.0005399303,0.0014488768,0.0004492223,0.0013808216,0.0010796757,0.00076928706,0.0038989463],"category_scores_gemma":[0.013429797,0.0003335111,0.0014994373,0.0011942612,0.001646382,0.003764171,0.002215833,0.0019072173,0.00043925422],"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":[0.0006888547,0.00019595433,0.022580156,0.0007099497,0.0006018368,0.001049571,0.005365888,0.124841936,0.067963,0.3667417,0.0034470535,0.40581417],"study_design_scores_gemma":[0.00004517744,0.00018399558,0.015758272,0.00008439242,0.000095144824,0.00051768264,0.000575917,0.5315483,0.0061801844,0.43846297,0.0064527947,0.000095161166],"about_ca_topic_score_codex":0.0029497659,"about_ca_topic_score_gemma":0.0025008866,"teacher_disagreement_score":0.0038989463,"about_ca_system_score_codex":0.0006234085,"about_ca_system_score_gemma":0.0006936319,"threshold_uncertainty_score":0.01617843},"labels":[],"label_agreement":null},{"id":"W2997940326","doi":"10.1109/access.2019.2963560","title":"Dietary Composition Perception Algorithm Using Social Robot Audition for Mandarin Chinese","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":62,"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":"Petroleum Technology Research Centre; Guizhou Science and Technology Department; National Natural Science Foundation of China","keywords":"Computer science; Robot; Semantics (computer science); Artificial intelligence; Speech recognition; Conversation; Social robot; Convolutional neural network; Mobile robot; Psychology; Robot control; Communication","score_opus":0.0859695610552689,"score_gpt":0.3456348266881955,"score_spread":0.2596652656329266,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997940326","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":[0.78715193,0.0005787269,0.20219405,0.00024203636,0.00012270836,0.00022436402,0.00037167457,0.0037361744,0.0053783366],"genre_scores_gemma":[0.91773105,0.00013501765,0.07759134,0.00008447295,0.000024223751,0.00011390226,0.000499296,0.000041571966,0.0037791599],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997917,0.000018820061,0.00001549381,0.00007779882,0.000057987178,0.000038226728],"domain_scores_gemma":[0.9998006,0.000050279836,0.000017419217,0.00001680675,0.000097872486,0.000017024113],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032687737,0.0005659277,0.00038862549,0.0006262512,0.00038752749,0.0002911421,0.0004999197,0.00043677137,0.0016582955],"category_scores_gemma":[0.00070494926,0.00012560924,0.0003863664,0.00028269496,0.0001881593,0.00028041942,0.00036516905,0.00027501103,0.00032318835],"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":[0.0012206569,0.00022838094,0.013912602,0.00016795265,0.00010302784,0.0008645391,0.00041696528,0.0382395,0.108059496,0.00071731856,0.0026667928,0.83340275],"study_design_scores_gemma":[0.000054825643,0.00021478765,0.019732542,0.000007158871,0.000056693123,0.00018923986,0.00018977572,0.9501379,0.027555339,0.00033838535,0.0014970348,0.000026254655],"about_ca_topic_score_codex":0.024910469,"about_ca_topic_score_gemma":0.017869933,"teacher_disagreement_score":0.024910469,"about_ca_system_score_codex":0.00043137177,"about_ca_system_score_gemma":0.0006923889,"threshold_uncertainty_score":0.049530983},"labels":[],"label_agreement":null},{"id":"W2998142337","doi":"10.26483/ijarcs.v10i6.6497","title":"INTERACTION ANALYSIS OVER SPEECH FOR CALL CENTRE","year":2019,"lang":"en","type":"article","venue":"International Journal of Advanced Research in Computer Science","topic":"Speech and dialogue systems","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; Call centre; Speech recognition; World Wide Web; Telecommunications","score_opus":0.04110760722433496,"score_gpt":0.4040420514168758,"score_spread":0.36293444419254084,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2998142337","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":[0.7488776,0.0025632058,0.18068422,0.001128179,0.00061420276,0.00044656193,0.034093305,0.00911183,0.022480909],"genre_scores_gemma":[0.93770736,0.00053868355,0.03402653,0.00017581726,0.00027511534,0.0002871371,0.018469222,0.00046637925,0.008053774],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983632,0.00029977938,0.00008475534,0.00037061507,0.0007153757,0.00016629319],"domain_scores_gemma":[0.99806124,0.0010004463,0.00013094352,0.0001521574,0.0005236485,0.00013149201],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005635104,0.00081019354,0.00054508593,0.00229077,0.00045443527,0.001132034,0.00035328753,0.0006709791,0.009341127],"category_scores_gemma":[0.0026394764,0.0001271503,0.0006746449,0.0016156097,0.00029352587,0.0006354689,0.00061357627,0.0005995465,0.0037268733],"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":[0.0034052606,0.0006132928,0.03543932,0.0015035609,0.0005829999,0.0022156248,0.001853211,0.0241508,0.1926324,0.0028188338,0.028361652,0.7064231],"study_design_scores_gemma":[0.00012054359,0.0013617296,0.41276857,0.00018408262,0.000513288,0.0031886105,0.0037943716,0.42335293,0.07966327,0.0068305493,0.06789495,0.0003270536],"about_ca_topic_score_codex":0.0050762547,"about_ca_topic_score_gemma":0.0047604223,"teacher_disagreement_score":0.009341127,"about_ca_system_score_codex":0.00060529145,"about_ca_system_score_gemma":0.00045295616,"threshold_uncertainty_score":0.031249166},"labels":[],"label_agreement":null},{"id":"W3001674625","doi":"","title":"Introducing two databases of spoken French throughout adulthood","year":2017,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Speech and dialogue systems","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 à Montréal","funders":"","keywords":"Computer science; Natural language processing; Database; Spoken language; Artificial intelligence; Information retrieval","score_opus":0.024913407410504736,"score_gpt":0.27395384645293924,"score_spread":0.2490404390424345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3001674625","genre_codex":"empirical","genre_gemma":"dataset","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5703117,0.005350224,0.2913469,0.009798989,0.0007392768,0.0004923077,0.048613362,0.0083743045,0.06497291],"genre_scores_gemma":[0.83354145,0.0015252231,0.120393544,0.0005722127,0.00018280401,0.000351827,0.024821734,0.0007404417,0.017870676],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978951,0.0009141606,0.00014480097,0.00053767674,0.00035814257,0.00015002165],"domain_scores_gemma":[0.99060947,0.0050875163,0.00033770915,0.0010032286,0.0024193646,0.00054271054],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022955071,0.0004613274,0.00044357372,0.0032063916,0.0013405413,0.0061847167,0.0012967705,0.001564773,0.006906428],"category_scores_gemma":[0.010775516,0.0003385591,0.0004475449,0.0025242716,0.0008071347,0.004243704,0.0017215624,0.00088929076,0.0017851604],"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":[0.0030230326,0.000663028,0.070341125,0.001048828,0.00028696423,0.0035458223,0.06337237,0.012197377,0.027014814,0.13992089,0.053175308,0.62541044],"study_design_scores_gemma":[0.0002619962,0.0008017703,0.09861033,0.00078446284,0.0003475692,0.004855353,0.072198704,0.094986744,0.04156207,0.059396256,0.62563753,0.00055725244],"about_ca_topic_score_codex":0.065602444,"about_ca_topic_score_gemma":0.06087855,"teacher_disagreement_score":0.065602444,"about_ca_system_score_codex":0.002593487,"about_ca_system_score_gemma":0.0015639397,"threshold_uncertainty_score":0.13044119},"labels":[],"label_agreement":null},{"id":"W3003292801","doi":"10.1080/0163853x.2019.1700760","title":"Interpretation of Discourse Connectives Is Probabilistic: Evidence From the Study of <i>But</i> and <i>Although</i>","year":2020,"lang":"en","type":"article","venue":"Discourse Processes","topic":"Speech and dialogue systems","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":"Simon Fraser University","funders":"","keywords":"Ambiguity; Interpretation (philosophy); Comprehension; Coherence (philosophical gambling strategy); Meaning (existential); Linguistics; Probabilistic logic; Computer science; Natural language processing; Semantics (computer science); Logical connective; Relation (database); Psychology; Artificial intelligence; Mathematics","score_opus":0.03827736900970941,"score_gpt":0.306500817544834,"score_spread":0.2682234485351246,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3003292801","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":[0.9071995,0.0019470243,0.05533841,0.0023395931,0.000077494886,0.00013382881,0.00019338918,0.00013009414,0.032640584],"genre_scores_gemma":[0.9924386,0.0004458834,0.0064452672,0.00019257497,0.00006002887,0.000056908335,0.00008616634,0.00006406363,0.00021058747],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98352283,0.009360581,0.0007956272,0.002662184,0.003278695,0.00038008092],"domain_scores_gemma":[0.68724024,0.25783375,0.030167162,0.015254649,0.0082065165,0.0012975972],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.020799499,0.00059886475,0.0004950634,0.0012724585,0.0016417837,0.004203585,0.00138619,0.001616934,0.004479245],"category_scores_gemma":[0.17964639,0.0011408253,0.00044859262,0.0011662479,0.0070390026,0.010129589,0.0039385767,0.0024870655,0.00055518775],"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":[0.007853044,0.001209237,0.20454468,0.0053338944,0.0011479045,0.0017357827,0.1014361,0.007049702,0.17096926,0.21546926,0.0025561373,0.28069502],"study_design_scores_gemma":[0.0007934304,0.0016741818,0.4872041,0.0009527718,0.0010065008,0.0047360025,0.01580549,0.029759487,0.047680497,0.39179844,0.018163418,0.00042563176],"about_ca_topic_score_codex":0.0014669389,"about_ca_topic_score_gemma":0.0011461311,"teacher_disagreement_score":0.020799499,"about_ca_system_score_codex":0.0007274408,"about_ca_system_score_gemma":0.0009969833,"threshold_uncertainty_score":0.1099996},"labels":[],"label_agreement":null},{"id":"W3006052429","doi":"","title":"Proceedings of the ISPIM Connecs Ottawa Conference","year":2019,"lang":"en","type":"article","venue":"Data Archiving and Networked Services (DANS)","topic":"Speech and dialogue systems","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":"Computer science","score_opus":0.011424948331886087,"score_gpt":0.20441847642663505,"score_spread":0.19299352809474896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3006052429","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":[0.035407286,0.022013301,0.010143081,0.046622183,0.04307817,0.0005120865,0.013011297,0.0021964428,0.8270162],"genre_scores_gemma":[0.023358664,0.0043946886,0.003014395,0.0006946838,0.000645177,0.000078112476,0.003223182,0.0003653108,0.96422577],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99816364,0.0002748089,0.000083460145,0.00021775503,0.00077841757,0.0004820034],"domain_scores_gemma":[0.99633104,0.00034785346,0.000062558436,0.0004465611,0.002000905,0.0008109678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0034199257,0.0011660224,0.0010039542,0.0018349199,0.0042152917,0.008379906,0.0017574873,0.002201883,0.1787032],"category_scores_gemma":[0.0030424832,0.0006471817,0.000801669,0.0022129726,0.0022707519,0.0020353002,0.0035422558,0.0022549157,0.056875516],"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":[0.0005875349,0.00018394904,0.0020734814,0.00027341576,0.000039711234,0.00032906796,0.0010089213,0.0010209115,0.0018381868,0.011089851,0.8820202,0.099534765],"study_design_scores_gemma":[0.000016930248,0.00003196495,0.0022171966,0.00012772452,0.00002650814,0.000039847357,0.0010368379,0.00049415196,0.0008561458,0.0011001772,0.9940256,0.000026789727],"about_ca_topic_score_codex":0.5777462,"about_ca_topic_score_gemma":0.7661654,"teacher_disagreement_score":0.5777462,"about_ca_system_score_codex":0.01279197,"about_ca_system_score_gemma":0.028335774,"threshold_uncertainty_score":0.84948105},"labels":[],"label_agreement":null},{"id":"W3034632137","doi":"10.71781/10273","title":"Representation learning for dialogue systems","year":2019,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Speech and dialogue systems","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":"Representation (politics); Cognitive science; Computer science; Artificial intelligence; Natural language processing; Psychology; Political science","score_opus":0.05531369063904014,"score_gpt":0.33908159487814016,"score_spread":0.28376790423910003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3034632137","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006131716,0.007932587,0.96265846,0.0022838009,0.00034423504,0.00009574303,0.00044739363,0.0015515159,0.018554416],"genre_scores_gemma":[0.55422693,0.010497559,0.39344534,0.0009654363,0.000921036,0.00058010203,0.0025560458,0.00055967557,0.036247756],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.998423,0.00068811985,0.00012191609,0.00035252282,0.00029421106,0.000120344834],"domain_scores_gemma":[0.9979517,0.0013352609,0.00011140207,0.00027513702,0.0002606078,0.00006591523],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017440395,0.000817736,0.0009376313,0.0009071978,0.0006720719,0.003123926,0.0013873257,0.001563779,0.013409381],"category_scores_gemma":[0.0071336376,0.00042885388,0.0012739847,0.0010471122,0.0011256165,0.004343073,0.0021644384,0.0023972725,0.002597625],"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":[0.00019701465,0.000085768945,0.0005892304,0.0008146934,0.00014651516,0.000130546,0.00050396373,0.123131715,0.00242819,0.52936053,0.015240268,0.32737157],"study_design_scores_gemma":[0.000034137884,0.000065261345,0.00027253522,0.00012046472,0.00004278666,0.000109403874,0.00010310244,0.54134226,0.0015880748,0.41420835,0.04207788,0.00003577609],"about_ca_topic_score_codex":0.004006528,"about_ca_topic_score_gemma":0.0036202902,"teacher_disagreement_score":0.013409381,"about_ca_system_score_codex":0.002015532,"about_ca_system_score_gemma":0.0012593649,"threshold_uncertainty_score":0.044858813},"labels":[],"label_agreement":null},{"id":"W3036227735","doi":"","title":"Sensory modalities and temporal processing.","year":2003,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Sensory system; Computer science; Artificial intelligence; Psychology; Cognitive psychology","score_opus":0.023073020242955183,"score_gpt":0.23289155582844528,"score_spread":0.2098185355854901,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3036227735","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":[0.18589644,0.17591563,0.23240024,0.010099747,0.004255347,0.0001661378,0.0031680844,0.0010427887,0.38705552],"genre_scores_gemma":[0.9168027,0.025403319,0.026087346,0.0009775087,0.001147699,0.00014203019,0.0007411208,0.00016941271,0.02852899],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99955255,0.00014039653,0.000030079338,0.00011985069,0.00008372147,0.00007333679],"domain_scores_gemma":[0.9983864,0.00090676424,0.00018902906,0.00017338178,0.0002546443,0.00008975948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000816367,0.0006646452,0.0003426008,0.0008688109,0.00048277952,0.0035983457,0.00055658707,0.0010968188,0.012166651],"category_scores_gemma":[0.0065972805,0.00042195583,0.00054901274,0.0006379587,0.0012902392,0.0039723376,0.0013922488,0.0010725816,0.0013700358],"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":[0.0019901632,0.00019750062,0.014871862,0.0020272608,0.00047977755,0.0024977385,0.004711831,0.0046440545,0.08630615,0.28846124,0.024125181,0.5696873],"study_design_scores_gemma":[0.00012225204,0.00064193516,0.09328458,0.0016912343,0.0006892807,0.0068330676,0.004880319,0.017917933,0.026950225,0.7756421,0.07109052,0.00025659768],"about_ca_topic_score_codex":0.0016748633,"about_ca_topic_score_gemma":0.0020285973,"teacher_disagreement_score":0.012166651,"about_ca_system_score_codex":0.00034391275,"about_ca_system_score_gemma":0.00051199255,"threshold_uncertainty_score":0.04070151},"labels":[],"label_agreement":null},{"id":"W3037158098","doi":"10.1609/aaai.v34i10.7127","title":"Modelling a Conversational Agent with Complex Emotional Intelligence","year":2020,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Speech and dialogue systems","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 à Montréal","funders":"","keywords":"Conversation; Popularity; Feeling; Dialog system; Task (project management); Natural (archaeology); Emotional intelligence; Computer science; Architecture; Psychology; Cognitive science; Human–computer interaction; Social psychology; Communication; World Wide Web; Dialog box; Engineering","score_opus":0.17617551579434185,"score_gpt":0.2822054156203577,"score_spread":0.10602989982601588,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3037158098","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.092783794,0.00056358066,0.86715716,0.0014066256,0.00014121261,0.00021684352,0.00024209083,0.0005260408,0.036962613],"genre_scores_gemma":[0.78897065,0.0005678852,0.18692844,0.00018971578,0.00009254548,0.00044369628,0.00022694597,0.00012024605,0.022459855],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99957687,0.00018315064,0.000025924486,0.00008885096,0.0000681396,0.00005702329],"domain_scores_gemma":[0.9994461,0.00031973544,0.00006526545,0.000032521668,0.00007138679,0.0000649473],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007555543,0.0006317746,0.00038907237,0.00040483562,0.00071158155,0.0025680803,0.0010816179,0.0014737402,0.0038850026],"category_scores_gemma":[0.0024032693,0.0005503128,0.0008258775,0.00026321298,0.0010772557,0.0017011653,0.0016816773,0.0010588377,0.0007442009],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00013241233,0.00010305784,0.0017054754,0.0001434953,0.00007481747,0.00065438374,0.0013173898,0.79800785,0.005841582,0.17675187,0.0014014577,0.013866192],"study_design_scores_gemma":[0.000015486943,0.000022793765,0.00011772472,0.000010603786,0.000013705722,0.00004611441,0.00007885144,0.97990626,0.00028300707,0.016900528,0.0025960447,0.000008936021],"about_ca_topic_score_codex":0.005699089,"about_ca_topic_score_gemma":0.0044072294,"teacher_disagreement_score":0.005699089,"about_ca_system_score_codex":0.00090212206,"about_ca_system_score_gemma":0.00086675165,"threshold_uncertainty_score":0.012996614},"labels":[],"label_agreement":null},{"id":"W3042578773","doi":"10.1145/3405755.3406161","title":"Let's Go There","year":2020,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Human–computer interaction; Identification (biology); Virtual reality; Teamwork; Feeling; Object (grammar); Augmented reality; Natural (archaeology); Tracking (education); Multimodal interaction; Virtual machine; Multimedia; Artificial intelligence; Psychology","score_opus":0.027949503825324625,"score_gpt":0.21675166194913456,"score_spread":0.18880215812380993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3042578773","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":[0.037414927,0.003942237,0.047461763,0.10930149,0.031619336,0.00044235273,0.0017962349,0.012743513,0.75527817],"genre_scores_gemma":[0.09456046,0.002309857,0.02352427,0.035603363,0.0017119788,0.00023942658,0.0009783834,0.0023623572,0.83870983],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995161,0.000109523025,0.000012518501,0.00007522771,0.00014199389,0.000144573],"domain_scores_gemma":[0.9988206,0.00013666585,0.000035067642,0.00009610015,0.00020185811,0.0007096047],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063908665,0.00095874013,0.00040925818,0.0005506258,0.0033203126,0.0039516254,0.0010484073,0.002185463,0.16660762],"category_scores_gemma":[0.002558234,0.0002805435,0.00073538715,0.00020347296,0.0014283281,0.0051558013,0.004336714,0.0033414378,0.066187866],"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":[0.00019586713,0.0002180811,0.0015426544,0.00022687358,0.000025305002,0.00068135955,0.006099228,0.00015742388,0.0044188513,0.01920257,0.81050044,0.15673143],"study_design_scores_gemma":[0.000011937455,0.00008513584,0.0005459167,0.00008392159,0.000011648164,0.00040873644,0.0029631467,0.00011561868,0.00063131703,0.0025735158,0.9925371,0.00003190932],"about_ca_topic_score_codex":0.0027197048,"about_ca_topic_score_gemma":0.007248685,"teacher_disagreement_score":0.16660762,"about_ca_system_score_codex":0.0007033572,"about_ca_system_score_gemma":0.0008641042,"threshold_uncertainty_score":0.557358},"labels":[],"label_agreement":null},{"id":"W3044198786","doi":"","title":"Haptic Augmentation of Audio and its Effects on Speech Perception","year":2020,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Speech and dialogue systems","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":"McGill University; Centre for Interdisciplinary Research in Music Media and Technology","funders":"","keywords":"Haptic technology; Perception; Computer science; Competence (human resources); Trustworthiness; Stimulus (psychology); Psychology; Speech recognition; Cognitive psychology; Social psychology; Simulation; Internet privacy","score_opus":0.01716700389108818,"score_gpt":0.23466451059498272,"score_spread":0.21749750670389453,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3044198786","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":[0.9700636,0.0021144827,0.016479144,0.00030739183,0.00029615426,0.00005040298,0.00024570202,0.00037882573,0.010064253],"genre_scores_gemma":[0.9927105,0.0005553948,0.0030720634,0.000058579124,0.00013559828,0.00002438697,0.000059650243,0.00006256052,0.0033212174],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998227,0.00005643989,0.000009439385,0.0000260777,0.00005135197,0.000034052464],"domain_scores_gemma":[0.9980305,0.001613372,0.00005599628,0.00012456227,0.00010027509,0.000075267344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002484072,0.00038986304,0.0003500364,0.00019014825,0.0001714471,0.00061512674,0.00026380012,0.00063170295,0.01743951],"category_scores_gemma":[0.0019020376,0.00016560081,0.00027868885,0.00016517266,0.0004638497,0.000585066,0.0005277311,0.0003451242,0.00072946755],"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":[0.007318578,0.00018642281,0.0003287249,0.0003315334,0.000019015451,0.00024236146,0.00013556522,0.0012912774,0.9427173,0.0005180968,0.00023313722,0.046677932],"study_design_scores_gemma":[0.0010721824,0.010533514,0.03800945,0.00019058464,0.00040517547,0.0025769153,0.0005720367,0.044831604,0.8878298,0.003058864,0.01078926,0.0001307059],"about_ca_topic_score_codex":0.00024964634,"about_ca_topic_score_gemma":0.00013280757,"teacher_disagreement_score":0.01743951,"about_ca_system_score_codex":0.00007215787,"about_ca_system_score_gemma":0.00011399241,"threshold_uncertainty_score":0.058340967},"labels":[],"label_agreement":null},{"id":"W3082898239","doi":"","title":"Can language help in the characterization of user behavior? Feature engineering experiments with Word.","year":2020,"lang":"en","type":"article","venue":"Software Engineering and Knowledge Engineering","topic":"Speech and dialogue systems","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":"Computer science; Word (group theory); Natural language processing; Feature (linguistics); Feature engineering; Characterization (materials science); Artificial intelligence; Linguistics","score_opus":0.008040751016663957,"score_gpt":0.20177740189257756,"score_spread":0.1937366508759136,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3082898239","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":[0.9900421,0.00022188293,0.0066282386,0.00018350763,0.00004423099,0.00011978297,0.00016904628,0.00019819022,0.002393069],"genre_scores_gemma":[0.99296784,0.00009457468,0.0050429367,0.00011890115,0.000015245626,0.00012398622,0.00015012006,0.00010383757,0.0013826294],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9955759,0.0029720373,0.00030975748,0.0005613878,0.000419898,0.0001609688],"domain_scores_gemma":[0.91231376,0.07944104,0.0023362455,0.0031263256,0.001657977,0.0011247015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0050703604,0.00051257096,0.0004035585,0.0005648502,0.00038294864,0.0019045396,0.0005522162,0.0010325998,0.0038189646],"category_scores_gemma":[0.06935865,0.00037296288,0.00027773585,0.00035336145,0.00071049633,0.003752038,0.00086625875,0.0009834048,0.0010854525],"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":[0.03585144,0.008690902,0.10688362,0.0023248983,0.0003417649,0.0007672694,0.04692393,0.004352037,0.249981,0.005256701,0.0051212334,0.53350514],"study_design_scores_gemma":[0.0028517984,0.051100917,0.5966911,0.0006801397,0.0016793838,0.0029237194,0.031021802,0.1308094,0.12390724,0.0350789,0.022569621,0.0006861106],"about_ca_topic_score_codex":0.0012233339,"about_ca_topic_score_gemma":0.00082853535,"teacher_disagreement_score":0.0050703604,"about_ca_system_score_codex":0.00023887196,"about_ca_system_score_gemma":0.0003262376,"threshold_uncertainty_score":0.026814938},"labels":[],"label_agreement":null},{"id":"W3087747045","doi":"10.48550/arxiv.2009.07616","title":"Parallel Interactive Networks for Multi-Domain Dialogue State Generation","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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":"Computer science; Context (archaeology); Encoder; Domain (mathematical analysis); State (computer science); Theoretical computer science; Artificial intelligence; Programming language","score_opus":0.13169550041580097,"score_gpt":0.2195769779747468,"score_spread":0.08788147755894582,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3087747045","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0077551166,0.00017864609,0.98890907,0.00009945239,0.000027014927,0.000054625238,0.00010665381,0.00077684113,0.002092514],"genre_scores_gemma":[0.7134314,0.00035920768,0.27928612,0.00013450443,0.00008087999,0.0004138499,0.00054112735,0.00032802945,0.0054249195],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990613,0.0003860765,0.000036459453,0.0002893734,0.00014573231,0.00008101538],"domain_scores_gemma":[0.9976999,0.0016946642,0.00015149776,0.00022948964,0.00015470177,0.00006964901],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013780922,0.0008003372,0.00042325628,0.0007287747,0.0005403764,0.0008165237,0.0014537782,0.0008652375,0.003543926],"category_scores_gemma":[0.00467448,0.00060130644,0.00071526685,0.0005947253,0.000846048,0.0021597,0.0016086646,0.0016642285,0.00077709893],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00031616923,0.000092224414,0.00095013046,0.00011713836,0.00006918549,0.00026327767,0.0005708547,0.8194448,0.0074338443,0.057654306,0.0017263177,0.11136177],"study_design_scores_gemma":[0.0000049523524,0.000014447996,0.00009074752,0.000004997772,0.00000831548,0.000026193322,0.000012571685,0.98340225,0.0010546691,0.014224118,0.001150031,0.0000067206915],"about_ca_topic_score_codex":0.006629399,"about_ca_topic_score_gemma":0.008599179,"teacher_disagreement_score":0.006629399,"about_ca_system_score_codex":0.0012768486,"about_ca_system_score_gemma":0.0008620116,"threshold_uncertainty_score":0.013181627},"labels":[],"label_agreement":null},{"id":"W3098826124","doi":"10.1109/taslp.2024.3426331","title":"Overview of the Ninth Dialog System Technology Challenge: DSTC9","year":2024,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Audio Speech and Language Processing","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":31,"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":"Dialog box; Computer science; Task (project management); Dialog system; Domain (mathematical analysis); Set (abstract data type); Human–computer interaction; Natural language processing; Artificial intelligence; Multimedia; World Wide Web; Programming language; Engineering","score_opus":0.020954514116271288,"score_gpt":0.27343512455951724,"score_spread":0.25248061044324593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3098826124","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":[0.04497108,0.06785179,0.5012492,0.06292696,0.036081634,0.01072802,0.1014316,0.0634568,0.11130295],"genre_scores_gemma":[0.06093185,0.017090052,0.3751514,0.00799458,0.0032683387,0.005946643,0.45923978,0.0058607142,0.06451669],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.97573394,0.007372221,0.0018740199,0.0029248393,0.010197103,0.0018979665],"domain_scores_gemma":[0.9620299,0.0074509457,0.000788357,0.0060235537,0.017978497,0.0057288124],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.030802825,0.0028982426,0.0029781726,0.0055159247,0.0039854203,0.0093469275,0.0060085715,0.0055757803,0.01565765],"category_scores_gemma":[0.03673344,0.0012510737,0.0021670896,0.004708015,0.0019863672,0.014357427,0.0112107815,0.009952625,0.019681932],"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":[0.00052353804,0.00083311216,0.0015765456,0.0026302824,0.00017034503,0.00017810294,0.0007799809,0.0051515526,0.008058876,0.013136392,0.68674964,0.28021172],"study_design_scores_gemma":[0.00013358891,0.0007101234,0.0028987224,0.0007498506,0.000084926265,0.000423705,0.00075271615,0.0209187,0.011470346,0.009456193,0.95223653,0.00016445653],"about_ca_topic_score_codex":0.030723482,"about_ca_topic_score_gemma":0.03364677,"teacher_disagreement_score":0.030802825,"about_ca_system_score_codex":0.007614073,"about_ca_system_score_gemma":0.019866647,"threshold_uncertainty_score":0.16290289},"labels":[],"label_agreement":null},{"id":"W3099289136","doi":"10.18653/v1/2020.findings-emnlp.142","title":"Neural Dialogue State Tracking with Temporally Expressive Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Ottawa","funders":"Beijing Advanced Innovation Center for Big Data and Brain Computing; Fundamental Research Funds for the Central Universities; State Key Laboratory of Software Development Environment; National Natural Science Foundation of China","keywords":"Computer science; Graphical model; Expressive power; State (computer science); Probabilistic logic; Tracking (education); Feature (linguistics); Artificial intelligence; Recurrent neural network; Artificial neural network; Natural language processing; Machine learning; Theoretical computer science; Algorithm","score_opus":0.02215996736713131,"score_gpt":0.20966751328886166,"score_spread":0.18750754592173036,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3099289136","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0723341,0.0013122051,0.9186788,0.00042935633,0.00014750485,0.00006284195,0.00070055446,0.0029026296,0.0034319186],"genre_scores_gemma":[0.88233525,0.00035054903,0.11126532,0.00020660115,0.00008192235,0.00013044893,0.0012427983,0.00012889806,0.0042582205],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991629,0.00025678036,0.000037918802,0.000362074,0.00010610289,0.00007425883],"domain_scores_gemma":[0.9987425,0.00077657274,0.00013261657,0.0001266484,0.00017544997,0.00004609968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013328773,0.00096712186,0.0006036711,0.0006835949,0.00042183482,0.00079035125,0.0011467432,0.00089586835,0.0012495392],"category_scores_gemma":[0.0044706715,0.0005037779,0.0005659749,0.0006344495,0.0004256754,0.0016683382,0.0012223858,0.0018564439,0.00051682227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00047891116,0.00019331397,0.0023232258,0.00010480771,0.00014586108,0.00012808297,0.00026816753,0.66199696,0.009469459,0.0076485933,0.0038052895,0.31343737],"study_design_scores_gemma":[0.0000041297158,0.000012467367,0.000154621,0.0000045503966,0.000008431523,0.000007690194,0.000006413166,0.9963605,0.00070738787,0.002402887,0.00032619396,0.0000047015264],"about_ca_topic_score_codex":0.010917888,"about_ca_topic_score_gemma":0.016336733,"teacher_disagreement_score":0.010917888,"about_ca_system_score_codex":0.00090983754,"about_ca_system_score_gemma":0.0006591612,"threshold_uncertainty_score":0.021708727},"labels":[],"label_agreement":null},{"id":"W3099489575","doi":"10.31513/linguistica.2020.v16nesp.a39406","title":"Deriving coordinate nouns with Merge and Principles of efficient computation","year":2020,"lang":"pt","type":"article","venue":"Revista Linguíʃtica","topic":"Speech and dialogue systems","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 à Montréal","funders":"","keywords":"Merge (version control); Noun; Associative property; Computer science; Computation; Natural language processing; Linguistics; Mathematics; Artificial intelligence; Pure mathematics; Algorithm; Philosophy; Information retrieval","score_opus":0.0363172215559239,"score_gpt":0.24771461970747147,"score_spread":0.21139739815154757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3099489575","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049887896,0.00028864804,0.92246914,0.00044609513,0.000046909536,0.00007537888,0.00008457192,0.0004144123,0.026286943],"genre_scores_gemma":[0.56313986,0.0004742829,0.42421386,0.00017633942,0.000091528644,0.00019021978,0.0002281695,0.0005665186,0.010919269],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9974112,0.00087921834,0.00022455,0.0005064771,0.0007639474,0.00021454293],"domain_scores_gemma":[0.99654007,0.0016318847,0.00033190794,0.00069537625,0.0006966095,0.000104168306],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022360564,0.0006304152,0.0006842929,0.002008442,0.0017177672,0.0048898607,0.0011661252,0.0010187353,0.0058581615],"category_scores_gemma":[0.009138227,0.0005810864,0.0019177354,0.0017821209,0.0055125277,0.010808641,0.0037953837,0.0017329488,0.001410413],"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":[0.000028928154,0.00001270076,0.0009024131,0.00006499296,0.000015864902,0.00016208642,0.0017607727,0.0019446283,0.0015322344,0.9688173,0.0004120389,0.024346115],"study_design_scores_gemma":[0.00001181893,0.000039981704,0.0006497756,0.00003403795,0.00002767242,0.0002991199,0.0006922834,0.01761166,0.005151659,0.96266145,0.012794267,0.000026220192],"about_ca_topic_score_codex":0.0019755089,"about_ca_topic_score_gemma":0.0020428882,"teacher_disagreement_score":0.0058581615,"about_ca_system_score_codex":0.0015641937,"about_ca_system_score_gemma":0.0013120838,"threshold_uncertainty_score":0.01959747},"labels":[],"label_agreement":null},{"id":"W3107721665","doi":"10.1075/ftl.10.06col","title":"On why people don’t say what they mean","year":2020,"lang":"en","type":"book-chapter","venue":"Figurative thought and language","topic":"Speech and dialogue systems","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 Alberta","funders":"","keywords":"Psychology; Mathematics","score_opus":0.014505159690129686,"score_gpt":0.23037148083341621,"score_spread":0.21586632114328652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3107721665","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":[0.1904999,0.014255537,0.061368275,0.058956787,0.0048399353,0.00006488734,0.00009607651,0.0004398768,0.66947865],"genre_scores_gemma":[0.89164245,0.003500003,0.005660741,0.008026974,0.00057002035,0.000058468802,0.000053920365,0.00021764709,0.09026966],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99886715,0.0007555625,0.000020802288,0.00009033164,0.0002186425,0.000047578913],"domain_scores_gemma":[0.9970426,0.002353615,0.00016456725,0.00012025411,0.00023801687,0.000080896636],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014316965,0.0002425881,0.00015319268,0.00023524211,0.0008093952,0.0020007142,0.00043276843,0.00076697324,0.003172336],"category_scores_gemma":[0.0037252624,0.00010805059,0.00011441876,0.00020334883,0.00525384,0.00268466,0.00079141953,0.0024189258,0.0012211796],"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":[0.00007806464,0.000058678354,0.0031551858,0.000381056,0.000018158578,0.0004842267,0.18347958,0.00031779235,0.005214168,0.62228537,0.06843358,0.11609408],"study_design_scores_gemma":[0.000021510732,0.00012647503,0.0067994096,0.0006317923,0.000019524074,0.0012927807,0.07204156,0.0021430182,0.0039848485,0.17684636,0.736038,0.00005464498],"about_ca_topic_score_codex":0.0005112533,"about_ca_topic_score_gemma":0.0008000588,"teacher_disagreement_score":0.003172336,"about_ca_system_score_codex":0.0006399906,"about_ca_system_score_gemma":0.00043583056,"threshold_uncertainty_score":0.010612547},"labels":[],"label_agreement":null},{"id":"W3115694136","doi":"10.4324/9781351266840-15","title":"When Dialogue Transforms a System","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Speech and dialogue systems","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","score_opus":0.019508490577080314,"score_gpt":0.20426932396555145,"score_spread":0.18476083338847113,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3115694136","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":[0.021753026,0.0037832642,0.036252115,0.0326503,0.0011568719,0.00013028918,0.00031199894,0.0005245504,0.9034376],"genre_scores_gemma":[0.8111707,0.0025486948,0.01545331,0.004980902,0.0003516937,0.00027935905,0.00038813063,0.00064789166,0.16417938],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9945697,0.0020707862,0.00013904125,0.0008932779,0.0013703584,0.0009567761],"domain_scores_gemma":[0.9967198,0.0012028656,0.00016276503,0.0007336706,0.0006768782,0.00050397875],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048299166,0.00050515553,0.00046741957,0.0011135653,0.010069408,0.018821476,0.0018305558,0.0041436492,0.011025794],"category_scores_gemma":[0.0061408645,0.0005240848,0.00048166967,0.0011617518,0.046121594,0.015888331,0.007814099,0.004129436,0.0020847844],"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":[0.000009427304,0.000004564619,0.0001855035,0.000036834103,0.0000029382797,0.00010260824,0.029840732,0.00012912593,0.00030550425,0.95930445,0.005608924,0.004469374],"study_design_scores_gemma":[0.000021357377,0.000019784016,0.00057436683,0.00018291685,0.000009884883,0.00018334892,0.02484171,0.0008676974,0.0005635385,0.36979273,0.6029072,0.000035357596],"about_ca_topic_score_codex":0.20615466,"about_ca_topic_score_gemma":0.19398756,"teacher_disagreement_score":0.20615466,"about_ca_system_score_codex":0.033148535,"about_ca_system_score_gemma":0.024353994,"threshold_uncertainty_score":0.40990937},"labels":[],"label_agreement":null},{"id":"W3116264359","doi":"10.18653/v1/2020.coling-main.40","title":"Speaker-change Aware CRF for Dialogue Act Classification","year":2020,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Polytechnique Montréal","funders":"","keywords":"Conditional random field; Utterance; Sequence labeling; Computer science; Task (project management); Layer (electronics); Sequence (biology); Code (set theory); Speech recognition; Natural language processing; Artificial intelligence; Artificial neural network; Field (mathematics); Transition (genetics); Set (abstract data type)","score_opus":0.17133978201337505,"score_gpt":0.2910911807624532,"score_spread":0.11975139874907817,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3116264359","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":[0.018768257,0.00070972246,0.9569037,0.00027092503,0.0002691389,0.00011959367,0.0015824522,0.018659664,0.0027166826],"genre_scores_gemma":[0.4638162,0.00037618398,0.5200762,0.00030689422,0.00024013745,0.0003976577,0.0073085264,0.0010215048,0.006456722],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99861586,0.00054359646,0.00006133359,0.0004902288,0.00018194079,0.00010713623],"domain_scores_gemma":[0.9963961,0.002229399,0.00015512486,0.0005785467,0.0005434374,0.00009741205],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002211886,0.001009057,0.0008876807,0.0008860455,0.0007436412,0.00053566566,0.0014439478,0.0010402615,0.0043645883],"category_scores_gemma":[0.0050054137,0.00046325006,0.0008498516,0.00086542254,0.00050200976,0.0014571478,0.0006612593,0.0026079784,0.0028533617],"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":[0.00093874236,0.00035783777,0.003918113,0.0003903878,0.00016310983,0.00028913605,0.0007198322,0.1156115,0.036878224,0.007121006,0.046061724,0.7875504],"study_design_scores_gemma":[0.000025218797,0.00006836363,0.0022917872,0.000031278087,0.000044063807,0.00010951558,0.00005217767,0.9699547,0.011252614,0.006927376,0.009189281,0.000053614174],"about_ca_topic_score_codex":0.007586785,"about_ca_topic_score_gemma":0.009744622,"teacher_disagreement_score":0.007586785,"about_ca_system_score_codex":0.0008449386,"about_ca_system_score_gemma":0.0009832291,"threshold_uncertainty_score":0.01508522},"labels":[],"label_agreement":null},{"id":"W31257076","doi":"10.1023/a:1023016804379","title":"The Effects of Multimedia Communication on Web-Based Negotiation","year":2003,"lang":"en","type":"article","venue":"Group Decision and Negotiation","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":60,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Negotiation; Computer science; Multimedia; Purchasing; Construct (python library); The Internet; Affect (linguistics); Computer-mediated communication; Psychology; World Wide Web; Communication; Business; Marketing","score_opus":0.007164708854747214,"score_gpt":0.22816209302183085,"score_spread":0.22099738416708364,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W31257076","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":[0.9564657,0.0011287208,0.00280101,0.00045955507,0.00013946678,0.000069101,0.0001017434,0.00010297993,0.038731813],"genre_scores_gemma":[0.99594104,0.00036595383,0.0011241351,0.0000742379,0.0001069814,0.000040989264,0.000044851455,0.000039225335,0.002262615],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99851733,0.000971633,0.00004227294,0.000074854834,0.00025998653,0.00013391781],"domain_scores_gemma":[0.93663764,0.05946795,0.0011424245,0.00077175605,0.0011670823,0.0008132271],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020264555,0.00041518788,0.00028944193,0.0010328951,0.0008543647,0.0023258885,0.0007198516,0.0013822233,0.01917716],"category_scores_gemma":[0.039222203,0.0003277021,0.00034516567,0.00079321954,0.00067750184,0.0026349726,0.00084793207,0.0007859056,0.00091648084],"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":[0.04983969,0.009472496,0.044915438,0.0021287603,0.00057337084,0.0033486253,0.013574607,0.05148279,0.12803033,0.05261729,0.008685126,0.63533145],"study_design_scores_gemma":[0.0057291305,0.015755065,0.3772415,0.0011045468,0.0033447868,0.0033374187,0.025251979,0.27682263,0.11642654,0.13442197,0.039835006,0.0007295048],"about_ca_topic_score_codex":0.0025471323,"about_ca_topic_score_gemma":0.0014510426,"teacher_disagreement_score":0.01917716,"about_ca_system_score_codex":0.0006620763,"about_ca_system_score_gemma":0.00040407202,"threshold_uncertainty_score":0.06415403},"labels":[],"label_agreement":null},{"id":"W3127371327","doi":"10.47756/aihc.y5i1.64","title":"The state of voice user interfaces in Latin America","year":2020,"lang":"en","type":"article","venue":"Avances en Interacción Humano-Computadora","topic":"Speech and dialogue systems","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":"Algoma University","funders":"","keywords":"State (computer science); Computer science; Latin Americans; Human–computer interaction; Speech recognition; Linguistics; Programming language; Philosophy","score_opus":0.01576619455509062,"score_gpt":0.2550863051775666,"score_spread":0.23932011062247596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3127371327","genre_codex":"review","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06155987,0.8595288,0.0015717322,0.014102554,0.00038451405,0.00004451723,0.0020663734,0.00017093246,0.060570702],"genre_scores_gemma":[0.42609394,0.5608611,0.0032469432,0.0030191531,0.000984055,0.00013211046,0.0022811878,0.00011036559,0.0032711737],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9943715,0.0014362553,0.0008919664,0.0010094348,0.0018544581,0.00043649104],"domain_scores_gemma":[0.9641168,0.015799597,0.007130488,0.00077050924,0.011497455,0.0006851476],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008566224,0.0005047678,0.0010523745,0.027782688,0.0011037813,0.010439134,0.0008505025,0.0010741032,0.0046682763],"category_scores_gemma":[0.022131464,0.000309004,0.0006848753,0.042763248,0.0023479045,0.0041481894,0.0019512892,0.00072473875,0.00058718777],"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":[0.00026343102,0.00010641049,0.079113245,0.018842846,0.00039828863,0.0006902002,0.007905523,0.0007091966,0.0027540186,0.023159329,0.01360523,0.8524523],"study_design_scores_gemma":[0.000050128783,0.00021722518,0.2952622,0.029901998,0.000840501,0.0018809584,0.024295555,0.00076146895,0.0023116942,0.0060374523,0.6383079,0.00013289122],"about_ca_topic_score_codex":0.019223796,"about_ca_topic_score_gemma":0.0140462965,"teacher_disagreement_score":0.027782688,"about_ca_system_score_codex":0.0051297317,"about_ca_system_score_gemma":0.0069549573,"threshold_uncertainty_score":0.045303106},"labels":[],"label_agreement":null},{"id":"W31450109","doi":"10.1016/b0-08-044854-2/00930-5","title":"Human Language Technology","year":2006,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Speech and dialogue systems","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 Toronto","funders":"","keywords":"Language technology; Computer science; Human language; Natural language processing; Universal Networking Language; Artificial intelligence; Natural language; Linguistics; Comprehension approach","score_opus":0.009937210980294544,"score_gpt":0.23144171908459357,"score_spread":0.22150450810429903,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W31450109","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":[0.0011433964,0.023094049,0.03223798,0.001713422,0.0013186674,0.000059693415,0.00052203523,0.0017877789,0.93812305],"genre_scores_gemma":[0.0069289873,0.010744657,0.0074247383,0.00038781622,0.00023293318,0.0000622802,0.00064653764,0.00042416257,0.9731479],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99974245,0.00004172493,0.000015055609,0.00006156508,0.00011756073,0.000021784637],"domain_scores_gemma":[0.9996971,0.00010148531,0.000009151648,0.0000833138,0.00007876528,0.000030136238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005178731,0.00097549823,0.00074044743,0.0010738141,0.0008993226,0.0034556556,0.0007804976,0.0011258792,0.14569472],"category_scores_gemma":[0.0009790242,0.0004982976,0.00033130107,0.0015427939,0.001033428,0.003737243,0.00147932,0.0014672825,0.11505258],"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":[0.000022741226,0.000040651077,0.00012910744,0.000347826,0.000009920515,0.000106499574,0.0006155232,0.00033089548,0.002171716,0.078288734,0.29419196,0.6237444],"study_design_scores_gemma":[0.0000037543455,0.000010865621,0.00024413457,0.00018384623,0.0000061106243,0.00020203156,0.00009518299,0.0003277817,0.0005868102,0.018282734,0.98005164,0.0000050919243],"about_ca_topic_score_codex":0.002477412,"about_ca_topic_score_gemma":0.0042582834,"teacher_disagreement_score":0.14569472,"about_ca_system_score_codex":0.00077197526,"about_ca_system_score_gemma":0.0009921356,"threshold_uncertainty_score":0.48739737},"labels":[],"label_agreement":null},{"id":"W3152030482","doi":"10.14740/jcgo232e","title":"E-mail Communication in the OB/GYN Office: Analysis of Patient E-mails to Their OB/GYN","year":2014,"lang":"en","type":"article","venue":"Journal of Clinical Gynecology and Obstetrics","topic":"Speech and dialogue systems","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":"Medicine; Family medicine","score_opus":0.03409554899580333,"score_gpt":0.3276034167653812,"score_spread":0.2935078677695778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3152030482","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":[0.99826556,0.000074328185,0.00012112603,0.0000619222,0.000005918202,0.00003892174,0.0006173316,0.000015174963,0.0007997338],"genre_scores_gemma":[0.9971685,0.0001065278,0.0003774697,0.000102574064,0.000019895833,0.00007026079,0.0012935132,0.000017960594,0.00084344554],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.996151,0.0018807785,0.0005896707,0.0002806892,0.00074683526,0.0003510089],"domain_scores_gemma":[0.9500114,0.03161303,0.009505872,0.0011446996,0.0058341306,0.0018908965],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024441225,0.00025510346,0.00036949344,0.0035802685,0.0006377891,0.0013681855,0.0004066508,0.000835892,0.00396824],"category_scores_gemma":[0.028599722,0.00018895738,0.00041525124,0.0028788191,0.0003743416,0.00068381446,0.0007349219,0.00056150847,0.0015144726],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0012266849,0.000404408,0.9743628,0.000113944945,0.00008206686,0.0003219479,0.004887673,0.00019638304,0.0012892614,0.000076613214,0.0006743528,0.01636385],"study_design_scores_gemma":[0.000016185384,0.00039887417,0.9910545,0.000033005555,0.000048276917,0.0003207453,0.0061283135,0.0006512904,0.00049591524,0.00003762658,0.00080015184,0.000015131291],"about_ca_topic_score_codex":0.0025173451,"about_ca_topic_score_gemma":0.0022789747,"teacher_disagreement_score":0.00396824,"about_ca_system_score_codex":0.00087507616,"about_ca_system_score_gemma":0.0009148765,"threshold_uncertainty_score":0.013275087},"labels":[],"label_agreement":null},{"id":"W3160295711","doi":"10.1145/3411763.3445008","title":"Conversational Voice User Interfaces: Connecting Engineering Fundamentals to Design Considerations","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Human–computer interaction; Modalities; Usability; Modality (human–computer interaction); Focus (optics); User interface","score_opus":0.043553914230154735,"score_gpt":0.25362958201343266,"score_spread":0.21007566778327794,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3160295711","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":[0.009997191,0.061301567,0.8122832,0.03447901,0.0016361005,0.00037335348,0.00013096046,0.0006580663,0.079140514],"genre_scores_gemma":[0.29553825,0.081670366,0.58778894,0.0065845964,0.003975309,0.001735241,0.0002603636,0.00069599145,0.021750925],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9934946,0.0028739409,0.00043032956,0.0005261688,0.0023824887,0.00029240383],"domain_scores_gemma":[0.98531777,0.010645556,0.0004592041,0.00077646005,0.0024811605,0.00031993628],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007982597,0.0013543848,0.000960373,0.0020964742,0.001123846,0.009739374,0.0031657142,0.004633818,0.005555552],"category_scores_gemma":[0.021110337,0.0016540807,0.000472478,0.00096707995,0.008162562,0.011481124,0.002258176,0.004547044,0.0024209623],"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":[0.00007435189,0.00014785059,0.0007727153,0.002894382,0.00004929493,0.00047358868,0.0037130418,0.011880963,0.007634031,0.80310357,0.0100155175,0.15924072],"study_design_scores_gemma":[0.000038391696,0.00036629508,0.00087804283,0.0020946248,0.000040382383,0.0014768783,0.002499542,0.033898924,0.0042474265,0.71844405,0.23589958,0.00011582702],"about_ca_topic_score_codex":0.0010908766,"about_ca_topic_score_gemma":0.0007860801,"teacher_disagreement_score":0.009739374,"about_ca_system_score_codex":0.0016385433,"about_ca_system_score_gemma":0.0015003735,"threshold_uncertainty_score":0.04221654},"labels":[],"label_agreement":null},{"id":"W3162737718","doi":"10.31234/osf.io/ez79s","title":"The Role of Prior Knowledge in Morphological Learning in an Artificial Second Language","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Morpheme; Linguistics; Morphology (biology); Language acquisition; Psychology; Natural language processing; Computer science; Artificial intelligence; Biology; Philosophy; Zoology","score_opus":0.021189898732811612,"score_gpt":0.2776086342228638,"score_spread":0.2564187354900522,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3162737718","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":[0.92772394,0.00031158404,0.059263553,0.00041719055,0.000019231986,0.000031491447,0.00004213057,0.00008710072,0.012103775],"genre_scores_gemma":[0.9864893,0.00018645868,0.011919292,0.000041877433,0.000007259593,0.000013901692,0.00004964619,0.000014117703,0.0012781053],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99943525,0.00022526376,0.00002423634,0.00015120665,0.00013249091,0.000031554548],"domain_scores_gemma":[0.9878588,0.009162568,0.00094792154,0.00093428727,0.00067394925,0.000422576],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016168838,0.00021877355,0.00026575173,0.0004318163,0.00039814343,0.0017009604,0.00045998045,0.00062807155,0.0025841529],"category_scores_gemma":[0.015612809,0.00033049568,0.000283542,0.00032635394,0.0013964343,0.0035466738,0.0010590734,0.0010764232,0.00029158266],"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":[0.0013095249,0.0013779951,0.13303655,0.0008324613,0.00027297487,0.0018932371,0.008928187,0.047504034,0.17561038,0.120575644,0.0011697325,0.5074893],"study_design_scores_gemma":[0.000121450044,0.0022928654,0.24919517,0.00037129736,0.00034771024,0.002874706,0.0033422308,0.26861292,0.08584239,0.37717456,0.0095482245,0.00027650272],"about_ca_topic_score_codex":0.0013820785,"about_ca_topic_score_gemma":0.0022239655,"teacher_disagreement_score":0.0025841529,"about_ca_system_score_codex":0.0004903846,"about_ca_system_score_gemma":0.000644005,"threshold_uncertainty_score":0.008644879},"labels":[],"label_agreement":null},{"id":"W3163442280","doi":"10.1145/3411764.3445640","title":"Tea, Earl Grey, Hot: Designing Speech Interactions from the Imagined Ideal of Star Trek","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Toronto","funders":"","keywords":"Star trek; Computer science; Ideal (ethics); Star (game theory); Context (archaeology); Human–computer interaction; Sociology; Media studies","score_opus":0.023449375253176464,"score_gpt":0.2532580115802622,"score_spread":0.2298086363270857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3163442280","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":[0.26923645,0.0032842648,0.6190477,0.009041893,0.0005982357,0.00047362805,0.00031416133,0.0035408447,0.094462834],"genre_scores_gemma":[0.7468301,0.0014469415,0.20961848,0.001985464,0.00007662603,0.0004227764,0.00035381067,0.0014356547,0.037830137],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99779874,0.0013938543,0.000052166328,0.00028045507,0.00035032723,0.00012435982],"domain_scores_gemma":[0.9965898,0.0026209718,0.00008104859,0.0001570076,0.00026591643,0.0002853528],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002461201,0.0006026593,0.0002724446,0.00037546974,0.002277322,0.004276657,0.00085034524,0.0013397429,0.008379003],"category_scores_gemma":[0.008644186,0.0005311865,0.00044656647,0.00021895238,0.002883138,0.0052598394,0.0021622323,0.0014475405,0.0022868447],"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":[0.0012039597,0.0005606458,0.007532442,0.002441042,0.00012944262,0.0021523454,0.30282256,0.01167384,0.1521004,0.13819145,0.05249368,0.32869813],"study_design_scores_gemma":[0.00021099085,0.0013751617,0.007670624,0.0008110111,0.00028338982,0.0034226219,0.11760404,0.08286618,0.0695763,0.086168446,0.62958986,0.00042145685],"about_ca_topic_score_codex":0.0022616757,"about_ca_topic_score_gemma":0.0045207646,"teacher_disagreement_score":0.008379003,"about_ca_system_score_codex":0.0009996393,"about_ca_system_score_gemma":0.0012912927,"threshold_uncertainty_score":0.028030574},"labels":[],"label_agreement":null},{"id":"W3165856572","doi":"10.1109/tla.2021.9468439","title":"Usability Questionnaires to Evaluate Voice User Interfaces","year":2021,"lang":"en","type":"article","venue":"IEEE Latin America Transactions","topic":"Speech and dialogue systems","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":"Algoma University","funders":"","keywords":"Usability; Human–computer interaction; Computer science; Usability lab; Popularity; Usability inspection; Usability goals; Dialog box; Heuristic evaluation; User interface; Quality (philosophy); Web usability; User experience design; Usability engineering; Multimedia; World Wide Web; Psychology","score_opus":0.0253875053828248,"score_gpt":0.28725321251088604,"score_spread":0.26186570712806123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3165856572","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":[0.44905904,0.1283719,0.18679954,0.0031690015,0.0017943319,0.12852426,0.02845239,0.0019993314,0.07183019],"genre_scores_gemma":[0.65293956,0.03071335,0.16605797,0.0027446554,0.00045018503,0.12561731,0.013484957,0.00038626746,0.007605652],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.94060373,0.02801826,0.01640757,0.0014019122,0.012813257,0.0007552259],"domain_scores_gemma":[0.88274944,0.07939779,0.010277033,0.002817102,0.02412471,0.0006339112],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.035272937,0.0012347614,0.0021278437,0.0070777857,0.00060141616,0.0015385639,0.0011017707,0.0009875407,0.0053450223],"category_scores_gemma":[0.09573032,0.0005055062,0.003490944,0.005740337,0.0007668885,0.0023528636,0.0014661086,0.0013091268,0.001159714],"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":[0.0018736871,0.0018582614,0.08805178,0.08182502,0.0035690207,0.0004583067,0.014651243,0.002234837,0.007355158,0.0057469225,0.03694267,0.7554332],"study_design_scores_gemma":[0.0016642301,0.015487366,0.43851987,0.049303144,0.0044339937,0.0026055144,0.0228025,0.007476188,0.011180004,0.009833043,0.4359106,0.0007835056],"about_ca_topic_score_codex":0.0009000285,"about_ca_topic_score_gemma":0.0013532883,"teacher_disagreement_score":0.035272937,"about_ca_system_score_codex":0.0017209732,"about_ca_system_score_gemma":0.001976994,"threshold_uncertainty_score":0.18654335},"labels":[],"label_agreement":null},{"id":"W3168942487","doi":"","title":"Individual differences in prosodic imitation","year":2021,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Speech and dialogue systems","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":"Imitation; Linguistics; Psychology; Cognitive psychology; Communication; Social psychology; Philosophy","score_opus":0.026548761906919526,"score_gpt":0.22869170892289747,"score_spread":0.20214294701597796,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3168942487","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":[0.9908319,0.0001919391,0.0008342801,0.00002981771,0.0000291046,0.000020354146,0.00026127652,0.000026733187,0.007774684],"genre_scores_gemma":[0.9971783,0.00006591838,0.00031212572,0.000020091837,0.000011211933,0.000021699792,0.00020038248,0.000034852615,0.0021554842],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999137,0.00025628885,0.00008279589,0.00024704996,0.00019945085,0.0000774537],"domain_scores_gemma":[0.9933078,0.0045678946,0.0006678063,0.0006342054,0.00048866513,0.0003334856],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011484628,0.00025813092,0.00040654323,0.0005773379,0.00019309936,0.0010963901,0.00022051783,0.0006269902,0.005567654],"category_scores_gemma":[0.013985349,0.00030073733,0.00021915622,0.00037929649,0.0003144002,0.0004785759,0.00071105955,0.00048266267,0.0010634718],"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":[0.0064096674,0.00027158062,0.32699546,0.0004364721,0.0012852385,0.0014658553,0.013918747,0.00427683,0.5073425,0.0024070386,0.0019177155,0.13327289],"study_design_scores_gemma":[0.000020165133,0.00022513936,0.9912367,0.000013418075,0.000098232274,0.0007707826,0.0005695282,0.0015111258,0.0043797432,0.0004641999,0.0006789643,0.00003190875],"about_ca_topic_score_codex":0.00065367785,"about_ca_topic_score_gemma":0.0008592735,"teacher_disagreement_score":0.005567654,"about_ca_system_score_codex":0.00011964329,"about_ca_system_score_gemma":0.00011080522,"threshold_uncertainty_score":0.018625617},"labels":[],"label_agreement":null},{"id":"W3175609992","doi":"10.21428/594757db.ae6ae665","title":"Direct Answer Threshold Optimization in Dialogue Systems","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"National Bank of Canada","funders":"","keywords":"Computer science; Set (abstract data type); Point (geometry); Focus (optics); Task (project management); Information retrieval; Machine learning; Artificial intelligence; Mathematics","score_opus":0.016972104828563536,"score_gpt":0.22541077166381412,"score_spread":0.20843866683525059,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3175609992","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.049337994,0.0026188795,0.9394589,0.0005709131,0.000102268095,0.0001966074,0.0004268471,0.005138027,0.0021496767],"genre_scores_gemma":[0.6453132,0.00042505816,0.34765795,0.00045175225,0.00020892476,0.00035776937,0.0015025616,0.0006053937,0.0034774467],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99436545,0.0020120637,0.00051598303,0.0013531114,0.0012756517,0.0004777357],"domain_scores_gemma":[0.9886805,0.008531219,0.0006169448,0.0004664847,0.0013327901,0.00037200697],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044256398,0.0016147469,0.0025627569,0.0024001515,0.0009060666,0.0023750858,0.0017473367,0.002343828,0.0029352254],"category_scores_gemma":[0.020065961,0.0006733416,0.0009792504,0.0012488461,0.0011468198,0.0024325484,0.0020810955,0.0022111286,0.00118183],"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":[0.0011267139,0.00050069066,0.0057376525,0.00087348896,0.00016478902,0.0002621807,0.0008760409,0.37513226,0.02242192,0.011393705,0.010807909,0.57070273],"study_design_scores_gemma":[0.000040362684,0.000099594574,0.00071599515,0.000028390354,0.000023362134,0.00006849267,0.000090755,0.9835265,0.004220878,0.00969884,0.0014633593,0.000023436467],"about_ca_topic_score_codex":0.0043198657,"about_ca_topic_score_gemma":0.0037530612,"teacher_disagreement_score":0.0044256398,"about_ca_system_score_codex":0.0013807695,"about_ca_system_score_gemma":0.0018351427,"threshold_uncertainty_score":0.023405313},"labels":[],"label_agreement":null},{"id":"W3185711006","doi":"10.1177/17470218211037117","title":"Comparing individual and collective management of referential choices in dialogue","year":2021,"lang":"en","type":"article","venue":"Quarterly Journal of Experimental Psychology","topic":"Speech and dialogue systems","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":"Université Laval","funders":"Fonds de Recherche du Québec - Santé; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Referent; Pronoun; Psychology; Character (mathematics); Noun phrase; Linguistics; Context (archaeology); Contrast (vision); Noun; Phrase; Control (management); Cognitive psychology; Communication; Social psychology; Computer science; Artificial intelligence; Mathematics","score_opus":0.0463916158556266,"score_gpt":0.3276392927698453,"score_spread":0.2812476769142187,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3185711006","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":[0.9944988,0.00016199365,0.0024224487,0.00005440009,0.0000047758926,0.000024431203,0.0000114707855,0.000016598357,0.0028052405],"genre_scores_gemma":[0.9984126,0.00004458581,0.0012151714,0.000011925303,0.0000038120393,0.000025395315,0.000019446506,0.000007965136,0.0002591167],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99061406,0.0061201043,0.00044132714,0.0011295145,0.0012967646,0.0003983119],"domain_scores_gemma":[0.96459144,0.023899019,0.0053403997,0.0027328832,0.0018015266,0.0016347507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008526257,0.0002825872,0.00049766205,0.0013916754,0.0009467008,0.00301468,0.00052106706,0.0008821733,0.0011156162],"category_scores_gemma":[0.040242437,0.00036349913,0.00026460414,0.00054672133,0.002132902,0.0024647897,0.0025108496,0.0007376893,0.00015699703],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00302254,0.00085415307,0.36576334,0.00085008657,0.000558658,0.00077611697,0.3189979,0.0026846826,0.09711211,0.009983009,0.00043037417,0.19896702],"study_design_scores_gemma":[0.0002220768,0.0026242877,0.8244544,0.00023056222,0.00033484533,0.0008469434,0.11553975,0.010871377,0.015483357,0.02112775,0.0079686,0.0002959893],"about_ca_topic_score_codex":0.0006735181,"about_ca_topic_score_gemma":0.0010115076,"teacher_disagreement_score":0.008526257,"about_ca_system_score_codex":0.0005673544,"about_ca_system_score_gemma":0.00042394965,"threshold_uncertainty_score":0.04509169},"labels":[],"label_agreement":null},{"id":"W3188372498","doi":"10.24963/ijcai.2021/538","title":"A Streaming End-to-End Framework For Spoken Language Understanding","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Keyword spotting; End-to-end principle; Connectionism; Latency (audio); Speech recognition; Process (computing); Spoken language; Spotting; Task (project management); Language model; Natural language processing; Artificial intelligence; Artificial neural network","score_opus":0.04723888852149595,"score_gpt":0.2930662013247493,"score_spread":0.24582731280325337,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3188372498","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":[0.005558912,0.00027103012,0.9883365,0.00008167507,0.000043058622,0.00008518074,0.00025040263,0.0045504766,0.00082281715],"genre_scores_gemma":[0.2906505,0.00041532892,0.69971365,0.00023176576,0.00010846753,0.0003453438,0.0022285774,0.0004774178,0.0058288802],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996309,0.00008335167,0.000022207309,0.00013675129,0.00009151536,0.00003524831],"domain_scores_gemma":[0.9994523,0.00021354343,0.000031393687,0.000070163616,0.00019222312,0.00004050919],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00073896913,0.0012208045,0.0006518684,0.00048330793,0.00032718387,0.00073844194,0.0015184603,0.0010408945,0.0038205325],"category_scores_gemma":[0.0016374516,0.000373401,0.0005470239,0.0003526732,0.00042676812,0.0017902256,0.00094630354,0.0017524327,0.0016663872],"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":[0.0006529445,0.00040238965,0.0014170723,0.00036888078,0.00015769758,0.0005770995,0.00052010955,0.26658097,0.056875903,0.013601536,0.013432709,0.6454127],"study_design_scores_gemma":[0.000011874427,0.00006806549,0.00015696962,0.000007774469,0.000012197223,0.00006472798,0.00003120569,0.98767716,0.0040405043,0.005642032,0.0022764152,0.000011066157],"about_ca_topic_score_codex":0.007038686,"about_ca_topic_score_gemma":0.01131152,"teacher_disagreement_score":0.007038686,"about_ca_system_score_codex":0.0005052501,"about_ca_system_score_gemma":0.0009793548,"threshold_uncertainty_score":0.013995409},"labels":[],"label_agreement":null},{"id":"W3201268321","doi":"10.1145/3459637.3482182","title":"Simulated Annealing for Emotional Dialogue Systems","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Compute Canada","keywords":"Simulated annealing; Coherence (philosophical gambling strategy); Task (project management); Emotion recognition; Quality (philosophy); Text generation","score_opus":0.028166814784069613,"score_gpt":0.2566235628162115,"score_spread":0.2284567480321419,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3201268321","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020126939,0.00076669396,0.9727874,0.00036833138,0.00010023668,0.00009079955,0.00007765512,0.001089137,0.0045927996],"genre_scores_gemma":[0.62527066,0.00039401863,0.36703792,0.0003793702,0.000091426344,0.0006760674,0.0003353284,0.0005115982,0.0053035794],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991762,0.00048632902,0.000038086895,0.00015317988,0.0000939461,0.00005221583],"domain_scores_gemma":[0.9982975,0.0013209819,0.00007182283,0.0001184906,0.00013464494,0.000056562974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014377951,0.00097373436,0.0009864208,0.0004648294,0.0006188839,0.0009100391,0.00095937384,0.0013584723,0.004205875],"category_scores_gemma":[0.0053935824,0.0006323309,0.0009092011,0.00028803525,0.0009817539,0.00087203225,0.0012252348,0.0016761938,0.00078190985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000078327575,0.000036623307,0.00035743814,0.00009673585,0.000050048387,0.00005307126,0.00012789253,0.9600842,0.0021986256,0.0136985155,0.0011235443,0.02209491],"study_design_scores_gemma":[0.000010640748,0.000013449126,0.000040110266,0.000005633625,0.0000043734185,0.0000064774144,0.000006854574,0.9910323,0.00037238045,0.0077942424,0.000709599,0.0000039857205],"about_ca_topic_score_codex":0.0026284694,"about_ca_topic_score_gemma":0.0034242545,"teacher_disagreement_score":0.004205875,"about_ca_system_score_codex":0.0010727369,"about_ca_system_score_gemma":0.00073733437,"threshold_uncertainty_score":0.014070094},"labels":[],"label_agreement":null},{"id":"W3202064793","doi":"10.1145/3447527.3474875","title":"Low-level Voice and Hand-Tracking Interaction Actions: Explorations with Let's Go There","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Human–computer interaction; Computer science; Tracking (education); Social relation; Selection (genetic algorithm); Multimodal interaction; Artificial intelligence; Psychology","score_opus":0.0776726390601548,"score_gpt":0.2815754859868818,"score_spread":0.203902846926727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3202064793","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34156212,0.0025118145,0.6095371,0.0021949916,0.00013200585,0.00056447415,0.0002832543,0.0044487636,0.038765498],"genre_scores_gemma":[0.6905087,0.0010864711,0.29595175,0.0005591432,0.000038093305,0.00036251725,0.00030071413,0.0005474756,0.010645028],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99760723,0.0014609582,0.00007845271,0.00024331869,0.00038716558,0.0002227762],"domain_scores_gemma":[0.99655724,0.0028239284,0.00006200972,0.00022435411,0.00017047496,0.00016207898],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002966853,0.00092730945,0.00059234403,0.00069630134,0.0009094298,0.0028306716,0.0013930923,0.0016618756,0.0049959044],"category_scores_gemma":[0.0043579834,0.0004723938,0.0008483749,0.00031065315,0.0027690951,0.0035835446,0.002918589,0.0012374182,0.0008948364],"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":[0.0014986537,0.0011950874,0.013691338,0.0030364878,0.00018427332,0.0034939847,0.14409865,0.017505782,0.18093365,0.045762144,0.009512469,0.5790875],"study_design_scores_gemma":[0.00041232706,0.005420007,0.04747337,0.0026998203,0.0005206445,0.012116713,0.07708988,0.32510278,0.122925855,0.064401925,0.3409715,0.0008652292],"about_ca_topic_score_codex":0.0024193216,"about_ca_topic_score_gemma":0.0056071617,"teacher_disagreement_score":0.0049959044,"about_ca_system_score_codex":0.0006343479,"about_ca_system_score_gemma":0.0006957391,"threshold_uncertainty_score":0.016712964},"labels":[],"label_agreement":null},{"id":"W3216524652","doi":"","title":"Using connector words: Theoretical, empirical, and practical considerations.","year":2019,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Alberta; Université de Saint-Boniface","funders":"","keywords":"Computer science; Epistemology; Psychology; Philosophy","score_opus":0.07441190181857445,"score_gpt":0.3501345211783486,"score_spread":0.27572261935977416,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216524652","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":[0.13143381,0.012780882,0.39494434,0.043074287,0.0011642325,0.0007483501,0.0016079575,0.0011474115,0.41309875],"genre_scores_gemma":[0.9124354,0.0036476254,0.07027262,0.0021003229,0.00041153337,0.000511728,0.0006968403,0.0005046056,0.009419478],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.97187513,0.021469023,0.0012825478,0.0014378738,0.0029558397,0.0009796353],"domain_scores_gemma":[0.87865895,0.09818656,0.003040635,0.009330253,0.009256364,0.0015272659],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018345406,0.0014830931,0.00077324046,0.003934058,0.0029907806,0.01741446,0.0032893957,0.0045743613,0.03948898],"category_scores_gemma":[0.13760547,0.0010998438,0.0005466161,0.005974808,0.010133573,0.06166443,0.006372033,0.00417453,0.007691319],"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":[0.00022416064,0.00012932521,0.0090994565,0.00061925856,0.00003751613,0.00024596558,0.010973423,0.00042320616,0.0014808937,0.9024948,0.007469467,0.06680254],"study_design_scores_gemma":[0.00007594981,0.00015143567,0.0051072533,0.0010889211,0.00010268974,0.0017321393,0.032776877,0.006351263,0.0047263033,0.887581,0.0601916,0.00011448529],"about_ca_topic_score_codex":0.0022711796,"about_ca_topic_score_gemma":0.0033051653,"teacher_disagreement_score":0.03948898,"about_ca_system_score_codex":0.0017368261,"about_ca_system_score_gemma":0.0032796005,"threshold_uncertainty_score":0.13210374},"labels":[],"label_agreement":null},{"id":"W3216898555","doi":"","title":"Korero: Facilitating Complex Referencing of Visual Materials in Asynchronous Discussion Interface","year":2018,"lang":"en","type":"article","venue":"Conference on Computer Supported Cooperative Work","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Referent; Computer science; Asynchronous communication; Interface (matter); Context (archaeology); Human–computer interaction; User interface; Multimedia; Linguistics","score_opus":0.04647666313927546,"score_gpt":0.30716294411871925,"score_spread":0.2606862809794438,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3216898555","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28697744,0.0013396401,0.65586907,0.000489799,0.00034775268,0.001955194,0.0010419212,0.0390978,0.012881399],"genre_scores_gemma":[0.4427569,0.00057462713,0.53706825,0.0005506859,0.00016704839,0.0018296435,0.0012258554,0.0019065595,0.013920482],"study_design_codex":"design_other","study_design_gemma":"qualitative","domain_scores_codex":[0.9970476,0.0015536041,0.00026873496,0.00048798957,0.00047603002,0.00016606977],"domain_scores_gemma":[0.9806964,0.015041486,0.0008868445,0.0018715702,0.0008874604,0.00061632105],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0045976616,0.0014441059,0.0006727079,0.0010021166,0.00047545985,0.0017643571,0.0020788219,0.0017440177,0.011150452],"category_scores_gemma":[0.023470985,0.00058565516,0.0007475413,0.00040784362,0.0005273849,0.0051847324,0.0044837617,0.00078308163,0.0022723414],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0050124135,0.0017100261,0.005554915,0.0067294715,0.00023442008,0.0021766257,0.031771325,0.0033265187,0.27453953,0.011844655,0.022760611,0.6343396],"study_design_scores_gemma":[0.0050702896,0.014112568,0.054395128,0.0031342008,0.0011818884,0.0088022845,0.019410187,0.10453912,0.19005422,0.032352503,0.56525487,0.0016928703],"about_ca_topic_score_codex":0.0002708314,"about_ca_topic_score_gemma":0.00041503043,"teacher_disagreement_score":0.011150452,"about_ca_system_score_codex":0.0002511384,"about_ca_system_score_gemma":0.0004384832,"threshold_uncertainty_score":0.037301958},"labels":[],"label_agreement":null},{"id":"W34011602","doi":"10.21437/interspeech.2006-40","title":"Measuring the acceptable word error rate of machine-generated webcast transcripts","year":2006,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Dalhousie University; University of Toronto","funders":"","keywords":"Webcast; Computer science; Broadcasting (networking); Word (group theory); Metadata; The Internet; Speech recognition; Information retrieval; World Wide Web; Linguistics","score_opus":0.03675406798063769,"score_gpt":0.22554743883744738,"score_spread":0.1887933708568097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W34011602","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":[0.8031977,0.00024779278,0.1900976,0.00015662608,0.00014258151,0.0005341968,0.0011821961,0.0023203786,0.0021208844],"genre_scores_gemma":[0.8615445,0.00017146327,0.13359828,0.00007651999,0.000053883323,0.00091247755,0.0020097003,0.00051126926,0.0011218367],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9871321,0.0054286327,0.0023313037,0.0019786642,0.002756991,0.0003723779],"domain_scores_gemma":[0.91039973,0.06625105,0.0036535317,0.0052400245,0.013949858,0.0005058265],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008477107,0.0009221498,0.0008144427,0.0016590386,0.00056743226,0.0013641748,0.0008149776,0.0014952694,0.001519399],"category_scores_gemma":[0.086159945,0.00032907585,0.000560226,0.0011489666,0.00075093517,0.0012927584,0.0010245865,0.0007972186,0.0014859453],"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":[0.0049717412,0.0009081688,0.06506085,0.0016182704,0.00042211582,0.00143592,0.010616987,0.031360686,0.53408384,0.002267197,0.00273705,0.34451723],"study_design_scores_gemma":[0.00026932612,0.005530937,0.14156286,0.0001494636,0.0003797082,0.002805922,0.0034187953,0.2058646,0.63030595,0.003326376,0.0059560426,0.00043011762],"about_ca_topic_score_codex":0.00090926385,"about_ca_topic_score_gemma":0.00083320687,"teacher_disagreement_score":0.008477107,"about_ca_system_score_codex":0.0004178026,"about_ca_system_score_gemma":0.0004273684,"threshold_uncertainty_score":0.044831753},"labels":[],"label_agreement":null},{"id":"W34538624","doi":"10.1016/j.encep.2021.04.004","title":"Reconfiguration of speech recognizers through layered-grammar structure to provide ease of navigation and recognition accuracy in speech-web.","year":2001,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Computer science; Speech recognition; Natural language processing; Grammar; Artificial intelligence; Linguistics","score_opus":0.027514266495692136,"score_gpt":0.26715399021303415,"score_spread":0.23963972371734202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W34538624","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":[0.8355784,0.00028346071,0.14807297,0.00036478843,0.00018072414,0.0002906819,0.0004620792,0.010962775,0.0038040262],"genre_scores_gemma":[0.9219872,0.000087385095,0.07454791,0.00012613683,0.000019022847,0.00012311433,0.00040191604,0.00027352007,0.002433976],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99939406,0.00019303139,0.00006213715,0.00017216065,0.000094342104,0.000084183084],"domain_scores_gemma":[0.99648094,0.0016748187,0.00025476134,0.0006957516,0.0006601878,0.0002333832],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009832578,0.0004444456,0.0002521877,0.00033222747,0.00014806884,0.00090377696,0.00061798585,0.0005103861,0.005052617],"category_scores_gemma":[0.008981956,0.00021517766,0.0004108321,0.00015014446,0.00031163977,0.0014813527,0.00057429716,0.00052083365,0.0020300807],"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":[0.0014842261,0.0009426553,0.019930713,0.00027393253,0.000098896184,0.0005831687,0.0010830853,0.008086946,0.6008772,0.0017120522,0.0025465556,0.3623805],"study_design_scores_gemma":[0.00033119385,0.003015425,0.09423061,0.0001223112,0.00052232697,0.0026103472,0.0008136672,0.23007283,0.6465086,0.0069587226,0.014517376,0.00029667435],"about_ca_topic_score_codex":0.0030187268,"about_ca_topic_score_gemma":0.0038288734,"teacher_disagreement_score":0.005052617,"about_ca_system_score_codex":0.00032695217,"about_ca_system_score_gemma":0.00056466775,"threshold_uncertainty_score":0.016902745},"labels":[],"label_agreement":null},{"id":"W4200087558","doi":"10.1145/3461615.3485416","title":"Clustering and Multimodal Analysis of Participants in Task-Based Discussions","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of the Fraser Valley; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Task (project management); Cluster analysis; Computer science; Outlier; Cluster (spacecraft); Task analysis; Artificial intelligence; Natural language processing","score_opus":0.026538429492589867,"score_gpt":0.2820455191544124,"score_spread":0.2555070896618225,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4200087558","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":[0.93681693,0.0002453305,0.057193164,0.00019813278,0.00004385695,0.0002716693,0.0019194855,0.0007219947,0.0025893478],"genre_scores_gemma":[0.9695115,0.00007789633,0.026017565,0.000026270076,0.000039451777,0.00032441705,0.0022210025,0.000092150214,0.0016897093],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99720323,0.0009165929,0.00016375688,0.0006174335,0.00078680477,0.0003121716],"domain_scores_gemma":[0.99395293,0.0024485562,0.00078222575,0.00051565043,0.0018543476,0.0004462238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018659888,0.0005331224,0.0006011277,0.0037193052,0.00084099075,0.0011498503,0.0005676324,0.00069574383,0.0023068038],"category_scores_gemma":[0.009935016,0.00014652597,0.0005614961,0.0021203707,0.0003929935,0.0006182545,0.0013171436,0.0005041456,0.0012320546],"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":[0.0042918012,0.0007998939,0.23630124,0.0010116097,0.0004582977,0.0012031615,0.042738322,0.008368675,0.27362722,0.0033400638,0.007898665,0.41996115],"study_design_scores_gemma":[0.000089370995,0.0012221411,0.71652853,0.00020062407,0.00028857923,0.0013209671,0.035506587,0.15342245,0.06331844,0.009193057,0.018555142,0.00035414062],"about_ca_topic_score_codex":0.0024946884,"about_ca_topic_score_gemma":0.0030854912,"teacher_disagreement_score":0.0037193052,"about_ca_system_score_codex":0.00044081802,"about_ca_system_score_gemma":0.000488799,"threshold_uncertainty_score":0.009868383},"labels":[],"label_agreement":null},{"id":"W4205435296","doi":"10.7557/5.5951","title":"Wikispeech","year":2021,"lang":"en","type":"article","venue":"Septentrio Conference Series","topic":"Speech and dialogue systems","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":"Active listening; License; Reading (process); Computer science; Quarter (Canadian coin); World Wide Web; Quality (philosophy); Population; Multimedia; Linguistics; Psychology; Sociology; Communication; History","score_opus":0.02035980886674459,"score_gpt":0.22685609655353436,"score_spread":0.20649628768678976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205435296","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0028253675,0.0019808034,0.09430734,0.0022163454,0.0046445853,0.0010040655,0.2189857,0.3686535,0.30538234],"genre_scores_gemma":[0.011562733,0.0019349313,0.06843434,0.0012526368,0.0009720542,0.0014816121,0.49526596,0.11033212,0.30876356],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9965249,0.00054141396,0.00036666213,0.00073422946,0.0014796613,0.00035303528],"domain_scores_gemma":[0.98748547,0.0019443765,0.0005019388,0.0035357121,0.0041181357,0.0024143835],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032391623,0.0024857149,0.0018149138,0.006665713,0.0029011653,0.011341615,0.004716211,0.0018465855,0.2687805],"category_scores_gemma":[0.018389447,0.0011886152,0.0014142442,0.005993315,0.00091488386,0.014205429,0.010202305,0.0031999496,0.3674207],"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":[0.00019941117,0.000048597416,0.00020369978,0.0006547195,0.0000339353,0.000081313745,0.00023423263,0.00017250735,0.0008468527,0.0062110797,0.9222488,0.06906479],"study_design_scores_gemma":[0.00002622491,0.000018170349,0.00030268356,0.000068673464,0.000010259152,0.00008876418,0.00008843322,0.00041833715,0.001036449,0.0043635094,0.99353665,0.000041761985],"about_ca_topic_score_codex":0.0045910473,"about_ca_topic_score_gemma":0.0060138227,"teacher_disagreement_score":0.2687805,"about_ca_system_score_codex":0.00123623,"about_ca_system_score_gemma":0.0052030333,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4210752374","doi":"10.1017/cbo9781139087636.004","title":"Research methodology","year":2018,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Speech and dialogue systems","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 Toronto","funders":"","keywords":"Computer science; Scripting language; Linguistics; Phonetics; Focus (optics); Field (mathematics); Second-language acquisition; Cognitive science; Psychology; Programming language","score_opus":0.17537061125236691,"score_gpt":0.3059471377791526,"score_spread":0.1305765265267857,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210752374","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":[0.02469843,0.009424936,0.15638985,0.008000098,0.0067414655,0.18796213,0.06728284,0.0019516827,0.5375486],"genre_scores_gemma":[0.063306145,0.008320534,0.2152183,0.010539079,0.001146163,0.37571245,0.037945427,0.0010868877,0.28672507],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98907685,0.0036827892,0.0012251654,0.0027175653,0.002449942,0.00084763137],"domain_scores_gemma":[0.98504585,0.0032401958,0.0007466543,0.0025078894,0.007551941,0.00090751983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.016382204,0.001316823,0.0015980053,0.0053002806,0.0037590866,0.00618113,0.0038691096,0.0028952758,0.24277785],"category_scores_gemma":[0.027347906,0.0010720427,0.0014473895,0.0062874258,0.001910056,0.0028779458,0.003825692,0.003094922,0.078248754],"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":[0.0014748633,0.0011971642,0.0069210776,0.008074539,0.00012938883,0.000855038,0.012481506,0.0013222247,0.0022922596,0.13858895,0.2934415,0.53322136],"study_design_scores_gemma":[0.00029771865,0.0005871573,0.004208592,0.0035919035,0.000079895704,0.00029176095,0.007073539,0.0004883775,0.0011071847,0.021757416,0.9604618,0.000054622105],"about_ca_topic_score_codex":0.0067407363,"about_ca_topic_score_gemma":0.008160578,"teacher_disagreement_score":0.24277785,"about_ca_system_score_codex":0.0057746205,"about_ca_system_score_gemma":0.017782815,"threshold_uncertainty_score":0.81217283},"labels":[],"label_agreement":null},{"id":"W4210849719","doi":"10.1007/978-3-540-49127-9","title":"Springer Handbook of Speech Processing","year":2007,"lang":"en","type":"book","venue":"Springer handbooks","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":716,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Computer science; Speech recognition; Psychology; Linguistics; Philosophy","score_opus":0.021044586203367393,"score_gpt":0.24223657330604853,"score_spread":0.22119198710268115,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4210849719","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":[0.0011926634,0.16712885,0.36596262,0.0026971304,0.0146317175,0.00033402053,0.004446802,0.016650913,0.4269553],"genre_scores_gemma":[0.007491615,0.09447604,0.099622436,0.0013269488,0.004816317,0.00045974186,0.00638429,0.0035910655,0.7818315],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99919504,0.000102480386,0.00006560665,0.000114527,0.0004846346,0.000037681086],"domain_scores_gemma":[0.9986946,0.00044928223,0.000047356007,0.00020969388,0.0005281335,0.00007097008],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007397668,0.0022127482,0.0023590242,0.0029623245,0.0006722628,0.0033801107,0.0018950657,0.0015763186,0.11660438],"category_scores_gemma":[0.002394986,0.0008110084,0.00060173526,0.004177909,0.00064454164,0.0029249971,0.0015478168,0.002149579,0.15038614],"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":[0.000026889908,0.000031851894,0.000045774264,0.0006518626,0.000021138077,0.00006633404,0.000107400854,0.001094978,0.0016169583,0.012465585,0.37544477,0.6084265],"study_design_scores_gemma":[0.0000066683497,0.000020731346,0.00020162451,0.0002029723,0.000015515796,0.00023563887,0.00006304619,0.0019132574,0.00059996895,0.009260693,0.9874607,0.00001912794],"about_ca_topic_score_codex":0.0025123274,"about_ca_topic_score_gemma":0.0034659985,"teacher_disagreement_score":0.11660438,"about_ca_system_score_codex":0.0005968545,"about_ca_system_score_gemma":0.0017717842,"threshold_uncertainty_score":0.3900805},"labels":[],"label_agreement":null},{"id":"W4211147687","doi":"10.2200/s00204ed1v01y200910hlt005","title":"Spoken Dialogue Systems","year":2009,"lang":"en","type":"article","venue":"Synthesis lectures on human language technologies","topic":"Speech and dialogue systems","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 Toronto","funders":"","keywords":"Spoken language; Computer science; Multimodality; Adaptation (eye); Communicative competence; Competence (human resources); Human–computer interaction; Natural language processing; Artificial intelligence; Linguistics; Psychology; World Wide Web","score_opus":0.01943691375922096,"score_gpt":0.2708791217803281,"score_spread":0.2514422080211071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4211147687","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":[0.01028491,0.0055824653,0.73480976,0.001866624,0.0033459768,0.0008280085,0.0077139107,0.06839556,0.16717279],"genre_scores_gemma":[0.19539624,0.003101719,0.35471934,0.0014760159,0.0009946214,0.0012158497,0.032316662,0.006609962,0.40416953],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9982193,0.00045157623,0.00013833493,0.0003991561,0.00067536795,0.0001161323],"domain_scores_gemma":[0.998555,0.0004153232,0.000031061874,0.0003984871,0.0005121323,0.00008803732],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015744136,0.001139536,0.0012643442,0.0008243113,0.0012265624,0.003766528,0.00166291,0.0015236288,0.068567514],"category_scores_gemma":[0.0036283436,0.00058844837,0.0006537255,0.0006754266,0.00069811294,0.0022568204,0.0024775513,0.001146278,0.049465273],"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":[0.00037170306,0.00016671368,0.000404356,0.00059716875,0.000072396855,0.0002023162,0.00061006873,0.0028612197,0.036693092,0.03398991,0.20986038,0.71417075],"study_design_scores_gemma":[0.00015608943,0.000241196,0.0010293525,0.00018867073,0.00010396886,0.00048066204,0.00048111545,0.041214354,0.052062415,0.040126313,0.8638299,0.000086006985],"about_ca_topic_score_codex":0.0021656826,"about_ca_topic_score_gemma":0.002069309,"teacher_disagreement_score":0.068567514,"about_ca_system_score_codex":0.0006529307,"about_ca_system_score_gemma":0.0012397788,"threshold_uncertainty_score":0.2293812},"labels":[],"label_agreement":null},{"id":"W4214827825","doi":"10.55492/dhasa.v3i01.3860","title":"Morphology-based investigation of differences between spoken and written isiZulu","year":2021,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Canadian Society of Intestinal Research","funders":"","keywords":"Morpheme; Computer science; Natural language processing; Spoken language; Linguistics; Artificial intelligence","score_opus":0.03197314121375673,"score_gpt":0.23340187469603646,"score_spread":0.20142873348227974,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4214827825","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":[0.9852343,0.00026182138,0.004400938,0.000069429036,0.00002414054,0.000043726377,0.0009076194,0.000086514345,0.008971476],"genre_scores_gemma":[0.991835,0.00016641547,0.0055768797,0.000017522192,0.000009404461,0.00007332082,0.0010628379,0.00007487176,0.0011836382],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99964607,0.00006259652,0.000059274294,0.0001288388,0.00006720547,0.00003602753],"domain_scores_gemma":[0.9988115,0.0004136966,0.00023608685,0.00013183453,0.00035993007,0.00004695275],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040049557,0.00024535053,0.0002908031,0.0019367444,0.0006190493,0.0010169636,0.00025019128,0.00021046083,0.0029713518],"category_scores_gemma":[0.002478947,0.00017986483,0.000134343,0.0020009228,0.00085402734,0.00072333874,0.0006649677,0.0003894778,0.0004739234],"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":[0.0015328629,0.00008350901,0.087813936,0.0012536236,0.00011537561,0.0012892437,0.033486553,0.0008432962,0.6946759,0.006061367,0.0016476064,0.17119676],"study_design_scores_gemma":[0.00003625724,0.00036534568,0.9076746,0.00014897468,0.00016532383,0.0020834287,0.01972247,0.00373527,0.052055903,0.0013551112,0.0125789745,0.00007842303],"about_ca_topic_score_codex":0.005000944,"about_ca_topic_score_gemma":0.010546348,"teacher_disagreement_score":0.005000944,"about_ca_system_score_codex":0.0006428243,"about_ca_system_score_gemma":0.00047161474,"threshold_uncertainty_score":0.009943664},"labels":[],"label_agreement":null},{"id":"W4220712653","doi":"10.18280/ria.360115","title":"ADCSA-WSD: Adapted Discrete Crow Search Algorithm for Word Sense Disambiguation","year":2022,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":3,"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":"Benchmark (surveying); Computer science; Word (group theory); Word-sense disambiguation; Set (abstract data type); Meaning (existential); Artificial intelligence; Context (archaeology); Sequence labeling; Natural language processing; Sequence (biology); Field (mathematics); SemEval; Algorithm; Mathematics; WordNet","score_opus":0.05413081108919264,"score_gpt":0.2913148097576753,"score_spread":0.23718399866848267,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4220712653","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":[0.020705175,0.0017360504,0.96985966,0.00046085328,0.000448411,0.00026671457,0.0008654459,0.0030731524,0.002584524],"genre_scores_gemma":[0.14806373,0.0005651098,0.8418302,0.0006508475,0.00013267991,0.00039999204,0.0036101737,0.0003330112,0.004414291],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989255,0.00024076727,0.00015949391,0.00031337026,0.00028526646,0.00007554233],"domain_scores_gemma":[0.99907196,0.0004035289,0.0000671695,0.00012823835,0.000276994,0.000052095093],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010181764,0.0012109689,0.0019225085,0.0031871218,0.00092419534,0.0015686959,0.0019819573,0.0018213011,0.003526301],"category_scores_gemma":[0.0032692805,0.00041115395,0.0014702387,0.003405793,0.0007968294,0.0017550805,0.0015413095,0.001336243,0.0014740132],"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":[0.000551214,0.0004822374,0.0030068825,0.0006520414,0.0003114594,0.00048524368,0.00029992202,0.18490049,0.016145905,0.019001035,0.028535543,0.745628],"study_design_scores_gemma":[0.00017374681,0.00010401605,0.0005281424,0.00003440162,0.000048738184,0.00025662713,0.00015918347,0.95880586,0.005489953,0.020036547,0.014319841,0.00004294355],"about_ca_topic_score_codex":0.007887932,"about_ca_topic_score_gemma":0.012434508,"teacher_disagreement_score":0.007887932,"about_ca_system_score_codex":0.0008163867,"about_ca_system_score_gemma":0.0026285755,"threshold_uncertainty_score":0.015684009},"labels":[],"label_agreement":null},{"id":"W4223990858","doi":"10.1016/j.actpsy.2022.103590","title":"Learning unfamiliar words and perceiving non-native vowels in a second language: Insights from eye tracking","year":2022,"lang":"en","type":"article","venue":"Acta Psychologica","topic":"Speech and dialogue systems","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":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de Recherche du Québec-Société et Culture; Canada First Research Excellence Fund; Canada Foundation for Innovation","keywords":"Psychology; Task (project management); First language; Word (group theory); Variety (cybernetics); Eye tracking; Word recognition; Speech recognition; Cognitive psychology; Linguistics; Computer science; Artificial intelligence; Reading (process)","score_opus":0.013869906124289939,"score_gpt":0.2754472837730601,"score_spread":0.26157737764877015,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4223990858","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":[0.99784887,0.00011363731,0.0014045296,0.000022199054,0.0000035130136,0.0000062793088,0.000021235051,0.000008213141,0.0005714702],"genre_scores_gemma":[0.99747413,0.00017567659,0.0017467373,0.000022646287,0.0000033191375,0.000010472729,0.0000444291,0.0000053233903,0.0005172367],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9999013,0.000017467653,0.000006400645,0.000032468226,0.000026231908,0.000016094704],"domain_scores_gemma":[0.9997008,0.00011236581,0.00008758965,0.000025762756,0.00003710392,0.000036494836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019915844,0.00020899487,0.00014417419,0.00017563885,0.00009678305,0.00039405012,0.00009540209,0.00030916993,0.00053467246],"category_scores_gemma":[0.0009044429,0.00008865188,0.00012163859,0.000081726444,0.00021084686,0.0004159902,0.00027488888,0.0002873079,0.00010016062],"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":[0.00032619902,0.00021168441,0.03797341,0.00008544484,0.000021740805,0.0002585975,0.0020659182,0.00026887833,0.93029,0.0001928519,0.00007901654,0.02822634],"study_design_scores_gemma":[0.00001800386,0.0010194951,0.9044752,0.000025345336,0.000034860113,0.0007883274,0.0019671964,0.0033925562,0.086414844,0.0007189998,0.0011129302,0.00003215773],"about_ca_topic_score_codex":0.0018038462,"about_ca_topic_score_gemma":0.0029688426,"teacher_disagreement_score":0.0018038462,"about_ca_system_score_codex":0.00012104651,"about_ca_system_score_gemma":0.00015992353,"threshold_uncertainty_score":0.003586769},"labels":[],"label_agreement":null},{"id":"W4225149910","doi":"10.1145/3491102.3517599","title":"Expressive Auditory Gestures in a Voice-Based Pedagogical Agent","year":2022,"lang":"en","type":"article","venue":"CHI Conference on Human Factors in Computing Systems","topic":"Speech and dialogue systems","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":"University of Waterloo","funders":"","keywords":"Gesture; Computer science; Speech recognition; Artificial intelligence","score_opus":0.17356655534339074,"score_gpt":0.3479224640722172,"score_spread":0.17435590872882648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4225149910","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":[0.95328957,0.00025311174,0.040682226,0.00015589956,0.000056654015,0.00011682608,0.00002217404,0.00035121752,0.0050722696],"genre_scores_gemma":[0.97069407,0.00010803786,0.026791919,0.000071248134,0.000021657188,0.00012155042,0.000023821702,0.000031513002,0.0021361806],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99679035,0.0022102948,0.00010795853,0.00028846407,0.00048544267,0.00011742146],"domain_scores_gemma":[0.9949078,0.0037113256,0.00053898414,0.00028300795,0.00028085188,0.00027806708],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021609655,0.00053028786,0.0003774333,0.00027481155,0.0004652266,0.0018831266,0.0005516854,0.0007464105,0.002960289],"category_scores_gemma":[0.011069874,0.0002324857,0.000305651,0.00011736391,0.0009559791,0.0013245235,0.0015158743,0.00056302536,0.0006357733],"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":[0.0028936374,0.0017171968,0.025702761,0.0017443327,0.00022368133,0.0018484306,0.054959543,0.009741404,0.6252839,0.010616776,0.0011435115,0.2641248],"study_design_scores_gemma":[0.0017355087,0.032948587,0.16748226,0.0012366666,0.0020632762,0.008415612,0.071471035,0.15618095,0.40250692,0.035356853,0.119679324,0.0009230112],"about_ca_topic_score_codex":0.00021838839,"about_ca_topic_score_gemma":0.00026713085,"teacher_disagreement_score":0.002960289,"about_ca_system_score_codex":0.00018151257,"about_ca_system_score_gemma":0.00030159266,"threshold_uncertainty_score":0.011428416},"labels":[],"label_agreement":null},{"id":"W4229455020","doi":"10.1121/10.0011270","title":"Perception and timing of acoustic distance","year":2022,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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":"Dynamic time warping; Speech recognition; Computer science; Euclidean distance; Phonetics; Lexicon; Vowel; Duration (music); Task (project management); Sensitivity (control systems); Perception; Acoustics; Artificial intelligence; Linguistics; Psychology","score_opus":0.013780401176523648,"score_gpt":0.2393242405821999,"score_spread":0.22554383940567624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229455020","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":[0.9635229,0.00052215264,0.028013095,0.00009132704,0.000112035035,0.000033775705,0.00013747205,0.00013962279,0.0074276514],"genre_scores_gemma":[0.99233466,0.00015483772,0.0065397774,0.00002674033,0.000023956713,0.000015923313,0.00008109075,0.00006620195,0.000756678],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9991736,0.000177851,0.000049630977,0.00028624214,0.00025892575,0.000053672124],"domain_scores_gemma":[0.9965918,0.0017536334,0.0005722216,0.00026938884,0.00053275103,0.00028020347],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008002811,0.00023487725,0.00026551925,0.00079718634,0.0001791511,0.0018533956,0.0003380252,0.0005894537,0.0024662968],"category_scores_gemma":[0.0137784695,0.00035383843,0.00024265565,0.00041090866,0.00046946356,0.0016540745,0.0008572355,0.00045831662,0.00044871148],"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":[0.0032715506,0.00012362325,0.07557426,0.0004572144,0.00016326194,0.00053177995,0.007327971,0.0054779174,0.71347207,0.008987457,0.00081439456,0.18379849],"study_design_scores_gemma":[0.00011311052,0.0023472933,0.8542096,0.00015419176,0.00018426534,0.002785713,0.006045742,0.042271417,0.06451393,0.018155625,0.008894928,0.0003242181],"about_ca_topic_score_codex":0.0009923441,"about_ca_topic_score_gemma":0.00051462883,"teacher_disagreement_score":0.0024662968,"about_ca_system_score_codex":0.00022695896,"about_ca_system_score_gemma":0.00021175934,"threshold_uncertainty_score":0.008250594},"labels":[],"label_agreement":null},{"id":"W4229735078","doi":"10.4018/978-1-61350-456-7.ch807","title":"Enhanced Speech-Enabled Tools for Intelligent and Mobile E-Learning Applications","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Speech and dialogue systems","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":"Institut National de la Recherche Scientifique; Université de Moncton","funders":"","keywords":"Computer science; Multimedia; Software portability; World Wide Web; Human–computer interaction; Context (archaeology)","score_opus":0.023826936005418048,"score_gpt":0.25843321736208036,"score_spread":0.2346062813566623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4229735078","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06565751,0.02411765,0.6522421,0.0009733046,0.0011989035,0.0005004818,0.0009827234,0.012764876,0.2415624],"genre_scores_gemma":[0.20386013,0.0150763905,0.3364714,0.00091841246,0.00045671698,0.00045991663,0.0018623178,0.0012444672,0.43965027],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99982136,0.00003422657,0.000010747337,0.000019757954,0.00009966682,0.0000143020325],"domain_scores_gemma":[0.9997533,0.00016036489,0.000009105889,0.000026207572,0.000036270383,0.000014795507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020812961,0.00048396367,0.00020312036,0.00039833912,0.00016095354,0.000971652,0.0005941282,0.0007391826,0.022668159],"category_scores_gemma":[0.0006725358,0.00014504399,0.0002409829,0.00036974048,0.0002165391,0.0012683886,0.00074311876,0.0006226819,0.008854764],"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":[0.0001454414,0.00012648346,0.0002498356,0.0010958967,0.000020225021,0.00054897123,0.00062346697,0.0018966232,0.097496845,0.019363608,0.028932149,0.84950036],"study_design_scores_gemma":[0.000059044698,0.00042178336,0.0032785633,0.00047998034,0.000055197026,0.0027416733,0.0003535242,0.019096827,0.05085759,0.01069062,0.91190803,0.00005728581],"about_ca_topic_score_codex":0.00025388054,"about_ca_topic_score_gemma":0.00053769007,"teacher_disagreement_score":0.022668159,"about_ca_system_score_codex":0.00020222447,"about_ca_system_score_gemma":0.00025159473,"threshold_uncertainty_score":0.075832546},"labels":[],"label_agreement":null},{"id":"W4235821642","doi":"10.32920/ryerson.14648646","title":"The effects of statistical learning and congruency on the development of multi-modal objects","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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; York University","funders":"","keywords":"Modality (human–computer interaction); Facilitation; Object (grammar); Modal; Psychology; Predictive value; Cognitive psychology; Artificial intelligence; Computer science; Medicine; Neuroscience","score_opus":0.0154997429367849,"score_gpt":0.2637500768733927,"score_spread":0.24825033393660778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235821642","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":[0.98198205,0.000317541,0.013532636,0.00006211725,0.00003771815,0.00015728013,0.00009605873,0.0001224496,0.0036921906],"genre_scores_gemma":[0.98346233,0.00023826458,0.014278891,0.00009331928,0.000018196315,0.0002261992,0.00014302699,0.00018417597,0.001355584],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99649554,0.0007222024,0.00045263526,0.0011031424,0.0010165503,0.00021005787],"domain_scores_gemma":[0.94423646,0.04367308,0.0053420123,0.004147231,0.0013223593,0.0012789066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039741835,0.00058806234,0.00080084446,0.00069190963,0.00030431434,0.0015175584,0.00096245,0.0006939354,0.004389195],"category_scores_gemma":[0.035524003,0.0009589695,0.0003572825,0.00044219484,0.0011554604,0.0019583325,0.0025594374,0.0012896537,0.00048097665],"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":[0.005610643,0.000764061,0.014825071,0.00041203044,0.00008968929,0.00013474426,0.0005755915,0.0010207193,0.93739176,0.0013945431,0.00007639116,0.03770479],"study_design_scores_gemma":[0.0005847284,0.010850555,0.3782652,0.00009048409,0.00040955815,0.0011542289,0.0003428902,0.018946001,0.5765084,0.010016855,0.0026433256,0.00018787847],"about_ca_topic_score_codex":0.00047523467,"about_ca_topic_score_gemma":0.0007843665,"teacher_disagreement_score":0.004389195,"about_ca_system_score_codex":0.0005151159,"about_ca_system_score_gemma":0.00069498137,"threshold_uncertainty_score":0.02101773},"labels":[],"label_agreement":null},{"id":"W4236851119","doi":"10.1145/2702613.2706679","title":"Speech-based Interaction","year":2015,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; USable; Modalities; Natural (archaeology); Modality (human–computer interaction); Speech community; Human–computer interaction; Natural language; Focus (optics); Artificial intelligence; Multimedia; Linguistics","score_opus":0.05868022331432372,"score_gpt":0.27831212364404023,"score_spread":0.21963190032971652,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4236851119","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":[0.02679561,0.017890036,0.4137271,0.0061616483,0.0038332902,0.0005477029,0.002196664,0.00823195,0.52061605],"genre_scores_gemma":[0.529614,0.013009461,0.1383787,0.005644384,0.0019257464,0.0006640832,0.003118931,0.0014156181,0.306229],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986053,0.0004417619,0.00007881556,0.00023904581,0.00054531376,0.000089795685],"domain_scores_gemma":[0.998686,0.00071901333,0.000051980052,0.00016475536,0.0002880125,0.000090209716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010079714,0.00073263986,0.00054081465,0.0008233688,0.0008341701,0.0037019819,0.0008726323,0.0017038283,0.059343357],"category_scores_gemma":[0.003861397,0.00019362812,0.00051597366,0.0006550081,0.0007373818,0.0020652106,0.0025741484,0.0007844342,0.02296397],"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":[0.0005417565,0.00013859003,0.0011330796,0.0019937323,0.00010953602,0.00075610704,0.0037555627,0.0016909569,0.077007055,0.077980995,0.13056305,0.70432967],"study_design_scores_gemma":[0.000084157604,0.0004010079,0.004337288,0.00072767946,0.00012310558,0.002935761,0.0019040774,0.012103053,0.02314125,0.0631965,0.8909168,0.00012927318],"about_ca_topic_score_codex":0.00097161456,"about_ca_topic_score_gemma":0.0011412047,"teacher_disagreement_score":0.059343357,"about_ca_system_score_codex":0.00056056544,"about_ca_system_score_gemma":0.00052646355,"threshold_uncertainty_score":0.19852328},"labels":[],"label_agreement":null},{"id":"W4238109636","doi":"10.1145/1083063.1083080","title":"&lt;username&gt;, i need you!","year":2005,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Usability; Affect (linguistics); Computer science; Control (management); Position paper; Human–computer interaction; Position (finance); Knowledge management; Internet privacy; World Wide Web; Business; Psychology; Artificial intelligence","score_opus":0.012877067233322282,"score_gpt":0.22088782959119463,"score_spread":0.20801076235787236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238109636","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":[0.017920524,0.0012842589,0.031435803,0.022019558,0.013342634,0.00054425094,0.0054616746,0.020784114,0.8872072],"genre_scores_gemma":[0.046003014,0.000926503,0.005320789,0.0065428475,0.0017261474,0.00026180985,0.002239546,0.0065950346,0.9303844],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999564,0.00013946625,0.00002825132,0.000056734414,0.000119455755,0.0000919867],"domain_scores_gemma":[0.997988,0.00057659537,0.00008682418,0.00030685883,0.00057634775,0.0004653211],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007392869,0.0006254647,0.00064849993,0.0005743957,0.0017336436,0.0033578994,0.00078037457,0.0013329465,0.5286444],"category_scores_gemma":[0.005461007,0.00035658848,0.00039927877,0.00067862496,0.00042571634,0.0040387334,0.0018405153,0.0013795517,0.46593335],"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":[0.00017744744,0.00006215058,0.0014673275,0.000106352214,0.000004572047,0.00028824215,0.00086744264,0.000086999135,0.00096466386,0.0032576288,0.89309794,0.09961927],"study_design_scores_gemma":[0.000014861175,0.000056783476,0.0013068654,0.00004680026,0.0000053781387,0.00030392743,0.0004876811,0.00073082856,0.000692717,0.0008126569,0.99550974,0.000031864583],"about_ca_topic_score_codex":0.003100481,"about_ca_topic_score_gemma":0.004655607,"teacher_disagreement_score":0.5286444,"about_ca_system_score_codex":0.00049288286,"about_ca_system_score_gemma":0.0003844612,"threshold_uncertainty_score":0.6723316},"labels":[],"label_agreement":null},{"id":"W4238635791","doi":"10.18653/v1/2020.cmcl-1","title":"Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics","year":2020,"lang":"en","type":"paratext","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":12,"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":"Università di Pisa; Indian Institute of Technology Delhi; Technion-Israel Institute of Technology; Universitat de Barcelona; Universität des Saarlandes; Centre National de la Recherche Scientifique; Universidade de Macau; University of Rochester; University of Wolverhampton; McGill University; Ohio State University; Max Planck Instituut voor Psycholinguïstiek; Université Catholique de Louvain; Aix-Marseille Université; Universiteit van Amsterdam; Universiteit van Tilburg; Göteborgs Universitet; Yale University","keywords":"Computer science; Cognitive linguistics; Computational linguistics; Cognitive science; Linguistics; Cognition; Natural language processing; Psychology; Philosophy","score_opus":0.03753460888852228,"score_gpt":0.27158413969867456,"score_spread":0.23404953081015228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4238635791","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":[0.018811513,0.04644482,0.49555075,0.07416652,0.042924307,0.00038664162,0.0065891948,0.003794529,0.31133178],"genre_scores_gemma":[0.09834906,0.025680497,0.16565262,0.00521796,0.014556782,0.0005951033,0.016863352,0.0046793637,0.66840523],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975858,0.0014684816,0.00011206084,0.00033038916,0.00034899393,0.00015431322],"domain_scores_gemma":[0.991892,0.004889865,0.00010923783,0.0012052044,0.00115707,0.0007466254],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006248613,0.0012250276,0.0020361643,0.0014350347,0.0012910068,0.009720403,0.002035211,0.002414532,0.073009774],"category_scores_gemma":[0.011255026,0.0007364769,0.0012380813,0.0015667313,0.00185747,0.008849204,0.0030936352,0.0045041465,0.025468655],"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":[0.000628226,0.00034700148,0.00074416783,0.00044999341,0.000095253294,0.0002236047,0.0010845405,0.0020941084,0.0017961122,0.12072292,0.62695026,0.2448638],"study_design_scores_gemma":[0.000084634885,0.000060926097,0.0009592598,0.00035871795,0.00007027112,0.00025606144,0.0004075701,0.015024901,0.0019502805,0.13156044,0.84923214,0.000034772263],"about_ca_topic_score_codex":0.0073122177,"about_ca_topic_score_gemma":0.007508907,"teacher_disagreement_score":0.073009774,"about_ca_system_score_codex":0.0020466705,"about_ca_system_score_gemma":0.0026077305,"threshold_uncertainty_score":0.24424201},"labels":[],"label_agreement":null},{"id":"W4239177510","doi":"10.1121/1.4800506","title":"Coordinating conversation through posture","year":2013,"lang":"en","type":"article","venue":"Proceedings of meetings on acoustics","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Conversation; Movement (music); Motion (physics); Categorization; Perception; Computer science; Dynamics (music); Speech recognition; Conversation analysis; Communication; Psychology; Human–computer interaction; Artificial intelligence; Acoustics","score_opus":0.00926486264413023,"score_gpt":0.21251725918389655,"score_spread":0.20325239653976632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239177510","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":[0.80585957,0.0016559802,0.11856434,0.0005537104,0.00014830705,0.00020509238,0.0005760528,0.0010733962,0.071363516],"genre_scores_gemma":[0.98475814,0.00025679503,0.0123286545,0.000043306067,0.00003447686,0.000050016024,0.00014214593,0.000069200665,0.002317252],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99877185,0.00049257133,0.00005617341,0.00026858578,0.0002491127,0.00016166382],"domain_scores_gemma":[0.9990908,0.00029099674,0.00020691038,0.00011125961,0.00020553,0.000094550596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00057797274,0.00039958526,0.00034637525,0.0011197436,0.0008786441,0.003008558,0.00036559455,0.000514103,0.0030707929],"category_scores_gemma":[0.0040123053,0.00020731342,0.00026150775,0.00075412495,0.00091036304,0.0013150045,0.0013470895,0.00032934197,0.0010328966],"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":[0.0005930269,0.000090265596,0.06815253,0.00073458825,0.00018436108,0.0010025627,0.0502064,0.0054614563,0.30746886,0.022519097,0.004630075,0.5389569],"study_design_scores_gemma":[0.00004663858,0.00064231345,0.727164,0.0004460357,0.00034261894,0.0033062722,0.04913925,0.03781404,0.04264939,0.045771554,0.09234606,0.00033185698],"about_ca_topic_score_codex":0.0019591164,"about_ca_topic_score_gemma":0.0016900228,"teacher_disagreement_score":0.0030707929,"about_ca_system_score_codex":0.00044063735,"about_ca_system_score_gemma":0.00054463564,"threshold_uncertainty_score":0.0102728605},"labels":[],"label_agreement":null},{"id":"W4241808013","doi":"10.1109/iv.2004.1320245","title":"Representing hierarchies using multiple synthetic voices","year":2004,"lang":"en","type":"article","venue":"Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004.","topic":"Speech and dialogue systems","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 Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hierarchy; Computer science; Set (abstract data type); Node (physics); Synthetic data; Representation (politics); Task (project management); Range (aeronautics); Artificial intelligence; Speech recognition; Natural language processing; Engineering","score_opus":0.05251117624943565,"score_gpt":0.30506165346328834,"score_spread":0.2525504772138527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4241808013","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32675982,0.00046525986,0.6663331,0.00020066494,0.00007406669,0.00016001044,0.00021162289,0.0011129978,0.0046824785],"genre_scores_gemma":[0.7079739,0.0003030572,0.28943112,0.000102293176,0.000030661333,0.00014612323,0.0004976847,0.00015629294,0.0013588521],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9987576,0.00063001324,0.000070377326,0.0002292827,0.00024417214,0.00006855259],"domain_scores_gemma":[0.99293846,0.0054096077,0.00041557217,0.00074209616,0.00036172933,0.00013249804],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014825036,0.0005519597,0.00039387002,0.0005600089,0.00023151615,0.0012886329,0.0009368977,0.0005801531,0.0032282437],"category_scores_gemma":[0.009078844,0.00033696083,0.00056141184,0.0002984321,0.0006486612,0.0023488083,0.0013289156,0.000522904,0.0003072564],"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":[0.0012207502,0.00041548014,0.008311216,0.0013170597,0.00023194161,0.0007082335,0.008244965,0.11599797,0.38102412,0.027526807,0.0019719617,0.45302945],"study_design_scores_gemma":[0.0003530841,0.001859387,0.009482443,0.0002956709,0.00030206272,0.001381843,0.0040196083,0.7547969,0.115541816,0.075934745,0.03577206,0.00026043877],"about_ca_topic_score_codex":0.0005754144,"about_ca_topic_score_gemma":0.0010152314,"teacher_disagreement_score":0.0032282437,"about_ca_system_score_codex":0.0003402574,"about_ca_system_score_gemma":0.00027687155,"threshold_uncertainty_score":0.010799587},"labels":[],"label_agreement":null},{"id":"W4243251602","doi":"10.3410/f.729979656.793559282","title":"Faculty Opinions recommendation of A web-based clinical decision support system for gestational diabetes: Automatic diet prescription and detection of insulin needs.","year":2019,"lang":"en","type":"dataset","venue":"Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature","topic":"Speech and dialogue systems","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","funders":"","keywords":"Gestational diabetes; Medical prescription; Insulin; Medicine; Recommender system; Diabetes mellitus; Computer science; Endocrinology; Gestation; Pregnancy; World Wide Web; Pharmacology; Biology","score_opus":0.03848256213627271,"score_gpt":0.3490644157377635,"score_spread":0.31058185360149076,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243251602","genre_codex":"dataset","genre_gemma":"dataset","domain_codex":null,"domain_gemma":"evaluation","model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"dataset","genre_consensus":"dataset","domain_candidate":"evaluation","domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0025558926,0.00018450856,0.00046917322,0.00041083747,0.00017761961,0.00012389847,0.9926864,0.0018459789,0.0015456494],"genre_scores_gemma":[0.0021231347,0.00006268066,0.0011180661,0.00009158716,0.000019770654,0.00011621409,0.99520916,0.000056072993,0.0012033276],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989955,0.00021257863,0.00013863592,0.0002851181,0.0002452664,0.00012288555],"domain_scores_gemma":[0.99692386,0.0007512938,0.00020487446,0.00052669254,0.0010704567,0.0005228126],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0014761153,0.002751393,0.0012257805,0.002464064,0.000727936,0.001326671,0.0023926415,0.0025896896,0.02335401],"category_scores_gemma":[0.005963686,0.00055125804,0.0013209959,0.001957193,0.0002735229,0.0009062375,0.0015010587,0.001600088,0.044798456],"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":[0.00042610595,0.00019830096,0.0044373744,0.00074244314,0.000086117274,0.00007640409,0.000034253546,0.000452882,0.0007062279,0.00013705183,0.98076564,0.011937219],"study_design_scores_gemma":[0.001702216,0.00037670007,0.049855568,0.00070322765,0.00033187948,0.00044340425,0.00037922687,0.015997164,0.006589551,0.001426795,0.92201465,0.00017970987],"about_ca_topic_score_codex":0.04174273,"about_ca_topic_score_gemma":0.09857745,"teacher_disagreement_score":0.9985239,"about_ca_system_score_codex":0.0013501606,"about_ca_system_score_gemma":0.002385148,"threshold_uncertainty_score":0.08299953},"labels":[],"label_agreement":null},{"id":"W4243818027","doi":"10.31219/osf.io/7vkwz","title":"Familiarization May Minimize Age-Related Declines in Rule-Based Category Learning","year":2017,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Western University","funders":"","keywords":"Categorization; Psychology; Cognition; Task (project management); Concept learning; Cognitive psychology; Executive functions; Function (biology); Developmental psychology; Artificial intelligence; Computer science","score_opus":0.03269559991436343,"score_gpt":0.277088181963707,"score_spread":0.24439258204934355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243818027","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":[0.993346,0.00047698242,0.003888713,0.00031951306,0.00006612984,0.00009126673,0.000083481056,0.00022277799,0.0015053535],"genre_scores_gemma":[0.9852601,0.00046773965,0.009405102,0.00034825056,0.000089886205,0.0001653724,0.00020535893,0.000049576014,0.004008594],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99970263,0.00004891267,0.000033695855,0.00012752022,0.000032090073,0.000055074343],"domain_scores_gemma":[0.9990395,0.00022655763,0.00025047886,0.00016657269,0.00011739428,0.00019944127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006343086,0.0003527835,0.00062317506,0.00023282842,0.00017209223,0.00057213637,0.0005025414,0.0007637627,0.0061031133],"category_scores_gemma":[0.002483396,0.00019938266,0.0002869044,0.0001289947,0.00037125006,0.0009859867,0.0005553031,0.00063792954,0.0010246646],"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":[0.005134705,0.009974997,0.025038954,0.0009009677,0.00018079625,0.00049527216,0.001584184,0.0006068861,0.7177246,0.0012313923,0.0024822094,0.23464504],"study_design_scores_gemma":[0.0013386422,0.07844821,0.6127644,0.00027847954,0.000729477,0.0026941493,0.0024999923,0.006639082,0.24462155,0.010204128,0.039602686,0.00017928898],"about_ca_topic_score_codex":0.0005481633,"about_ca_topic_score_gemma":0.0015263945,"teacher_disagreement_score":0.0061031133,"about_ca_system_score_codex":0.00014754948,"about_ca_system_score_gemma":0.00032024758,"threshold_uncertainty_score":0.020416975},"labels":[],"label_agreement":null},{"id":"W4243883973","doi":"10.1121/1.3277008","title":"Function words of lexical bundles: the relation of frequency and reduction","year":2009,"lang":"en","type":"article","venue":"Proceedings of meetings on acoustics","topic":"Speech and dialogue systems","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 Alberta","funders":"","keywords":"Reduction (mathematics); Predictability; Word (group theory); Word lists by frequency; Computer science; Speech recognition; Duration (music); Speech production; Function (biology); Part of speech; Natural language processing; Artificial intelligence; Mathematics; Acoustics; Statistics; Physics; Biology","score_opus":0.011209981190798086,"score_gpt":0.22156638594633904,"score_spread":0.21035640475554096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4243883973","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":[0.9942372,0.00032485378,0.0031790363,0.000043810032,0.000012034599,0.000023050385,0.00007580849,0.0000555904,0.0020484924],"genre_scores_gemma":[0.99664176,0.00011559436,0.0026623898,0.000023276763,0.00001681669,0.00003502707,0.0001309461,0.000050580555,0.00032367927],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9987091,0.00027874194,0.00014083006,0.00030152584,0.00050621544,0.000063546366],"domain_scores_gemma":[0.9816358,0.012180985,0.0032192748,0.0014411657,0.0011171382,0.00040569334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008115279,0.0003004098,0.00041210768,0.0009792527,0.00029264373,0.0010017954,0.0002997352,0.0004566725,0.0024338495],"category_scores_gemma":[0.019511962,0.00035075698,0.00020319976,0.0004558722,0.0008120702,0.0010736729,0.0007516411,0.00065322197,0.0003514723],"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":[0.0037350927,0.00048380214,0.13526055,0.00040081242,0.00025069635,0.0005012646,0.005184228,0.0016430934,0.7288477,0.0018312333,0.00032138516,0.121540174],"study_design_scores_gemma":[0.00005332991,0.0015334054,0.9453085,0.000032651413,0.00014570475,0.0017957388,0.0009644508,0.004155332,0.04183808,0.0027811022,0.0013247321,0.00006692636],"about_ca_topic_score_codex":0.00073634187,"about_ca_topic_score_gemma":0.00050508353,"teacher_disagreement_score":0.0024338495,"about_ca_system_score_codex":0.0002788138,"about_ca_system_score_gemma":0.00018406482,"threshold_uncertainty_score":0.0081419945},"labels":[],"label_agreement":null},{"id":"W4244748443","doi":"10.31234/osf.io/xp6k2","title":"Automatic word count estimation from daylong child-centered recordings in various language environments using language-independent syllabification of speech","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"","keywords":"Computer science; Syllable; Word (group theory); Speech recognition; Syllabification; Phonotactics; Natural language processing; Artificial intelligence; Mathematics; Linguistics","score_opus":0.01606227370194699,"score_gpt":0.2556369938349796,"score_spread":0.23957472013303263,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244748443","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46240556,0.0019034054,0.47136036,0.0002386851,0.0004956206,0.0008584297,0.01380603,0.040499505,0.0084324395],"genre_scores_gemma":[0.41803417,0.0009906486,0.5389751,0.0002279758,0.00018809197,0.0013704918,0.030274361,0.0017913253,0.008147918],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9985297,0.00021433173,0.0001267826,0.00060936547,0.00041059588,0.00010932596],"domain_scores_gemma":[0.99722856,0.0010761402,0.00022884154,0.0003030221,0.0010193783,0.00014398377],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011012129,0.0013281817,0.0011442509,0.0024389927,0.0003010563,0.0011581619,0.0009675029,0.0009713771,0.004664797],"category_scores_gemma":[0.0041033416,0.00035143577,0.00054457935,0.0012251216,0.0003808536,0.0015699248,0.0014607935,0.0007330264,0.006599315],"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":[0.0007242961,0.00022487559,0.013121425,0.00094604824,0.00020760832,0.00060005044,0.0008695707,0.003321011,0.24594219,0.00076573767,0.010177341,0.7230998],"study_design_scores_gemma":[0.00025212023,0.0009767236,0.22712025,0.00034650633,0.0003610973,0.0038510638,0.002283995,0.34435916,0.37699264,0.003843319,0.039055943,0.00055712095],"about_ca_topic_score_codex":0.0026021393,"about_ca_topic_score_gemma":0.0050128214,"teacher_disagreement_score":0.004664797,"about_ca_system_score_codex":0.00031682148,"about_ca_system_score_gemma":0.00059829175,"threshold_uncertainty_score":0.0156053305},"labels":[],"label_agreement":null},{"id":"W4245127862","doi":"10.24908/iqurcp.8574","title":"How Looking While Listening Affects Speech Segmentation","year":2018,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Speech and dialogue systems","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":"Active listening; Segmentation; Speech segmentation; Context (archaeology); Natural (archaeology); Task (project management); Psychology; Cognitive psychology; Computer science; Audio visual; Speech recognition; Text segmentation; Linguistics; Natural language processing; Communication; Artificial intelligence; Multimedia; History","score_opus":0.08973062391492762,"score_gpt":0.3474432551572023,"score_spread":0.2577126312422747,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245127862","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":[0.9945437,0.00017056329,0.0012248568,0.00019793992,0.000055044195,0.000020730864,0.00005756794,0.0000816707,0.0036479847],"genre_scores_gemma":[0.99571496,0.00015589024,0.002041048,0.0002663624,0.00002156549,0.000036025547,0.000098961056,0.00005877334,0.0016063717],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.999169,0.00028690058,0.00006150889,0.00018278108,0.00017683576,0.00012304258],"domain_scores_gemma":[0.9936373,0.004489454,0.00064225966,0.0002463456,0.00031304028,0.0006716137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063367654,0.00033325082,0.00030738825,0.0002698373,0.00039360338,0.0014501287,0.0003379351,0.0009369579,0.006188349],"category_scores_gemma":[0.011897996,0.00028870467,0.00030807185,0.00012248091,0.0006499432,0.0008400508,0.0006457963,0.0006284904,0.0006751276],"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":[0.0047850762,0.0010935096,0.09551709,0.0005484343,0.00013958159,0.0017802884,0.016636068,0.0007284053,0.79497546,0.00076630607,0.0017924573,0.08123737],"study_design_scores_gemma":[0.00032094336,0.007619882,0.8824555,0.00019553032,0.0006274257,0.00231771,0.012294131,0.0035263877,0.08134749,0.003675441,0.005426725,0.00019280352],"about_ca_topic_score_codex":0.0011521182,"about_ca_topic_score_gemma":0.001614275,"teacher_disagreement_score":0.006188349,"about_ca_system_score_codex":0.00023384846,"about_ca_system_score_gemma":0.0002214867,"threshold_uncertainty_score":0.020702124},"labels":[],"label_agreement":null},{"id":"W4245453220","doi":"10.32920/ryerson.14648646.v1","title":"The effects of statistical learning and congruency on the development of multi-modal objects","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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; York University","funders":"","keywords":"Modality (human–computer interaction); Facilitation; Object (grammar); Psychology; Modal; Predictive value; Cognitive psychology; Artificial intelligence; Computer science; Medicine; Neuroscience","score_opus":0.0154997429367849,"score_gpt":0.2637500768733927,"score_spread":0.24825033393660778,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4245453220","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":[0.98198205,0.000317541,0.013532636,0.00006211725,0.00003771815,0.00015728013,0.00009605873,0.0001224496,0.0036921906],"genre_scores_gemma":[0.98346233,0.00023826458,0.014278891,0.00009331928,0.000018196315,0.0002261992,0.00014302699,0.00018417597,0.001355584],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99649554,0.0007222024,0.00045263526,0.0011031424,0.0010165503,0.00021005787],"domain_scores_gemma":[0.94423646,0.04367308,0.0053420123,0.004147231,0.0013223593,0.0012789066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039741835,0.00058806234,0.00080084446,0.00069190963,0.00030431434,0.0015175584,0.00096245,0.0006939354,0.004389195],"category_scores_gemma":[0.035524003,0.0009589695,0.0003572825,0.00044219484,0.0011554604,0.0019583325,0.0025594374,0.0012896537,0.00048097665],"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":[0.005610643,0.000764061,0.014825071,0.00041203044,0.00008968929,0.00013474426,0.0005755915,0.0010207193,0.93739176,0.0013945431,0.00007639116,0.03770479],"study_design_scores_gemma":[0.0005847284,0.010850555,0.3782652,0.00009048409,0.00040955815,0.0011542289,0.0003428902,0.018946001,0.5765084,0.010016855,0.0026433256,0.00018787847],"about_ca_topic_score_codex":0.00047523467,"about_ca_topic_score_gemma":0.0007843665,"teacher_disagreement_score":0.004389195,"about_ca_system_score_codex":0.0005151159,"about_ca_system_score_gemma":0.00069498137,"threshold_uncertainty_score":0.02101773},"labels":[],"label_agreement":null},{"id":"W4248085993","doi":"10.1109/dnsr.2004.1344716","title":"LRRP SpeechWebs","year":2004,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Hyperlink; Architecture; The Internet; World Wide Web; Speech analytics; Web page; Speech synthesis; Speech recognition; Speech corpus","score_opus":0.01001156045615998,"score_gpt":0.21133329051939342,"score_spread":0.20132173006323345,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4248085993","genre_codex":"software","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":[0.009943913,0.0010528446,0.32920316,0.0013619964,0.0006752538,0.0005060027,0.0052725086,0.43434763,0.21763673],"genre_scores_gemma":[0.17910132,0.0020481944,0.24172375,0.0029351064,0.0007767366,0.0011243394,0.04770901,0.051166326,0.47341523],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99798334,0.00037199678,0.00016657221,0.0003165317,0.0009285302,0.00023298195],"domain_scores_gemma":[0.9975999,0.00038734276,0.00012412522,0.000952597,0.0006310739,0.00030487883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015128194,0.0010225493,0.0006876824,0.0016679442,0.00090342265,0.004082525,0.0028147427,0.0018046277,0.09794532],"category_scores_gemma":[0.0034459205,0.00096952793,0.0007562335,0.0011562592,0.0007877838,0.0052871937,0.0036537484,0.0018494239,0.09196508],"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":[0.0009852344,0.00023439994,0.001330259,0.0007235194,0.00006843813,0.0009951001,0.0014100957,0.0026788162,0.02285776,0.06681505,0.45758292,0.44431832],"study_design_scores_gemma":[0.0000674938,0.00007569652,0.00056214456,0.00006689949,0.000023930623,0.0004744809,0.00012095416,0.011912546,0.012197033,0.007324706,0.9671214,0.000052789583],"about_ca_topic_score_codex":0.0049709124,"about_ca_topic_score_gemma":0.0035419853,"teacher_disagreement_score":0.09794532,"about_ca_system_score_codex":0.0012201559,"about_ca_system_score_gemma":0.0013296308,"threshold_uncertainty_score":0.32765973},"labels":[],"label_agreement":null},{"id":"W4251366631","doi":"10.1145/3027063.3027117","title":"Speech-based Interaction","year":2017,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Modalities; Usability; Modality (human–computer interaction); Natural language; Human–computer interaction; Speech community; Natural (archaeology); Field (mathematics); Artificial intelligence; Linguistics","score_opus":0.03618438702753543,"score_gpt":0.29374229515474315,"score_spread":0.2575579081272077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251366631","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":[0.021122172,0.027256643,0.34198666,0.008039282,0.006826748,0.0006491951,0.0032584826,0.010557262,0.58030355],"genre_scores_gemma":[0.4058493,0.01801245,0.15448667,0.010315019,0.0032884544,0.0009250896,0.005497053,0.0021975706,0.39942843],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984951,0.0004188122,0.00009050576,0.00030704873,0.0005886804,0.00009983626],"domain_scores_gemma":[0.99866736,0.0006874787,0.000054799526,0.00017877227,0.0003045285,0.00010712479],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010279636,0.000969516,0.00064295443,0.0009521101,0.0009240848,0.0040191957,0.0010613013,0.00210803,0.08356544],"category_scores_gemma":[0.0039704554,0.00023283287,0.000638876,0.00079791935,0.00074860273,0.0025714403,0.0031160866,0.0010710418,0.0375342],"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":[0.0005230829,0.00014188334,0.000970619,0.0020743902,0.00012274402,0.00087720144,0.0024270902,0.001334796,0.059689727,0.062394187,0.19564383,0.6738004],"study_design_scores_gemma":[0.000079464546,0.00032823283,0.0030033155,0.00065352477,0.00011072139,0.002818713,0.0012022522,0.008909947,0.014952073,0.050782423,0.91702557,0.00013371225],"about_ca_topic_score_codex":0.0009140252,"about_ca_topic_score_gemma":0.0012237115,"teacher_disagreement_score":0.08356544,"about_ca_system_score_codex":0.0006397,"about_ca_system_score_gemma":0.0005852384,"threshold_uncertainty_score":0.27955425},"labels":[],"label_agreement":null},{"id":"W4251859513","doi":"10.1145/1180995","title":"Proceedings of the 8th international conference on Multimodal interfaces","year":2006,"lang":"en","type":"paratext","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":30,"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; Presentation (obstetrics); Multimodal interaction; User interface; Human–computer interaction; Multimedia","score_opus":0.02410713025590538,"score_gpt":0.2615951921719252,"score_spread":0.2374880619160198,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251859513","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":[0.023134872,0.109949335,0.28606436,0.0139007475,0.08797801,0.0019381677,0.005826863,0.014040504,0.45716718],"genre_scores_gemma":[0.07107705,0.042254116,0.10474251,0.0049965256,0.012962264,0.0014560582,0.014396149,0.002191719,0.74592364],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99816245,0.0004987757,0.00018207042,0.00031950485,0.00067299115,0.00016418273],"domain_scores_gemma":[0.9982716,0.00041918198,0.00006334764,0.00021775575,0.0007730595,0.00025508384],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019115757,0.0020595705,0.00172936,0.0012477076,0.0007058333,0.0051879557,0.0016480028,0.0025059434,0.1520794],"category_scores_gemma":[0.003776531,0.00033471864,0.00079331326,0.00089445495,0.0010011275,0.0035944495,0.0023197015,0.002564198,0.06520406],"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":[0.0006270506,0.00022788567,0.00080994685,0.00082286797,0.00014600574,0.0005127257,0.00045065177,0.00050955475,0.012327331,0.006289923,0.6051503,0.37212577],"study_design_scores_gemma":[0.00004462015,0.00014585663,0.001399376,0.0002738855,0.00006327876,0.00050342403,0.00019317871,0.002960766,0.0020540403,0.0034267455,0.9888931,0.000041699564],"about_ca_topic_score_codex":0.00129344,"about_ca_topic_score_gemma":0.0015696753,"teacher_disagreement_score":0.1520794,"about_ca_system_score_codex":0.0006553396,"about_ca_system_score_gemma":0.0008854711,"threshold_uncertainty_score":0.5087563},"labels":[],"label_agreement":null},{"id":"W4253160425","doi":"10.1167/10.7.1055","title":"Human Echolocation II","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Speech and dialogue systems","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; Baycrest Hospital","funders":"","keywords":"Human echolocation; Communication; Neuroscience; Psychology","score_opus":0.012763248483183314,"score_gpt":0.29731319759037,"score_spread":0.2845499491071867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253160425","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.32365146,0.009336018,0.3388914,0.0016872359,0.0018602735,0.000072604416,0.00091982953,0.0023460463,0.32123515],"genre_scores_gemma":[0.84328973,0.0017649081,0.01844141,0.0002835934,0.00031023173,0.00003528416,0.0009366283,0.00024715107,0.13469094],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99991155,0.000012855417,0.0000027783103,0.00003955633,0.000017883725,0.00001545918],"domain_scores_gemma":[0.99985576,0.0000397195,0.0000067905994,0.000034994486,0.00003706737,0.000025681156],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00017433177,0.00038008377,0.00021187162,0.000427249,0.0002550947,0.0010853921,0.00024251222,0.00062932057,0.01327129],"category_scores_gemma":[0.0006513396,0.00021529749,0.00021514032,0.00030524997,0.0004382797,0.0008937547,0.00048603947,0.0004936617,0.0055326084],"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":[0.00052707404,0.00010594544,0.005361455,0.00020798096,0.00006489131,0.000607728,0.0010212878,0.011220092,0.383045,0.06105176,0.024465181,0.5123217],"study_design_scores_gemma":[0.000156204,0.00089331064,0.1469816,0.00026592362,0.00019179478,0.009605494,0.0027672986,0.1591117,0.20556942,0.136202,0.3379683,0.0002869934],"about_ca_topic_score_codex":0.0011303944,"about_ca_topic_score_gemma":0.00058480876,"teacher_disagreement_score":0.01327129,"about_ca_system_score_codex":0.00020892233,"about_ca_system_score_gemma":0.00015606626,"threshold_uncertainty_score":0.044396937},"labels":[],"label_agreement":null},{"id":"W4253449628","doi":"10.1109/icosc.2007.4338375","title":"Adding Semantics to Formal Data Specifications to Automatically Generate Corresponding Voice Data-Input Applications","year":2007,"lang":"en","type":"article","venue":"International Conference on Semantic Computing (ICSC 2007)","topic":"Speech and dialogue systems","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":"Computer science; Semantics (computer science); Formal semantics (linguistics); Programming language; Formal methods; Natural language processing","score_opus":0.17971773490567128,"score_gpt":0.3690396209567837,"score_spread":0.18932188605111244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4253449628","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003740308,0.000061713145,0.9899095,0.000113280315,0.00007245896,0.00013560025,0.0002033166,0.004656496,0.0011073246],"genre_scores_gemma":[0.05530487,0.0001798068,0.93897337,0.00021910477,0.000031592743,0.00027455384,0.001095116,0.002386297,0.0015352793],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99695575,0.0009390658,0.00044095513,0.00041722527,0.0011189895,0.00012806535],"domain_scores_gemma":[0.9917658,0.0051030205,0.00034837314,0.0011804817,0.0014818896,0.000120378114],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039170017,0.0009861698,0.000597595,0.0014843761,0.0005541523,0.0019775436,0.0010635006,0.0009643624,0.0035828927],"category_scores_gemma":[0.011252983,0.0008869899,0.001353691,0.00074845116,0.0011623828,0.00230737,0.002020843,0.0018761775,0.0018377353],"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":[0.00053047773,0.00035013552,0.0033230674,0.0020929181,0.00016337144,0.0019068471,0.004356038,0.04629021,0.1255486,0.2558171,0.01686465,0.5427567],"study_design_scores_gemma":[0.0002451388,0.00018312168,0.00054189394,0.0005006156,0.00014669447,0.0013293083,0.00061422057,0.35459197,0.28292596,0.12220392,0.23651345,0.00020370026],"about_ca_topic_score_codex":0.0012532455,"about_ca_topic_score_gemma":0.0013244357,"teacher_disagreement_score":0.0039170017,"about_ca_system_score_codex":0.0008487057,"about_ca_system_score_gemma":0.0019452446,"threshold_uncertainty_score":0.020715356},"labels":[],"label_agreement":null},{"id":"W4254909673","doi":"10.1145/2851581.2856689","title":"Speech-based Interaction","year":2016,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Toronto","funders":"Networks of Centres of Excellence of Canada","keywords":"Computer science; Modalities; Natural language; Usability; Natural (archaeology); Modality (human–computer interaction); Human–computer interaction; Speech community; Field (mathematics); Artificial intelligence","score_opus":0.01939153048110885,"score_gpt":0.2445686132079305,"score_spread":0.22517708272682163,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254909673","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":[0.020776859,0.026886435,0.34941223,0.008079334,0.006655367,0.0006567136,0.0031181735,0.01033818,0.5740767],"genre_scores_gemma":[0.41463405,0.018299194,0.15999007,0.010596696,0.003307529,0.00096495706,0.005457993,0.0022395807,0.38450992],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984242,0.0004550855,0.000095167845,0.0003172561,0.00060398143,0.00010424728],"domain_scores_gemma":[0.9985464,0.000765251,0.00005924185,0.00019313012,0.00032115396,0.00011471383],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011033698,0.0009870642,0.00065857504,0.0009758143,0.0009616476,0.004153377,0.0011124129,0.0021655466,0.08349524],"category_scores_gemma":[0.0042717094,0.00023919785,0.00065699493,0.0008051919,0.0007942754,0.0027425077,0.0033408073,0.0011016489,0.036453053],"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":[0.00053152,0.0001462389,0.0010407371,0.0021820692,0.00012623917,0.0009098097,0.0027444924,0.0013787505,0.05728348,0.06635548,0.1951968,0.6721043],"study_design_scores_gemma":[0.000080440215,0.0003299228,0.0030364536,0.00069050957,0.00011478242,0.0028683033,0.0013324819,0.009030688,0.014076821,0.053758934,0.91454256,0.00013799475],"about_ca_topic_score_codex":0.00094108016,"about_ca_topic_score_gemma":0.0012697551,"teacher_disagreement_score":0.08349524,"about_ca_system_score_codex":0.0006594531,"about_ca_system_score_gemma":0.00061510975,"threshold_uncertainty_score":0.27931935},"labels":[],"label_agreement":null},{"id":"W4256459269","doi":"10.4108/icst.ambisys2008.2882","title":"A Formal model to handle the adaptability of Multimodal User Interfaces","year":2008,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 de Moncton","funders":"","keywords":"Computer science; Adaptability; Property (philosophy); Human–computer interaction; Multimodal interaction; Model checking; Formal methods; Formal verification; User interface; Formal description; Formal specification; Software engineering; Programming language","score_opus":0.041957774805335996,"score_gpt":0.24969196944784108,"score_spread":0.2077341946425051,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256459269","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0031690677,0.00007887211,0.9942986,0.00016867935,0.000049487695,0.00007180455,0.00007310732,0.0010193409,0.0010710828],"genre_scores_gemma":[0.19784257,0.00025039096,0.79710704,0.0002940201,0.00015293619,0.0005863143,0.00050285173,0.0004251332,0.0028386968],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9960967,0.0012244376,0.00038203842,0.0005945922,0.0013717334,0.00033063174],"domain_scores_gemma":[0.9927631,0.004009834,0.0005341056,0.00159781,0.0009334958,0.00016168256],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004491025,0.00086919306,0.0007241795,0.0012819452,0.0012218277,0.0022008554,0.0026902119,0.0016792056,0.00413516],"category_scores_gemma":[0.012337628,0.0010277751,0.0029912756,0.0005709893,0.0027440432,0.0057809455,0.002990333,0.0036204779,0.00065525906],"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":[0.00013752677,0.00014234314,0.0013888243,0.0005101677,0.0001294784,0.0005859941,0.0008838346,0.065824784,0.016455662,0.8598119,0.0028462438,0.051283143],"study_design_scores_gemma":[0.00013738702,0.0002786281,0.00042561995,0.00028910747,0.00020874191,0.0006167158,0.00023479873,0.514436,0.024891317,0.41021416,0.048150875,0.00011653504],"about_ca_topic_score_codex":0.0028492482,"about_ca_topic_score_gemma":0.00229088,"teacher_disagreement_score":0.004491025,"about_ca_system_score_codex":0.0016722908,"about_ca_system_score_gemma":0.0023248552,"threshold_uncertainty_score":0.02375114},"labels":[],"label_agreement":null},{"id":"W4281854806","doi":"10.3233/shti220052","title":"Towards an Adaptive Clinical Transcription System for In-Situ Transcribing of Patient Encounter Information","year":2022,"lang":"en","type":"article","venue":"Studies in health technology and informatics","topic":"Speech and dialogue systems","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":"Izaak Walton Killam Health Centre; Dalhousie University","funders":"Nova Scotia Health Research Foundation","keywords":"Transcription (linguistics); Workflow; Computer science; Recall; Psychology; Database","score_opus":0.06605879334062394,"score_gpt":0.34095783340282854,"score_spread":0.2748990400622046,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4281854806","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":[0.02274133,0.00020907432,0.9479768,0.00059539545,0.00032752746,0.0005985403,0.00057024107,0.025324477,0.0016566964],"genre_scores_gemma":[0.07703538,0.00022756278,0.91369665,0.00036296068,0.0002550773,0.0005028423,0.0018293512,0.00091806543,0.0051720687],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9979473,0.00077397114,0.00022270448,0.00054475304,0.00043672463,0.00007459766],"domain_scores_gemma":[0.99486804,0.0017442782,0.00031905677,0.0007021596,0.0019485264,0.00041791852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0031633961,0.0009147012,0.00050071324,0.00073758006,0.0004251826,0.0017527522,0.0015619647,0.0014480816,0.0059076124],"category_scores_gemma":[0.007297729,0.0004557193,0.00048058963,0.00046264063,0.0007403881,0.0011172493,0.001225135,0.0014004636,0.0069414517],"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":[0.0014153224,0.0003508495,0.0029513228,0.00060524466,0.00008242463,0.000803861,0.0018435507,0.00990087,0.3625298,0.0028528196,0.020537328,0.59612656],"study_design_scores_gemma":[0.0005971109,0.0018751149,0.006992324,0.00032414377,0.00029561247,0.003338857,0.0015706255,0.4909212,0.36463016,0.0074654776,0.12165303,0.00033625547],"about_ca_topic_score_codex":0.001940516,"about_ca_topic_score_gemma":0.0014438041,"teacher_disagreement_score":0.0059076124,"about_ca_system_score_codex":0.0003763298,"about_ca_system_score_gemma":0.0014397872,"threshold_uncertainty_score":0.019762993},"labels":[],"label_agreement":null},{"id":"W4284880418","doi":"10.1017/9781108955638.031","title":"Working Memory and L2 Grammar Development in Children","year":2022,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Speech and dialogue systems","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":"Wilfrid Laurier University","funders":"","keywords":"Grammar; Vocabulary; Working memory; Computer science; Natural language processing; Language acquisition; Verb; Linguistics; Psychology; Artificial intelligence; Cognitive psychology; Cognition; Mathematics education","score_opus":0.018344604798180248,"score_gpt":0.17237809527774586,"score_spread":0.1540334904795656,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4284880418","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":[0.9501542,0.015502017,0.0014739139,0.0013287457,0.000048764607,0.000019262632,0.00047330317,0.00013984338,0.030860001],"genre_scores_gemma":[0.9725901,0.010753128,0.0021916055,0.00025997937,0.000029223896,0.00006622033,0.0003298844,0.000090139474,0.013689692],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9997645,0.000038667535,0.000017737528,0.00006165281,0.000070608694,0.000046820307],"domain_scores_gemma":[0.9991066,0.00047947594,0.00021367306,0.000054855427,0.000070840564,0.0000745425],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058096455,0.0004710569,0.00034505085,0.0008398904,0.00029933255,0.0020170885,0.00037974858,0.00064131676,0.005072413],"category_scores_gemma":[0.0019739603,0.00029855903,0.00035539866,0.0005567555,0.0013090177,0.00133862,0.0010437777,0.0009225234,0.000645869],"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":[0.0005500828,0.0005434269,0.3663913,0.0013375455,0.00017929437,0.010190226,0.06391079,0.0015575315,0.036965135,0.0410678,0.011162129,0.46614483],"study_design_scores_gemma":[0.000046425404,0.00061367126,0.8766656,0.00081872276,0.0001460501,0.010894594,0.008902647,0.00073576916,0.008128075,0.039387,0.053564616,0.00009694847],"about_ca_topic_score_codex":0.005305409,"about_ca_topic_score_gemma":0.005658435,"teacher_disagreement_score":0.005305409,"about_ca_system_score_codex":0.00093235617,"about_ca_system_score_gemma":0.0005529649,"threshold_uncertainty_score":0.016968906},"labels":[],"label_agreement":null},{"id":"W4296671721","doi":"10.48550/arxiv.1607.00070","title":"A Sequence-to-Sequence Model for User Simulation in Spoken Dialogue\\n Systems","year":2016,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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":"Hôtel-Dieu de Montréal","funders":"","keywords":"Computer science; Sequence (biology); Granularity; Action (physics); Encoder; Artificial intelligence; Space (punctuation); Artificial neural network; Human–computer interaction; Natural language processing; Programming language","score_opus":0.20202565006617085,"score_gpt":0.24456067268659143,"score_spread":0.04253502262042058,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4296671721","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09041592,0.0004560993,0.90081334,0.00085823494,0.00012351549,0.00019922882,0.0012424169,0.0031564122,0.0027347803],"genre_scores_gemma":[0.8729133,0.00024170498,0.11735456,0.00027058317,0.0000857865,0.00050633564,0.0017742241,0.0002908992,0.0065626986],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9982377,0.0008876032,0.000103863844,0.00046263714,0.0001868642,0.000121272904],"domain_scores_gemma":[0.99709713,0.0020909796,0.00012555154,0.0002746611,0.00029054075,0.00012126911],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002017055,0.00083609234,0.00091407576,0.0005294154,0.0005232694,0.0011141092,0.0014963911,0.0016167646,0.0034712434],"category_scores_gemma":[0.0063281907,0.0007112524,0.0011123726,0.00043359204,0.00084524706,0.0018277516,0.0013255582,0.0023646734,0.001540465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00054096134,0.00016551801,0.0028285456,0.00012878241,0.00009876163,0.00017510382,0.0007109725,0.906983,0.005810489,0.01814013,0.0027396544,0.061678052],"study_design_scores_gemma":[0.000006637662,0.00002841775,0.000113544666,0.000002746305,0.0000044348794,0.000012434038,0.000008254364,0.9958371,0.0003658888,0.0032883657,0.00032656282,0.000005725046],"about_ca_topic_score_codex":0.013389913,"about_ca_topic_score_gemma":0.015487041,"teacher_disagreement_score":0.013389913,"about_ca_system_score_codex":0.0014091086,"about_ca_system_score_gemma":0.0013918192,"threshold_uncertainty_score":0.026623964},"labels":[],"label_agreement":null},{"id":"W4299434809","doi":"","title":"In and Out of SSA : a Denotational Specification","year":2009,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Speech and dialogue systems","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":"Advanced Micro Devices (Canada)","funders":"","keywords":"Denotational semantics of the Actor model; Computer science; Denotational semantics; Programming language; Semantics (computer science); Operational semantics","score_opus":0.018418064691633623,"score_gpt":0.23417026365933302,"score_spread":0.2157521989676994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4299434809","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":[0.017057633,0.00014564239,0.9644599,0.00047270404,0.00014047051,0.00012633314,0.00044660814,0.002509525,0.014641302],"genre_scores_gemma":[0.66239154,0.0004011284,0.31796384,0.00037928455,0.0003064544,0.0004257056,0.0009337035,0.0036522548,0.013546034],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9962107,0.0014892573,0.00056481326,0.000541569,0.000742019,0.00045169573],"domain_scores_gemma":[0.99479586,0.0028694496,0.0002714258,0.0009669714,0.0009117791,0.00018443132],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0036776615,0.0012864855,0.0012007294,0.0011027472,0.0017591554,0.0054012053,0.0016116688,0.0018509587,0.011250967],"category_scores_gemma":[0.00472528,0.0016866407,0.0021733607,0.0010946946,0.0045260894,0.008506568,0.0038595926,0.003268041,0.0025095397],"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":[0.0001781868,0.00004752362,0.0010870742,0.00029209748,0.000038024802,0.00043258042,0.0032005152,0.0053872787,0.0060998523,0.9613981,0.0021912972,0.019647535],"study_design_scores_gemma":[0.00008961808,0.00016880085,0.0006244831,0.00017162481,0.00028624642,0.0005593332,0.0012370745,0.0655153,0.0231335,0.8362045,0.071901925,0.00010770695],"about_ca_topic_score_codex":0.0019598056,"about_ca_topic_score_gemma":0.0022466541,"teacher_disagreement_score":0.011250967,"about_ca_system_score_codex":0.0009974289,"about_ca_system_score_gemma":0.0017784026,"threshold_uncertainty_score":0.037638247},"labels":[],"label_agreement":null},{"id":"W4301622407","doi":"10.1007/978-1-4939-7131-2_100124","title":"Collaborative Filtering","year":2018,"lang":"en","type":"book-chapter","venue":"","topic":"Speech and dialogue systems","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":"Computer science","score_opus":0.016018676821808683,"score_gpt":0.22592259527784456,"score_spread":0.20990391845603587,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4301622407","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":[0.0011264564,0.005349729,0.86057436,0.0007650847,0.001284186,0.00015042957,0.0004162622,0.0035224818,0.12681088],"genre_scores_gemma":[0.039782014,0.008480067,0.46575463,0.0009653286,0.0017404425,0.0002975336,0.0032431711,0.0016512503,0.47808552],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9980596,0.0002928557,0.00010674274,0.0006234817,0.0008126947,0.00010461977],"domain_scores_gemma":[0.9980882,0.0006166786,0.0000553697,0.00070204743,0.0004745518,0.00006319186],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016567128,0.0017344226,0.0014337035,0.0028177223,0.0017361251,0.0039002467,0.0022967502,0.0022811193,0.051927596],"category_scores_gemma":[0.004525662,0.00071648875,0.0012070322,0.0031675205,0.0010337284,0.0037857958,0.0021435532,0.0019456539,0.047938947],"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":[0.00007039499,0.000067061716,0.00014006806,0.00033955116,0.00006188293,0.00006969945,0.00018580475,0.0024997746,0.0043838443,0.0950303,0.08855889,0.8085927],"study_design_scores_gemma":[0.000023288496,0.000074485666,0.00048550148,0.00023394467,0.000089225156,0.0007532865,0.000121995414,0.03203217,0.014880181,0.14369471,0.8075265,0.00008475347],"about_ca_topic_score_codex":0.0022396978,"about_ca_topic_score_gemma":0.0022812323,"teacher_disagreement_score":0.051927596,"about_ca_system_score_codex":0.000957216,"about_ca_system_score_gemma":0.001101407,"threshold_uncertainty_score":0.17371511},"labels":[],"label_agreement":null},{"id":"W4310244398","doi":"10.5430/wjel.v13n1p92","title":"Voice Assistant as a Modern Contrivance to Acquire Oral Fluency: An Acoustical and Computational Analysis","year":2022,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":14,"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":"Fluency; Computer science; Test (biology); Focus (optics); Mathematics education; Psychology","score_opus":0.009011816638380325,"score_gpt":0.26473776749504707,"score_spread":0.2557259508566668,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4310244398","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41251257,0.0018344304,0.56568605,0.0005014131,0.00022053182,0.00040631232,0.00030341526,0.003064742,0.015470477],"genre_scores_gemma":[0.7314449,0.0009451351,0.25645635,0.00010338838,0.00008934693,0.00021523198,0.00022253548,0.00021431642,0.0103088245],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991549,0.00024358302,0.000048908067,0.0001433362,0.00036094943,0.000048247035],"domain_scores_gemma":[0.99833494,0.0009950347,0.00012424808,0.00011814908,0.00035151842,0.00007604758],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001233191,0.0004621791,0.00044595302,0.0011947346,0.0003285755,0.0015298511,0.0005665532,0.0004812521,0.0035282385],"category_scores_gemma":[0.0027018045,0.00017197232,0.0004364669,0.0006438577,0.00060266966,0.0011279264,0.00064667827,0.00038248437,0.00069891213],"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":[0.0007799159,0.00030929383,0.016443726,0.0006781994,0.00009468711,0.00047005687,0.0019919563,0.003435489,0.16180405,0.0077262353,0.0019634385,0.80430305],"study_design_scores_gemma":[0.00024532128,0.009854528,0.18099836,0.0004558415,0.00065916573,0.007947792,0.009327047,0.3067181,0.36963177,0.01873935,0.0949432,0.00047961864],"about_ca_topic_score_codex":0.0009462021,"about_ca_topic_score_gemma":0.0010199302,"teacher_disagreement_score":0.0035282385,"about_ca_system_score_codex":0.0002905207,"about_ca_system_score_gemma":0.0005216843,"threshold_uncertainty_score":0.01180315},"labels":[],"label_agreement":null},{"id":"W4312850468","doi":"10.1109/hri53351.2022.9889423","title":"More than words: A Framework for Describing Human-Robot Dialog Designs","year":2022,"lang":"en","type":"article","venue":"2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI)","topic":"Speech and dialogue systems","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","funders":"","keywords":"Dialog box; Computer science; Dialog system; Robot; Snapshot (computer storage); Human–computer interaction; Human–robot interaction; Artificial intelligence; Semantic interpretation; Field (mathematics); Natural language processing; World Wide Web; Database","score_opus":0.40053342482858817,"score_gpt":0.42922255097393575,"score_spread":0.028689126145347577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312850468","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":[0.0046342863,0.004277798,0.95001286,0.0024270914,0.00045786417,0.0005757183,0.0017307419,0.0015491635,0.034334473],"genre_scores_gemma":[0.1203208,0.0035016243,0.85197526,0.0012429014,0.00041667034,0.0031341338,0.002988171,0.0011181686,0.015302294],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9908812,0.0052129608,0.0012381685,0.0011242318,0.0011771251,0.00036641923],"domain_scores_gemma":[0.9905946,0.0050799325,0.0011651079,0.0015046857,0.0012631343,0.00039250497],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007948428,0.0029597413,0.0011524315,0.009454814,0.003970016,0.011084275,0.0032568984,0.003662146,0.012148933],"category_scores_gemma":[0.014891268,0.001147945,0.002098079,0.0057741716,0.0075987177,0.022455085,0.0057492484,0.0041290927,0.0056469664],"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":[0.00008540219,0.00004529422,0.0011669329,0.0009604002,0.000038302525,0.0002744409,0.023122612,0.0024167493,0.0021312428,0.887924,0.011575996,0.0702586],"study_design_scores_gemma":[0.000031091007,0.00012164729,0.0008759057,0.0009789856,0.00005004503,0.0011164523,0.010398165,0.013508826,0.0017763625,0.41950858,0.5515191,0.00011480116],"about_ca_topic_score_codex":0.0052998755,"about_ca_topic_score_gemma":0.0040872446,"teacher_disagreement_score":0.012148933,"about_ca_system_score_codex":0.0033799454,"about_ca_system_score_gemma":0.0039902255,"threshold_uncertainty_score":0.042035818},"labels":[],"label_agreement":null},{"id":"W4313024785","doi":"10.1121/10.0015545","title":"SpeakerPool: A remote speech data collection platform","year":2022,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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":"Data collection; Computer science; Mobile device; Software; World Wide Web; Set (abstract data type); Web application; Multimedia; Human–computer interaction; Operating system","score_opus":0.03296708753106537,"score_gpt":0.2621355701566172,"score_spread":0.22916848262555184,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313024785","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":[0.12441771,0.0010987503,0.5408737,0.0012664925,0.00059864484,0.0062609385,0.0476811,0.23768574,0.040116966],"genre_scores_gemma":[0.4137936,0.0011752552,0.44001377,0.0014977095,0.00082711375,0.010710766,0.06559446,0.01673906,0.049648214],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99875903,0.00028638303,0.00010584831,0.00032020384,0.00040016606,0.00012837238],"domain_scores_gemma":[0.9966461,0.0013417234,0.00024433652,0.0006340286,0.0006648474,0.00046886207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002669769,0.0010927832,0.00082710286,0.0017446205,0.00072287355,0.001416005,0.001651611,0.0009078628,0.024364516],"category_scores_gemma":[0.0051301355,0.00050102215,0.0006728874,0.0009310925,0.000613621,0.0024444656,0.003692223,0.001058983,0.012399878],"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":[0.008446386,0.0010690963,0.018841619,0.0032637964,0.00050110376,0.0031491634,0.012393516,0.0029141281,0.1943037,0.009059541,0.16444735,0.58161056],"study_design_scores_gemma":[0.0013700102,0.0028159218,0.10833781,0.00084841734,0.00058123714,0.00354902,0.0042666215,0.062502176,0.14962275,0.0200754,0.6448437,0.0011869422],"about_ca_topic_score_codex":0.001895135,"about_ca_topic_score_gemma":0.00217785,"teacher_disagreement_score":0.024364516,"about_ca_system_score_codex":0.00030341683,"about_ca_system_score_gemma":0.0015205534,"threshold_uncertainty_score":0.081507385},"labels":[],"label_agreement":null},{"id":"W4375868876","doi":"10.1109/icassp49357.2023.10095598","title":"Towards Dialogue Modeling Beyond Text","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Public Health Ontario; University of Toronto","funders":"","keywords":"Conversation; Computer science; Modalities; Component (thermodynamics); Active listening; Multimodality; Modality (human–computer interaction); Multimodal interaction; Natural language processing; Human–computer interaction; Speech recognition; Artificial intelligence; Linguistics; World Wide Web; Communication; Psychology","score_opus":0.03276172241210811,"score_gpt":0.25589980548426905,"score_spread":0.22313808307216093,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4375868876","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.029288663,0.003251923,0.9474506,0.002163465,0.00037922055,0.0003244162,0.004869832,0.0049608657,0.0073110904],"genre_scores_gemma":[0.48311162,0.0014087778,0.4873361,0.001375284,0.0006004706,0.0009342638,0.014102935,0.0010214933,0.010109072],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99699616,0.0015435879,0.0001499251,0.00090530043,0.00026352203,0.00014154948],"domain_scores_gemma":[0.9951899,0.0032125409,0.00033460665,0.00044014183,0.0005672392,0.00025561667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024275663,0.0019015362,0.00078637304,0.0018966566,0.00097957,0.003391983,0.001630756,0.0020628122,0.0042684595],"category_scores_gemma":[0.010261505,0.00052892836,0.0021058735,0.00093822513,0.0007943094,0.005587874,0.0021065911,0.0029399346,0.0023110644],"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":[0.001756215,0.0010459461,0.014651601,0.0023073324,0.0006329713,0.0012107538,0.008118847,0.306083,0.027681533,0.09564075,0.0541154,0.48675573],"study_design_scores_gemma":[0.000040683106,0.00013733968,0.001184321,0.00017868605,0.00009117239,0.00021787014,0.00076925795,0.884875,0.0042131143,0.06532979,0.042913467,0.00004932685],"about_ca_topic_score_codex":0.005859447,"about_ca_topic_score_gemma":0.006647703,"teacher_disagreement_score":0.005859447,"about_ca_system_score_codex":0.0010792336,"about_ca_system_score_gemma":0.0013090326,"threshold_uncertainty_score":0.014279425},"labels":[],"label_agreement":null},{"id":"W4376869336","doi":"10.18280/isi.280220","title":"Spontaneous Speech and Its Features Are Taken into Account When Creating Recognition Programs","year":2023,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Speech and dialogue systems","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":"Speech recognition; Computer science; Natural language processing; Psychology; Linguistics; Philosophy","score_opus":0.02238493823948893,"score_gpt":0.23320606951456707,"score_spread":0.21082113127507815,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4376869336","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":[0.07883795,0.0003788261,0.9121286,0.00016258184,0.00008498478,0.00041621382,0.00030804367,0.0015713784,0.0061113406],"genre_scores_gemma":[0.37213057,0.00067902973,0.6205684,0.0000844422,0.00010532188,0.0009857242,0.0009882746,0.00079713634,0.0036611506],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9952408,0.0024905114,0.00037800174,0.000718699,0.0010742123,0.000097864344],"domain_scores_gemma":[0.9776225,0.01645529,0.0010466169,0.0026316626,0.0021051986,0.00013868629],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0039895144,0.0006558035,0.00061322784,0.0010567412,0.00042855638,0.0026631812,0.00080286316,0.000632258,0.0030881208],"category_scores_gemma":[0.022077436,0.00040915987,0.0004551497,0.0008858425,0.0010364648,0.003938966,0.00094916334,0.0007993593,0.0013374921],"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":[0.0005836825,0.0003280945,0.0069752634,0.0017852519,0.000115885174,0.0005295402,0.0036102084,0.014626582,0.16104393,0.025541482,0.0014606557,0.7833994],"study_design_scores_gemma":[0.00016062887,0.0027517981,0.051747333,0.0006752571,0.0006521732,0.0027647892,0.0041541145,0.22340414,0.55030304,0.06268957,0.10032111,0.00037609393],"about_ca_topic_score_codex":0.00045419103,"about_ca_topic_score_gemma":0.00058488175,"teacher_disagreement_score":0.0039895144,"about_ca_system_score_codex":0.00025916888,"about_ca_system_score_gemma":0.0010189561,"threshold_uncertainty_score":0.021098852},"labels":[],"label_agreement":null},{"id":"W4377966496","doi":"10.32920/23153441","title":"Listenapp: An AI-Based Mobile Application Platform for Auditory Learning","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Faculty of Communication and Design, Ryerson University","keywords":"Computer science; Newspaper; Meaning (existential); Multimedia; Field (mathematics); Class (philosophy); Word (group theory); Style (visual arts); Natural (archaeology); Natural language processing; Human–computer interaction; Speech recognition; Linguistics; Artificial intelligence; Psychology; Advertising","score_opus":0.041706795736136934,"score_gpt":0.3041273478803065,"score_spread":0.26242055214416954,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4377966496","genre_codex":"software","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025999626,0.0011360538,0.39852777,0.001009254,0.0007592729,0.0013235786,0.004822428,0.4559835,0.1104386],"genre_scores_gemma":[0.2758798,0.0017105277,0.28668177,0.002802952,0.00084883603,0.0021486315,0.016474271,0.016982818,0.3964704],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996877,0.00004118303,0.00002275545,0.00005873901,0.00015433,0.00003537667],"domain_scores_gemma":[0.9995454,0.00015004406,0.000026273789,0.00005844664,0.00010012338,0.000119712866],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004649174,0.00094962603,0.00045462415,0.0007681868,0.00053813896,0.0016961908,0.0014950352,0.001042232,0.044987436],"category_scores_gemma":[0.0013136212,0.00032644856,0.00044100356,0.0004192854,0.00033648027,0.0018923655,0.001974305,0.0011306023,0.020746926],"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":[0.0017397995,0.0008311478,0.0019521982,0.0010000875,0.00012446588,0.00226527,0.0020225968,0.0021583894,0.1154073,0.013425926,0.33556703,0.52350575],"study_design_scores_gemma":[0.000584772,0.0011323502,0.007219176,0.0002214852,0.00016965218,0.0022282372,0.00088827737,0.10478696,0.047372844,0.016419556,0.81862056,0.00035617079],"about_ca_topic_score_codex":0.0025413262,"about_ca_topic_score_gemma":0.003405157,"teacher_disagreement_score":0.044987436,"about_ca_system_score_codex":0.00032140224,"about_ca_system_score_gemma":0.0005290338,"threshold_uncertainty_score":0.15049797},"labels":[],"label_agreement":null},{"id":"W4382566950","doi":"10.1007/978-3-031-36336-8_94","title":"Impact of Experiencing Misrecognition by Teachable Agents on Learning and Rapport","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Conversation; Computer science; Teachable moment; Artificial intelligence; Psychology; Communication; Psychotherapist","score_opus":0.06663819570248916,"score_gpt":0.324522156627977,"score_spread":0.2578839609254878,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4382566950","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":[0.98287535,0.00016725824,0.0007655231,0.00031511657,0.00003152036,0.000011684845,0.00005674352,0.000065420485,0.01571138],"genre_scores_gemma":[0.9968399,0.000093669965,0.0005319443,0.000039133232,0.000009709433,0.000009156833,0.000042589418,0.000021472237,0.0024124074],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976266,0.0010430312,0.00008645684,0.00026817265,0.00070628145,0.00026946396],"domain_scores_gemma":[0.9624789,0.030367572,0.0021744915,0.0015468233,0.0012001686,0.0022320698],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015215976,0.0003480885,0.00032599724,0.00027629038,0.0007945051,0.0040570516,0.00097479956,0.0014705159,0.009032683],"category_scores_gemma":[0.027175069,0.00029652988,0.00024791338,0.00028187278,0.001178177,0.0022354852,0.0019295361,0.0020458456,0.0007279727],"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":[0.01362171,0.009930978,0.24833755,0.00087587984,0.0009229783,0.006803156,0.11641682,0.028541062,0.11596178,0.020699263,0.0074890014,0.43039984],"study_design_scores_gemma":[0.0006253,0.01238717,0.6404838,0.00046422242,0.0017314431,0.00533264,0.14618,0.04670141,0.07349587,0.0424497,0.029632956,0.0005154769],"about_ca_topic_score_codex":0.0020825507,"about_ca_topic_score_gemma":0.0028171812,"teacher_disagreement_score":0.009032683,"about_ca_system_score_codex":0.000852163,"about_ca_system_score_gemma":0.00090506865,"threshold_uncertainty_score":0.03021741},"labels":[],"label_agreement":null},{"id":"W4385322332","doi":"10.1109/botse59190.2023.00011","title":"Idiolect: A Reconfigurable Voice Coding Assistant","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; McGill University","funders":"","keywords":"Computer science; Coding (social sciences); Speech recognition; Mathematics","score_opus":0.030539296115488973,"score_gpt":0.25147312033797053,"score_spread":0.22093382422248156,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385322332","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":[0.027066547,0.00027909916,0.84977865,0.0002733318,0.00028648178,0.00027373745,0.00040897104,0.09910952,0.022523692],"genre_scores_gemma":[0.3123623,0.00040979925,0.62117934,0.0008000718,0.00016016289,0.0004928145,0.0016824554,0.0068895854,0.056023527],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992843,0.000121603065,0.000040914594,0.00021169092,0.00025596458,0.0000856035],"domain_scores_gemma":[0.9991424,0.00043550102,0.000056143253,0.00014554801,0.00010095016,0.000119360055],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007524603,0.00066656916,0.00039241323,0.0006159002,0.00051285786,0.0010391264,0.0020653207,0.0009498571,0.011767957],"category_scores_gemma":[0.0022253245,0.00043813518,0.00041164283,0.00020985348,0.0005156988,0.0014884837,0.0021357425,0.0011938404,0.004750463],"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":[0.0012142395,0.00040965658,0.0016647794,0.00063761335,0.00006436903,0.0018972511,0.002014855,0.010647167,0.13819446,0.02599334,0.044540495,0.77272177],"study_design_scores_gemma":[0.00042098886,0.00071231456,0.0022220602,0.00023121854,0.00015361913,0.005297516,0.00094475085,0.26359308,0.1763914,0.0131964795,0.53649735,0.00033919976],"about_ca_topic_score_codex":0.0010239898,"about_ca_topic_score_gemma":0.001167811,"teacher_disagreement_score":0.011767957,"about_ca_system_score_codex":0.00040367988,"about_ca_system_score_gemma":0.0006646107,"threshold_uncertainty_score":0.039367735},"labels":[],"label_agreement":null},{"id":"W4385436799","doi":"10.48550/arxiv.2307.15508","title":"The Road to Quality is Paved with Good Revisions: A Detailed Evaluation Methodology for Revision Policies in Incremental Sequence Labelling","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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":"Atomic Energy of Canada Limited","keywords":"Computer science; Prefix; Sequence (biology); Labelling; Encoder; Quality (philosophy); Transformer; Engineering","score_opus":0.47321015250608517,"score_gpt":0.34796481321220585,"score_spread":0.12524533929387932,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385436799","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":[0.06971976,0.00068458414,0.9215406,0.00059826375,0.00009689932,0.0005092267,0.00047644624,0.0037995987,0.002574626],"genre_scores_gemma":[0.5629856,0.00025313662,0.4337156,0.0001819533,0.00005359002,0.00032582865,0.0007421185,0.00073291495,0.0010091782],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9565759,0.022703635,0.0043635927,0.0042416104,0.010840137,0.0012751193],"domain_scores_gemma":[0.8043579,0.11969041,0.014460171,0.030629702,0.026610494,0.0042513753],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03696633,0.0014689539,0.0014026819,0.0035079347,0.0011510596,0.004875186,0.0027438358,0.0026910922,0.0018502234],"category_scores_gemma":[0.18250252,0.0009141341,0.0009671108,0.0023691978,0.0031155962,0.0074333497,0.0037102534,0.0033028868,0.0006586924],"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":[0.0020645552,0.0008168959,0.03500763,0.0012895295,0.00048375575,0.0002383675,0.0036929771,0.27951226,0.02609744,0.06097334,0.0052248067,0.5845985],"study_design_scores_gemma":[0.00010570265,0.0012795402,0.005973633,0.00016533204,0.0001403243,0.00026979894,0.00039434194,0.9134632,0.030270992,0.043114316,0.004668292,0.00015459007],"about_ca_topic_score_codex":0.0065641007,"about_ca_topic_score_gemma":0.0070784255,"teacher_disagreement_score":0.03696633,"about_ca_system_score_codex":0.0038983577,"about_ca_system_score_gemma":0.004215342,"threshold_uncertainty_score":0.195499},"labels":[],"label_agreement":null},{"id":"W4385573049","doi":"10.18653/v1/2022.emnlp-main.195","title":"Improving Multi-turn Emotional Support Dialogue Generation with Lookahead Strategy Planning","year":2022,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Université de Montréal; Canadian Institute for Advanced Research","funders":"Hong Kong Polytechnic University; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canadian Institute for Advanced Research","keywords":"Conversation; Computer science; Heuristics; Turn-taking; Facial expression; Human–computer interaction; Term (time); Artificial intelligence; Psychology","score_opus":0.04671185926340579,"score_gpt":0.2549916835519332,"score_spread":0.2082798242885274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385573049","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.11762409,0.0015445581,0.85062426,0.00048883975,0.00026341065,0.0005041447,0.0004055663,0.021930452,0.0066147023],"genre_scores_gemma":[0.66234934,0.00024615056,0.33218077,0.00030494313,0.00006308655,0.00034606358,0.0008629353,0.0004085535,0.003238155],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999243,0.0002277525,0.000051258266,0.0002467613,0.0001570564,0.00007426273],"domain_scores_gemma":[0.9984817,0.00089638395,0.000074512296,0.0001637315,0.00026212021,0.000121569836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011068592,0.0014315882,0.00093248097,0.000598231,0.00044432338,0.0010134634,0.0013487256,0.0010772938,0.0037039255],"category_scores_gemma":[0.0041232575,0.00041502173,0.0005880197,0.00031408295,0.0003455135,0.0012912232,0.0013874902,0.0011984931,0.0013300678],"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":[0.0017036279,0.0010684369,0.0035967187,0.0006325261,0.00019560664,0.00042901043,0.001281727,0.10999342,0.08675262,0.0036637844,0.011407698,0.7792748],"study_design_scores_gemma":[0.00014509159,0.0002887809,0.00072012417,0.000017806933,0.000061026476,0.0001349685,0.00015694936,0.9763638,0.01587135,0.001930683,0.004266212,0.000043154287],"about_ca_topic_score_codex":0.0040857117,"about_ca_topic_score_gemma":0.004590082,"teacher_disagreement_score":0.0040857117,"about_ca_system_score_codex":0.00047095076,"about_ca_system_score_gemma":0.0010672758,"threshold_uncertainty_score":0.012390852},"labels":[],"label_agreement":null},{"id":"W4385573378","doi":"10.18653/v1/2022.gem-1.44","title":"Improving Dialogue Act Recognition with Augmented Data","year":2022,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Minnow Environmental (Canada)","funders":"","keywords":"Dialog box; Ambiguity; Computer science; Dialog system; Artificial intelligence; Natural language processing; Human–computer interaction; Speech recognition; Machine learning; World Wide Web","score_opus":0.04641892614692756,"score_gpt":0.2345474553222367,"score_spread":0.18812852917530914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385573378","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.28027356,0.002244631,0.6861462,0.0011034241,0.0009673009,0.000503742,0.005618636,0.015516852,0.0076256855],"genre_scores_gemma":[0.7213004,0.00034076997,0.2627865,0.00036218372,0.00019604206,0.00042581666,0.011422108,0.00024314488,0.0029229636],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99054027,0.0058025126,0.00047286635,0.0017007805,0.0011552994,0.00032818684],"domain_scores_gemma":[0.9683164,0.019426627,0.0012347468,0.006093225,0.0044135866,0.00051545637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006545817,0.0022416615,0.0017185909,0.0016008195,0.0006397134,0.003181068,0.0018078578,0.0017896447,0.0039140168],"category_scores_gemma":[0.032086473,0.00075244886,0.0013453868,0.0009845528,0.0008325141,0.0036618554,0.0032943757,0.0032023157,0.0034086544],"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":[0.0018019597,0.0020949738,0.020385642,0.0010391871,0.00077372824,0.00040469362,0.0013271963,0.205456,0.063003756,0.0031999664,0.0132290395,0.6872838],"study_design_scores_gemma":[0.00004761667,0.0004301539,0.0042288164,0.000067901005,0.0000777591,0.00019196693,0.0003055541,0.9571178,0.027226578,0.0029334633,0.0072715688,0.00010089769],"about_ca_topic_score_codex":0.0035274925,"about_ca_topic_score_gemma":0.0050030965,"teacher_disagreement_score":0.006545817,"about_ca_system_score_codex":0.0005941319,"about_ca_system_score_gemma":0.001140117,"threshold_uncertainty_score":0.03461796},"labels":[],"label_agreement":null},{"id":"W4385574182","doi":"10.18653/v1/2022.findings-emnlp.318","title":"Controllable Dialogue Simulation with In-context Learning","year":2022,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Vector Institute; University of Waterloo","funders":"Defense Advanced Research Projects Agency","keywords":"Dialogic; Computer science; Crowdsourcing; Context (archaeology); Annotation; Fluency; Set (abstract data type); Workflow; Artificial intelligence; Training set; Language model; Code (set theory); Natural language processing; Machine learning; World Wide Web; Database; Programming language; Linguistics","score_opus":0.010786972541543092,"score_gpt":0.21468725496401686,"score_spread":0.20390028242247377,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385574182","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04389942,0.00060260994,0.927799,0.00038267157,0.00019667274,0.00046591164,0.00095424603,0.021566657,0.004132788],"genre_scores_gemma":[0.5373822,0.00020467154,0.45194948,0.0005165374,0.00008889029,0.001517587,0.003367996,0.0011299722,0.0038426802],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99586797,0.0023330892,0.0001455233,0.0011944494,0.00029393483,0.00016506785],"domain_scores_gemma":[0.99461854,0.0035251759,0.00019363605,0.0010137414,0.00035453693,0.00029436397],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030137198,0.00218367,0.0011878653,0.0007532222,0.00085986854,0.0015939736,0.0032803644,0.001457603,0.004845552],"category_scores_gemma":[0.013339839,0.00092633185,0.0014422972,0.0004109402,0.0012583769,0.0030075812,0.0044026747,0.0028522129,0.0025395984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001466592,0.0012548624,0.0077264807,0.001311417,0.00034573794,0.0006393966,0.002706057,0.50069296,0.05066367,0.01436672,0.022029065,0.39679706],"study_design_scores_gemma":[0.00008863014,0.00014858462,0.00043287626,0.00003579042,0.000025883965,0.00009069708,0.00018300097,0.97119576,0.00997306,0.010492769,0.0072927247,0.000040306237],"about_ca_topic_score_codex":0.0029436215,"about_ca_topic_score_gemma":0.005776855,"teacher_disagreement_score":0.004845552,"about_ca_system_score_codex":0.0009384576,"about_ca_system_score_gemma":0.00140474,"threshold_uncertainty_score":0.01621002},"labels":[],"label_agreement":null},{"id":"W4385786281","doi":"","title":"ON THE USE OF LINGUISTIC FEATURES IN AN AUTOMATIC SYSTEM FOR SPEECH ANALYTICS OF TELEPHONE CONVERSATIONS","year":2011,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Computer science; Analytics; Natural language processing; Speech recognition; Speech corpus; Linguistics; Speech synthesis; Data science","score_opus":0.04479030691898692,"score_gpt":0.2359495362847823,"score_spread":0.19115922936579538,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4385786281","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":[0.53542984,0.00060827896,0.4455931,0.00096160686,0.00019750225,0.00044551646,0.0010966442,0.008230176,0.007437404],"genre_scores_gemma":[0.8306657,0.00018822556,0.16453522,0.00023333635,0.000087266955,0.0001518499,0.00076171366,0.0005355858,0.0028411269],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9984982,0.00061503565,0.00013411859,0.00031772687,0.00031254723,0.00012238076],"domain_scores_gemma":[0.9878221,0.009693177,0.0002928752,0.00059956295,0.0014373615,0.00015488967],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023934415,0.00055038,0.00055161625,0.0010590607,0.00087594334,0.0024456764,0.00083187333,0.0011114432,0.002377393],"category_scores_gemma":[0.011297614,0.00035625751,0.00049583055,0.00069276977,0.000537343,0.002641217,0.0009625371,0.00077867904,0.0012804125],"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":[0.0029743165,0.0005674953,0.0108060045,0.0002716151,0.00013458052,0.00058818527,0.00093772914,0.012514412,0.23676626,0.0028031797,0.0041287695,0.7275075],"study_design_scores_gemma":[0.00012978425,0.0009866656,0.022266429,0.000074216536,0.0002955041,0.00058831996,0.0005951856,0.7807689,0.1846966,0.0032944072,0.006172897,0.00013107451],"about_ca_topic_score_codex":0.0064539826,"about_ca_topic_score_gemma":0.006470598,"teacher_disagreement_score":0.0064539826,"about_ca_system_score_codex":0.00041456186,"about_ca_system_score_gemma":0.00052433816,"threshold_uncertainty_score":0.01283282},"labels":[],"label_agreement":null},{"id":"W4386576630","doi":"10.18653/v1/2023.findings-eacl.25","title":"PREME: Preference-based Meeting Exploration through an Interactive Questionnaire","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Preference; Correctness; Task (project management); Computer science; Work (physics); Volume (thermodynamics); Human–computer interaction; Data science; Multimedia; Engineering","score_opus":0.1111433524017075,"score_gpt":0.30098103721625463,"score_spread":0.18983768481454713,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386576630","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":[0.04757226,0.000113417926,0.91773176,0.00016449603,0.000060644703,0.0022655025,0.003327616,0.025387088,0.0033773181],"genre_scores_gemma":[0.23291726,0.000102064376,0.75151855,0.00013899326,0.00004731006,0.0037961684,0.005145761,0.0016208875,0.00471298],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9910075,0.0060349107,0.00045783352,0.00089131395,0.0012891055,0.00031932924],"domain_scores_gemma":[0.9725276,0.01993045,0.0012365774,0.0027934762,0.0026604629,0.00085147924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007845612,0.0017552334,0.0008410733,0.001722181,0.00041067626,0.0016460199,0.0018764203,0.0010167592,0.012184653],"category_scores_gemma":[0.03034258,0.0005787958,0.0007652154,0.0008241515,0.00046152752,0.002238706,0.0026614505,0.00081064453,0.0053441986],"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":[0.003838583,0.0018758015,0.0164299,0.0027375827,0.000292356,0.0008829944,0.011181242,0.015487332,0.10331382,0.008412011,0.037358474,0.7981898],"study_design_scores_gemma":[0.0011339069,0.005660086,0.056935593,0.00058294315,0.000269232,0.0017499581,0.006968292,0.61208594,0.129085,0.027052997,0.15758587,0.0008901911],"about_ca_topic_score_codex":0.0006751392,"about_ca_topic_score_gemma":0.0011619267,"teacher_disagreement_score":0.012184653,"about_ca_system_score_codex":0.00039274056,"about_ca_system_score_gemma":0.00073858834,"threshold_uncertainty_score":0.041492045},"labels":[],"label_agreement":null},{"id":"W4386576775","doi":"10.18653/v1/2023.eacl-srw.12","title":"Automatic Dialog Flow Extraction and Guidance","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Fundação para a Ciência e a Tecnologia; Programa Operacional Regional do Centro; Atomic Energy of Canada Limited","keywords":"Dialog box; Computer science; Dialog system; Human–computer interaction; Natural language; Service (business); Artificial intelligence; Portuguese; Representation (politics); Order (exchange); Information extraction; World Wide Web; Natural language processing","score_opus":0.018492300910543408,"score_gpt":0.26011281206639,"score_spread":0.24162051115584657,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386576775","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":[0.048105545,0.0014830794,0.87861305,0.00060218334,0.00019471586,0.0008481435,0.0089482125,0.05396981,0.007235238],"genre_scores_gemma":[0.22114462,0.0007397598,0.7489702,0.00013330473,0.000120367404,0.0005430294,0.018706154,0.0012711422,0.008371421],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99815744,0.00044331735,0.00014876586,0.0007346391,0.00034645153,0.0001693117],"domain_scores_gemma":[0.9971455,0.0015138752,0.00025972442,0.0003497071,0.0005976456,0.0001335922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014879671,0.0022224826,0.0011513914,0.0066429377,0.0013140435,0.0019846635,0.0011618282,0.001335215,0.008012877],"category_scores_gemma":[0.005783873,0.00061039627,0.0010771306,0.0019983754,0.0004847853,0.0022899539,0.0017648678,0.0013116471,0.004724928],"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":[0.0006837475,0.0002497737,0.003906686,0.0010918025,0.000058829417,0.00027592693,0.0016721041,0.0041828607,0.044538837,0.0069911485,0.025897672,0.9104505],"study_design_scores_gemma":[0.00020359442,0.0005021141,0.025614208,0.00072250084,0.0002466217,0.001327672,0.0045661633,0.5432741,0.18081765,0.057147656,0.18529722,0.00028056806],"about_ca_topic_score_codex":0.0063176565,"about_ca_topic_score_gemma":0.0075937174,"teacher_disagreement_score":0.008012877,"about_ca_system_score_codex":0.0008121515,"about_ca_system_score_gemma":0.0024957743,"threshold_uncertainty_score":0.026805818},"labels":[],"label_agreement":null},{"id":"W4387782006","doi":"10.1145/3622758.3622885","title":"programmingLanguage as Language;","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Marsden Fund; Royal Society Te Apārangi","keywords":"Computer science; Natural language processing; Programming language","score_opus":0.00983375967666655,"score_gpt":0.268335720750555,"score_spread":0.25850196107388845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4387782006","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":[0.0027482554,0.044124596,0.43268448,0.037385095,0.006760475,0.0002819914,0.0019844645,0.0069580316,0.4670725],"genre_scores_gemma":[0.2867418,0.054052554,0.34671617,0.026230315,0.012106978,0.0023026424,0.0063626957,0.009634053,0.25585285],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99354047,0.0031542953,0.00047268652,0.0011872078,0.0013242872,0.0003210425],"domain_scores_gemma":[0.9943541,0.0028281335,0.0005113482,0.0011082188,0.0009002914,0.0002978998],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003949507,0.0016874077,0.0011685648,0.0023288059,0.0022974692,0.012801969,0.0022499184,0.0029370973,0.025777858],"category_scores_gemma":[0.010109079,0.000779212,0.0007404358,0.004325955,0.0107750185,0.02204729,0.004943858,0.00872166,0.012503963],"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":[0.000011022612,0.0000069392227,0.00005341313,0.0001573657,0.000007680521,0.000052342773,0.00051625347,0.00018038403,0.00013434618,0.95401555,0.02592013,0.018944679],"study_design_scores_gemma":[0.000009435258,0.0000060516745,0.000051064977,0.000116221854,0.0000067268506,0.00016028828,0.00017655893,0.00064900506,0.00024205279,0.45003963,0.54853064,0.000012328215],"about_ca_topic_score_codex":0.003171594,"about_ca_topic_score_gemma":0.001451037,"teacher_disagreement_score":0.9742221,"about_ca_system_score_codex":0.0038432705,"about_ca_system_score_gemma":0.0037386795,"threshold_uncertainty_score":0.08623546},"labels":[],"label_agreement":null},{"id":"W4388213222","doi":"10.32920/24488803","title":"Voice familiarity in an interactive voice-reminders app for elderly care recipients and their family caregivers","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Psychology; Qualitative research; S Voice; Medicine; Nursing; Computer science","score_opus":0.04485251354302356,"score_gpt":0.2901395936979332,"score_spread":0.24528708015490963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388213222","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":[0.995131,0.00017628394,0.0026491007,0.00013580361,0.000024383891,0.00016938403,0.000039756687,0.0001901438,0.0014841291],"genre_scores_gemma":[0.9872953,0.0002033461,0.010923027,0.00012403572,0.0000526216,0.00027771413,0.000054694643,0.000032434007,0.001036757],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9987974,0.0007239307,0.00009081533,0.000097789205,0.00021220716,0.00007788097],"domain_scores_gemma":[0.9909108,0.007660594,0.0005265506,0.00022894322,0.000350444,0.0003225444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00232553,0.00036002087,0.00032020334,0.00028234994,0.00047968983,0.0010012854,0.00039646387,0.000537831,0.0032186285],"category_scores_gemma":[0.012512073,0.00021208262,0.00036929097,0.00013885483,0.00020596379,0.0011087154,0.0011002655,0.0002985348,0.00040523155],"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":[0.0082527,0.007609475,0.07971138,0.002920531,0.00029788603,0.0023071738,0.059786268,0.0012070502,0.09073102,0.00041787402,0.0061053885,0.7406533],"study_design_scores_gemma":[0.002742632,0.072690144,0.6734742,0.0017780353,0.004384087,0.0073766387,0.06795484,0.018625539,0.10744976,0.0014728337,0.04136061,0.0006906866],"about_ca_topic_score_codex":0.00044362847,"about_ca_topic_score_gemma":0.00084667903,"teacher_disagreement_score":0.0032186285,"about_ca_system_score_codex":0.0001705191,"about_ca_system_score_gemma":0.00031549076,"threshold_uncertainty_score":0.012298763},"labels":[],"label_agreement":null},{"id":"W4388213547","doi":"10.32920/24488803.v1","title":"Voice familiarity in an interactive voice-reminders app for elderly care recipients and their family caregivers","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Psychology; Qualitative research; Interactive voice response; S Voice; Medicine; Nursing; Computer science","score_opus":0.04485251354302356,"score_gpt":0.2901395936979332,"score_spread":0.24528708015490963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388213547","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":[0.995131,0.00017628394,0.0026491007,0.00013580361,0.000024383891,0.00016938403,0.000039756687,0.0001901438,0.0014841291],"genre_scores_gemma":[0.9872953,0.0002033461,0.010923027,0.00012403572,0.0000526216,0.00027771413,0.000054694643,0.000032434007,0.001036757],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9987974,0.0007239307,0.00009081533,0.000097789205,0.00021220716,0.00007788097],"domain_scores_gemma":[0.9909108,0.007660594,0.0005265506,0.00022894322,0.000350444,0.0003225444],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00232553,0.00036002087,0.00032020334,0.00028234994,0.00047968983,0.0010012854,0.00039646387,0.000537831,0.0032186285],"category_scores_gemma":[0.012512073,0.00021208262,0.00036929097,0.00013885483,0.00020596379,0.0011087154,0.0011002655,0.0002985348,0.00040523155],"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":[0.0082527,0.007609475,0.07971138,0.002920531,0.00029788603,0.0023071738,0.059786268,0.0012070502,0.09073102,0.00041787402,0.0061053885,0.7406533],"study_design_scores_gemma":[0.002742632,0.072690144,0.6734742,0.0017780353,0.004384087,0.0073766387,0.06795484,0.018625539,0.10744976,0.0014728337,0.04136061,0.0006906866],"about_ca_topic_score_codex":0.00044362847,"about_ca_topic_score_gemma":0.00084667903,"teacher_disagreement_score":0.0032186285,"about_ca_system_score_codex":0.0001705191,"about_ca_system_score_gemma":0.00031549076,"threshold_uncertainty_score":0.012298763},"labels":[],"label_agreement":null},{"id":"W4388547027","doi":"10.1108/jdal-11-2022-0010","title":"A survey of technologies supporting design of a multimodal interactive robot for military communication","year":2023,"lang":"en","type":"article","venue":"Journal of Defense Analytics and Logistics","topic":"Speech and dialogue systems","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":"Defence Research and Development Canada","funders":"","keywords":"Human–computer interaction; Computer science; Robot; Key (lock); Field (mathematics); Multimodality; Set (abstract data type); Systems engineering; Engineering; Data science; Artificial intelligence; World Wide Web","score_opus":0.08824007566765671,"score_gpt":0.3268137406571464,"score_spread":0.2385736649894897,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4388547027","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":[0.023356874,0.20855188,0.6455083,0.001012069,0.0005190795,0.00041414943,0.00053471525,0.0041373,0.11596565],"genre_scores_gemma":[0.19320007,0.26009682,0.49752712,0.0010110025,0.0002848201,0.00081996317,0.0014627547,0.00094286766,0.04465449],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99886453,0.00022144907,0.00009569264,0.00022083409,0.0005251005,0.00007241019],"domain_scores_gemma":[0.9982444,0.00092462817,0.00018101673,0.00020416995,0.00039214932,0.00005376236],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012123678,0.001008005,0.0006675393,0.002461331,0.00049777376,0.0018817085,0.001602018,0.0013674208,0.011599843],"category_scores_gemma":[0.0027587884,0.0007685573,0.00083459826,0.0015197637,0.00047753486,0.0029022594,0.0009362672,0.0008318202,0.0049598394],"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":[0.00008882281,0.000060763334,0.0008386089,0.0048061963,0.000046014444,0.0002143646,0.0005344159,0.002885286,0.026701577,0.010880277,0.005348067,0.9475957],"study_design_scores_gemma":[0.000021362655,0.0009486305,0.004648148,0.004763418,0.00022850509,0.0030489522,0.0011269038,0.019039884,0.052635934,0.009118929,0.90423244,0.00018693312],"about_ca_topic_score_codex":0.0007774057,"about_ca_topic_score_gemma":0.00080623454,"teacher_disagreement_score":0.011599843,"about_ca_system_score_codex":0.0006165554,"about_ca_system_score_gemma":0.00065829454,"threshold_uncertainty_score":0.038805306},"labels":[],"label_agreement":null},{"id":"W4389084365","doi":"10.1121/10.0023128","title":"The effect of perceived human-likeness on voice-user interface–directed speech","year":2023,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Vowel; Voice; Voice-onset time; Consonant; Speech recognition; Quality (philosophy); Duration (music); Formant; Psychology; Computer science; Audiology; Acoustics; Physics","score_opus":0.012396342638490054,"score_gpt":0.27529642156381434,"score_spread":0.2629000789253243,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389084365","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":[0.9962379,0.00015804471,0.0014279764,0.000026150934,0.000010185054,0.00004340555,0.000087114015,0.000037778205,0.001971409],"genre_scores_gemma":[0.9984055,0.0000570429,0.0011212213,0.000024110675,0.0000073818114,0.000029755767,0.0000646974,0.000017144495,0.00027309946],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9971727,0.0013165697,0.00024247255,0.0005140689,0.00064736285,0.00010679465],"domain_scores_gemma":[0.95308334,0.037065115,0.0043745013,0.0017965944,0.0024131662,0.0012672654],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030126008,0.0003330996,0.00025491917,0.00037956637,0.00024170108,0.0013665063,0.00026341883,0.00038078465,0.002930879],"category_scores_gemma":[0.030933792,0.00025299905,0.0003290733,0.00020601075,0.0006224396,0.00063785777,0.00093617797,0.0003979336,0.00027638944],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0068578376,0.00095452566,0.5835186,0.0016370793,0.0010153119,0.0007750151,0.029520182,0.0018418714,0.24832867,0.0004698907,0.0007155158,0.12436547],"study_design_scores_gemma":[0.00002502848,0.0014862934,0.99017334,0.000031556876,0.00008886052,0.00024777887,0.0017926727,0.0009067975,0.004558521,0.00012269149,0.0005300877,0.000036407786],"about_ca_topic_score_codex":0.00078915316,"about_ca_topic_score_gemma":0.0009963955,"teacher_disagreement_score":0.0030126008,"about_ca_system_score_codex":0.00023613333,"about_ca_system_score_gemma":0.00014942151,"threshold_uncertainty_score":0.015932322},"labels":[],"label_agreement":null},{"id":"W4389523717","doi":"10.18653/v1/2023.emnlp-main.290","title":"Mirages. On Anthropomorphism in Dialogue Systems","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":49,"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":"Engineering and Physical Sciences Research Council; European Commission; Leverhulme Trust","keywords":"Transparency (behavior); Unconscious mind; Computer science; Natural (archaeology); Human–computer interaction; Psychology; Computer security","score_opus":0.03080043570966766,"score_gpt":0.2594030610480685,"score_spread":0.2286026253384008,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389523717","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.031401973,0.0121024,0.47605798,0.043652184,0.0018649952,0.0002424058,0.00021770589,0.0026561255,0.4318042],"genre_scores_gemma":[0.7196876,0.005405252,0.14834383,0.006279282,0.002266789,0.00057588913,0.00027771931,0.0012155247,0.11594821],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9916333,0.00559391,0.00039195767,0.0009330668,0.001130184,0.00031748845],"domain_scores_gemma":[0.98517585,0.010540821,0.00083056965,0.0021702894,0.0008015798,0.0004808963],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00526063,0.0007515115,0.00049677526,0.001619241,0.0037945781,0.0062681646,0.0010988682,0.003624727,0.017911514],"category_scores_gemma":[0.017976426,0.00076025317,0.00094412145,0.00076939113,0.010743263,0.014785124,0.009019806,0.0051043276,0.0032131027],"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":[0.00008446676,0.000023459577,0.00061186065,0.0001784846,0.000012981842,0.0003746687,0.010268661,0.0009635273,0.0012323603,0.9370151,0.0063585746,0.042875838],"study_design_scores_gemma":[0.000047725352,0.00012535976,0.001006236,0.00041554705,0.000032762884,0.0014870672,0.0032164734,0.011870506,0.0032859922,0.5305795,0.447862,0.00007087442],"about_ca_topic_score_codex":0.0016591698,"about_ca_topic_score_gemma":0.0012319161,"teacher_disagreement_score":0.017911514,"about_ca_system_score_codex":0.0017326782,"about_ca_system_score_gemma":0.0007377329,"threshold_uncertainty_score":0.059920013},"labels":[],"label_agreement":null},{"id":"W4389786288","doi":"10.4006/0836-1398-36.4.464","title":"On the propagation of light and the existence of physical distances","year":2023,"lang":"en","type":"article","venue":"Physics Essays","topic":"Speech and dialogue systems","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":"Fallacy; Physics; Classical mechanics; Speed of light (cellular automaton); Theoretical physics; Physical system; Optics; Quantum mechanics; Epistemology; Philosophy","score_opus":0.019475109879501493,"score_gpt":0.23793061075247243,"score_spread":0.21845550087297094,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4389786288","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":[0.03438377,0.01195077,0.30995506,0.10022916,0.005178263,0.00012084846,0.00030386253,0.00024141253,0.5376368],"genre_scores_gemma":[0.8137717,0.008836538,0.098135404,0.01322746,0.0037656382,0.0004100575,0.00025360213,0.0003243005,0.061275337],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9937583,0.0029143344,0.00040395636,0.0009781672,0.0014777336,0.0004674897],"domain_scores_gemma":[0.970058,0.0237665,0.0013104002,0.0016604519,0.0026850319,0.0005195087],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009997819,0.00075010204,0.00082900637,0.0017830534,0.0064539644,0.0073788133,0.002103275,0.0054153916,0.009003816],"category_scores_gemma":[0.025699837,0.0009525887,0.0010670725,0.0011209138,0.034835897,0.02172158,0.006265896,0.011681112,0.002272761],"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":[0.0000132665255,0.0000048936577,0.00004127164,0.000026195874,0.0000024143094,0.00005653514,0.0005893515,0.00009876749,0.00009252333,0.996837,0.0009372349,0.0013005829],"study_design_scores_gemma":[0.000012832128,0.000015197429,0.00015064997,0.00009044185,0.000010467007,0.00010381835,0.00056894816,0.00060911436,0.000523858,0.964331,0.03356365,0.00002010132],"about_ca_topic_score_codex":0.002897387,"about_ca_topic_score_gemma":0.0013426438,"teacher_disagreement_score":0.009997819,"about_ca_system_score_codex":0.003372507,"about_ca_system_score_gemma":0.0019597795,"threshold_uncertainty_score":0.052874148},"labels":[],"label_agreement":null},{"id":"W4390912761","doi":"10.21437/speechprosody.2010-250","title":"Relative prosodic boundary strength and prior bias in disambiguation","year":2010,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":36,"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":"Social Sciences and Humanities Research Council of Canada; Universität Potsdam","keywords":"Computer science; Natural language processing; Artificial intelligence; Boundary (topology); Speech recognition; Mathematics","score_opus":0.022896547163558406,"score_gpt":0.2562313677071357,"score_spread":0.23333482054357732,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4390912761","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":[0.9414263,0.0008734379,0.02549118,0.0006296362,0.0000859444,0.000052839292,0.000066793145,0.00019745101,0.031176457],"genre_scores_gemma":[0.9938066,0.00013276181,0.0051824246,0.00013435842,0.00003883793,0.000019125224,0.000043741933,0.00009230005,0.0005499202],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9977223,0.00091333705,0.00016901564,0.00052957475,0.0005530632,0.000112714806],"domain_scores_gemma":[0.98181903,0.013651357,0.001711436,0.00130862,0.0008012184,0.0007083173],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044093034,0.00036986984,0.00040551752,0.001109391,0.0007051821,0.0030632932,0.0006180666,0.0009973039,0.0071750474],"category_scores_gemma":[0.031729273,0.00085431634,0.00029498525,0.0005586796,0.0028103443,0.0043133814,0.0030481538,0.0017002474,0.00078528683],"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":[0.0032177074,0.0004889138,0.07632135,0.0010453152,0.0002573558,0.0012601786,0.012059909,0.008054905,0.6512215,0.08867549,0.0014148586,0.15598257],"study_design_scores_gemma":[0.0003564128,0.001399141,0.6152653,0.0002899971,0.00040431027,0.0028856501,0.004167264,0.03101388,0.07471929,0.26465547,0.0044583525,0.000384868],"about_ca_topic_score_codex":0.00047555953,"about_ca_topic_score_gemma":0.0006382971,"teacher_disagreement_score":0.0071750474,"about_ca_system_score_codex":0.0005446219,"about_ca_system_score_gemma":0.000347949,"threshold_uncertainty_score":0.02400297},"labels":[],"label_agreement":null},{"id":"W4391824156","doi":"10.1101/2024.02.13.580071","title":"The Lab Streaming Layer for Synchronized Multimodal Recording","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":100,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital","funders":"","keywords":"Layer (electronics); Computer science; Application layer; Streaming current; Operating system; Materials science; Nanotechnology","score_opus":0.017131536497271425,"score_gpt":0.23691149251364801,"score_spread":0.2197799560163766,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391824156","genre_codex":"methods","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":[0.015456728,0.00083053,0.8522982,0.0010838492,0.00057156634,0.00092945114,0.002877214,0.09855739,0.02739506],"genre_scores_gemma":[0.30368257,0.0019184065,0.6237478,0.0031702104,0.00087190105,0.0031273596,0.011122295,0.009540323,0.042819194],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9986021,0.00015350078,0.00012792683,0.00026062023,0.0007027885,0.00015294096],"domain_scores_gemma":[0.99798787,0.0003740192,0.0001663204,0.000518024,0.00071035995,0.00024345865],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019372533,0.0010576189,0.00066691707,0.0013411746,0.0005513455,0.0021499977,0.0026738911,0.0008875491,0.03431246],"category_scores_gemma":[0.0040837913,0.0005721314,0.0005481006,0.0007116456,0.0006178472,0.003064955,0.0036824867,0.0014617376,0.012361392],"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":[0.0017436738,0.00038272465,0.004003535,0.0012083288,0.0001836319,0.0010558361,0.0008246411,0.007036541,0.36244452,0.04037438,0.156508,0.42423418],"study_design_scores_gemma":[0.0002953087,0.00073836686,0.003791673,0.0004751281,0.00016426707,0.0014583007,0.00025855307,0.19732212,0.29035607,0.02137183,0.4833549,0.00041349424],"about_ca_topic_score_codex":0.0015351343,"about_ca_topic_score_gemma":0.001502272,"teacher_disagreement_score":0.03431246,"about_ca_system_score_codex":0.0012253813,"about_ca_system_score_gemma":0.001604918,"threshold_uncertainty_score":0.114786625},"labels":[],"label_agreement":null},{"id":"W4391831724","doi":"10.4995/eurocall2023.2023.16997","title":"Writing with automatic speech recognition: Examining user’s behaviours and text quality (lexical diversity)","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Computer science; Lexical diversity; Diversity (politics); Exploratory research; Quality (philosophy); Speech recognition; Natural language processing; Human–computer interaction; Linguistics; Vocabulary","score_opus":0.1041953918260542,"score_gpt":0.28978383341101427,"score_spread":0.18558844158496007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391831724","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":[0.99867225,0.00003352548,0.000809663,0.000010826674,0.00000124234,0.000018431623,0.000022050024,0.000011237964,0.00042083292],"genre_scores_gemma":[0.99745864,0.000052736195,0.001917326,0.000018550689,0.0000034008299,0.00003547063,0.000056156554,0.000006074546,0.0004516551],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984579,0.0007372687,0.00015919119,0.00021962581,0.00032959995,0.000096427444],"domain_scores_gemma":[0.9870148,0.007918,0.0024560972,0.0006233004,0.0014772265,0.0005106483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017802998,0.00036473625,0.00035637696,0.00069263804,0.00031072542,0.0011578348,0.00024437445,0.00045949093,0.0011713348],"category_scores_gemma":[0.016625313,0.00021810312,0.0002504918,0.00034245092,0.00041806232,0.0009431474,0.0006841391,0.00031897696,0.0004540341],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0016493232,0.0006444208,0.62069917,0.0006870201,0.00019867597,0.00077411515,0.090478435,0.00068330474,0.124196425,0.00016461723,0.0003562939,0.15946825],"study_design_scores_gemma":[0.000050716146,0.0034385335,0.94317514,0.00007423992,0.00008729399,0.0016166497,0.032214683,0.0036502623,0.013441102,0.0003056397,0.0018350978,0.00011063077],"about_ca_topic_score_codex":0.000641487,"about_ca_topic_score_gemma":0.0010486116,"teacher_disagreement_score":0.0017802998,"about_ca_system_score_codex":0.00017361763,"about_ca_system_score_gemma":0.00017444602,"threshold_uncertainty_score":0.009415269},"labels":[],"label_agreement":null},{"id":"W4391831852","doi":"10.4995/eurocall2023.2023.16979","title":"Beyond the walls of classrooms: Exploring the pedagogical effectiveness of Text-To-Speech-based Shadowing (TTS-S) on the development of Mandarin tones","year":2023,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Mandarin Chinese; Pronunciation; Task (project management); Perception; Speech production; Psychology; Production (economics); Metacognition; Computer science; Speech recognition; Linguistics; Cognition; Engineering","score_opus":0.12396470880494669,"score_gpt":0.3111726444556165,"score_spread":0.1872079356506698,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391831852","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":[0.99832314,0.00008790145,0.000780598,0.00003260767,0.000003977791,0.000044937344,0.0000056464473,0.000011289153,0.00070986775],"genre_scores_gemma":[0.9933583,0.0002111655,0.0058283405,0.000031083146,0.000012318426,0.00008993245,0.000014574935,0.000005424971,0.0004487607],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9981292,0.0011039829,0.00011053171,0.00025221266,0.00027078114,0.00013331538],"domain_scores_gemma":[0.98990345,0.008352525,0.0006989756,0.00034116668,0.00026113677,0.00044275838],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029882863,0.00033116335,0.00043055936,0.00033369305,0.00038285795,0.0008052637,0.0005071331,0.00049272284,0.0015492006],"category_scores_gemma":[0.009933145,0.00021151315,0.0003381288,0.00018736065,0.0005103204,0.0007021493,0.00091494754,0.0003924475,0.00025773302],"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":[0.0035061517,0.013018601,0.07019582,0.0021154087,0.00024027984,0.0009776473,0.054199066,0.0030374452,0.16716011,0.0011325419,0.00047358917,0.68394333],"study_design_scores_gemma":[0.0013690685,0.12762119,0.558592,0.0009752213,0.0013302626,0.0017408252,0.048330512,0.012524192,0.22107984,0.003211862,0.023018315,0.00020660493],"about_ca_topic_score_codex":0.00037889174,"about_ca_topic_score_gemma":0.0008489192,"teacher_disagreement_score":0.0029882863,"about_ca_system_score_codex":0.00025544662,"about_ca_system_score_gemma":0.00068128895,"threshold_uncertainty_score":0.015803814},"labels":[],"label_agreement":null},{"id":"W4392337651","doi":"10.1016/j.eswa.2024.123484","title":"An NLP-based system for modulating virtual experiences using speech instructions","year":2024,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Speech and dialogue systems","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 Ottawa","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence; Speech recognition","score_opus":0.02394420026868275,"score_gpt":0.289669436656138,"score_spread":0.2657252363874552,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4392337651","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.10422771,0.00045298375,0.7756534,0.00033814568,0.0006149305,0.0016127959,0.0029259368,0.094557896,0.019616231],"genre_scores_gemma":[0.47652632,0.0003305977,0.485688,0.00083062256,0.00023041612,0.003206979,0.0032596553,0.0032718827,0.026655592],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99961156,0.0000984785,0.000040407635,0.00012003048,0.00010341148,0.000026111435],"domain_scores_gemma":[0.99884653,0.00068034604,0.000054113498,0.00011503286,0.00019689629,0.00010701299],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00064172054,0.00082963903,0.0005832821,0.00060961396,0.00032092,0.0009001083,0.0010850726,0.00095011014,0.027096057],"category_scores_gemma":[0.003027881,0.00028075997,0.00023154421,0.00030434274,0.00028690058,0.00088430254,0.0011694394,0.00056494656,0.0067282994],"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":[0.0033215275,0.0004742733,0.001551456,0.00090652064,0.00007355738,0.0007046617,0.0011532246,0.0024631857,0.35657078,0.0026709468,0.018893838,0.61121595],"study_design_scores_gemma":[0.0020133248,0.0027181206,0.02634716,0.00043341494,0.000571215,0.0026089866,0.00084485265,0.4036514,0.42900765,0.009325634,0.121988624,0.0004895992],"about_ca_topic_score_codex":0.0008650256,"about_ca_topic_score_gemma":0.0008141083,"teacher_disagreement_score":0.027096057,"about_ca_system_score_codex":0.0002731018,"about_ca_system_score_gemma":0.00037217527,"threshold_uncertainty_score":0.09064537},"labels":[],"label_agreement":null},{"id":"W4393146392","doi":"10.1609/aaai.v38i20.30612","title":"Your Prompt Is My Command: On Assessing the Human-Centred Generality of Multimodal Models (Abstract Reprint)","year":2024,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Speech and dialogue systems","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":"Reprint; Generality; Computer science; Cognitive science; Psychology; Human–computer interaction; Psychotherapist; Physics","score_opus":0.212102811081108,"score_gpt":0.3623498035420163,"score_spread":0.15024699246090828,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393146392","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":[0.86181605,0.0017614416,0.10231178,0.0021642712,0.00014843246,0.0010344114,0.00044591932,0.0006136691,0.029704047],"genre_scores_gemma":[0.9681341,0.00038736252,0.029867979,0.00026730984,0.00003410372,0.00026773615,0.00019115946,0.00008002968,0.0007702029],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9857896,0.010263138,0.00064538984,0.0012460898,0.0017855251,0.00027029274],"domain_scores_gemma":[0.7550524,0.21783079,0.006753521,0.011795117,0.0063880347,0.002180208],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03715419,0.0006531034,0.0004528305,0.0019153921,0.0009237094,0.0054210755,0.0008951942,0.0016649908,0.004553299],"category_scores_gemma":[0.24521537,0.00040371894,0.0006354268,0.0011424735,0.004111698,0.008624887,0.0051652826,0.001721463,0.0006139264],"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":[0.008052161,0.0014373712,0.18198344,0.0031748463,0.0007639152,0.0005966981,0.077035695,0.0681271,0.019275552,0.0592889,0.011996742,0.5682676],"study_design_scores_gemma":[0.0005029057,0.008309297,0.35484344,0.0025607815,0.00069884903,0.0015802418,0.058317833,0.3457135,0.023309072,0.1740206,0.029135182,0.0010083667],"about_ca_topic_score_codex":0.001941232,"about_ca_topic_score_gemma":0.0019015897,"teacher_disagreement_score":0.03715419,"about_ca_system_score_codex":0.0016481552,"about_ca_system_score_gemma":0.0005307523,"threshold_uncertainty_score":0.19649243},"labels":[],"label_agreement":null},{"id":"W4393148525","doi":"10.1609/aaai.v38i5.28272","title":"SeTformer Is What You Need for Vision and Language","year":2024,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Speech and dialogue systems","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":"École de Technologie Supérieure","funders":"Vetenskapsrådet; Knut och Alice Wallenbergs Stiftelse","keywords":"Computer science; Linguistics; Philosophy","score_opus":0.05020884113658372,"score_gpt":0.3140827375632839,"score_spread":0.2638738964267002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393148525","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":[0.0051322337,0.0025254765,0.8307467,0.017940173,0.0026929874,0.00024114265,0.0034687938,0.09138823,0.04586418],"genre_scores_gemma":[0.11625134,0.0036319795,0.7336235,0.014165932,0.0013955523,0.00053506525,0.00850285,0.016833395,0.10506035],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99899894,0.00018105443,0.000063497675,0.00024592166,0.0003843116,0.00012629635],"domain_scores_gemma":[0.99774265,0.0005092188,0.00009158777,0.0009038027,0.0005332197,0.00021957756],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015641416,0.0024135308,0.0011563788,0.00096044666,0.0008997554,0.0044011157,0.0025328335,0.0023383207,0.09233],"category_scores_gemma":[0.008125362,0.0012695532,0.0015571964,0.0010256119,0.0014354748,0.011248251,0.0037614394,0.004365063,0.07900098],"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":[0.00043321398,0.0001238016,0.0009841636,0.00047960124,0.00010676192,0.0003033371,0.00031741904,0.0050002458,0.027063342,0.038528793,0.28265655,0.64400274],"study_design_scores_gemma":[0.00012702074,0.0002654798,0.0012840623,0.00028069684,0.00012066981,0.0010146489,0.00036945674,0.08380991,0.04852415,0.14345756,0.7205676,0.00017866968],"about_ca_topic_score_codex":0.0041272873,"about_ca_topic_score_gemma":0.0064679254,"teacher_disagreement_score":0.09233,"about_ca_system_score_codex":0.0012380925,"about_ca_system_score_gemma":0.0016972489,"threshold_uncertainty_score":0.30887467},"labels":[],"label_agreement":null},{"id":"W4393436843","doi":"10.5281/zenodo.3866267","title":"Best practice templates for tephra collection, analysis, and correlation","year":2020,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Speech and dialogue systems","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":"Tephra; Template; Computer science; Geology; Paleontology; Volcano; Programming language","score_opus":0.028949176731381775,"score_gpt":0.26105868930795273,"score_spread":0.23210951257657095,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393436843","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":[0.0015725241,0.00029340512,0.043053675,0.0006817415,0.00024819127,0.00081675634,0.90233785,0.04584837,0.0051475056],"genre_scores_gemma":[0.0024231856,0.00016005308,0.03937523,0.00017310122,0.000030262418,0.002000673,0.95219904,0.0023108697,0.0013276062],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9935694,0.0015114404,0.001706765,0.0016210525,0.0011824005,0.00040899668],"domain_scores_gemma":[0.98158115,0.0039901193,0.001083453,0.008796763,0.0038655568,0.0006829679],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007949609,0.002546902,0.00124867,0.0054801735,0.0010430466,0.003576919,0.0036467025,0.0024707525,0.026103163],"category_scores_gemma":[0.033933036,0.0013580369,0.0019327116,0.00715709,0.00082049443,0.0034847786,0.004479862,0.0026886822,0.059749704],"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":[0.00022728076,0.00008176928,0.002705003,0.0011255168,0.000066775254,0.00011447091,0.00021649218,0.0019278247,0.0016917711,0.0037625674,0.95519614,0.0328843],"study_design_scores_gemma":[0.00026632892,0.00003272094,0.0037177375,0.00032663526,0.000031418487,0.00016800601,0.00018971095,0.007439365,0.0039200685,0.008411684,0.9754204,0.00007579387],"about_ca_topic_score_codex":0.013184855,"about_ca_topic_score_gemma":0.029410148,"teacher_disagreement_score":0.026103163,"about_ca_system_score_codex":0.0019924187,"about_ca_system_score_gemma":0.0045749913,"threshold_uncertainty_score":0.087323785},"labels":[],"label_agreement":null},{"id":"W4394672802","doi":"10.1145/3613905.3650921","title":"Chart What I Say: Exploring Cross-Modality Prompt Alignment in AI-Assisted Chart Authoring","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Mitacs; University of Toronto","keywords":"Computer science; Chart; Modality (human–computer interaction); Variety (cybernetics); Focus (optics); Affordance; Natural language processing; Interface (matter); User interface; Spoken language; Artificial intelligence; Human–computer interaction; Programming language","score_opus":0.09878289714193828,"score_gpt":0.33179760244848694,"score_spread":0.23301470530654866,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394672802","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.41609806,0.0003430041,0.5575028,0.0005570571,0.00015571014,0.000770756,0.00053875527,0.009317796,0.014716034],"genre_scores_gemma":[0.7453572,0.000105364896,0.24940498,0.00024336958,0.000034986027,0.00041850214,0.0005054379,0.0005717383,0.0033584202],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99504244,0.0033884358,0.0001670645,0.0007062777,0.00052951905,0.00016629849],"domain_scores_gemma":[0.969242,0.026312463,0.0010404235,0.0013619062,0.0015010929,0.00054205675],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005693353,0.0006499704,0.00047452626,0.00067018636,0.00067954004,0.0030074697,0.001276764,0.0011061108,0.0061783334],"category_scores_gemma":[0.04175932,0.00029844462,0.00042419054,0.00069194334,0.0012167848,0.0036322316,0.0027229232,0.0011619007,0.0010512453],"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":[0.004297441,0.0014729785,0.016799157,0.002003734,0.00012372833,0.0019045076,0.07767075,0.02859535,0.22566634,0.01861768,0.0057230033,0.61712533],"study_design_scores_gemma":[0.0007498949,0.0030427612,0.028168702,0.0005408197,0.00033945678,0.0012819862,0.03131686,0.59058166,0.20663749,0.0659095,0.070927374,0.00050338457],"about_ca_topic_score_codex":0.0013933828,"about_ca_topic_score_gemma":0.0019038972,"teacher_disagreement_score":0.0061783334,"about_ca_system_score_codex":0.000669876,"about_ca_system_score_gemma":0.0009475743,"threshold_uncertainty_score":0.030109644},"labels":[],"label_agreement":null},{"id":"W4396650996","doi":"10.1145/3640457.3688142","title":"Bayesian Optimization with LLM-Based Acquisition Functions for Natural Language Preference Elicitation","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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 Toronto; University of Waterloo","funders":"","keywords":"Preference elicitation; Preference; Computer science; Bayesian optimization; Natural language; Natural (archaeology); Artificial intelligence; Natural language processing; Mathematics; Statistics; Biology","score_opus":0.01651333121361138,"score_gpt":0.24805292120653533,"score_spread":0.23153958999292396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396650996","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005004246,0.00009230257,0.9928306,0.0002487753,0.0000093576355,0.000095041774,0.000054867694,0.00035920492,0.0013055948],"genre_scores_gemma":[0.2920647,0.00018505631,0.70138925,0.00073161843,0.000061658175,0.0010982039,0.00044191844,0.00033148786,0.0036960985],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9953868,0.0028192697,0.00020566651,0.0005823818,0.00073906087,0.0002669316],"domain_scores_gemma":[0.9835112,0.013852147,0.0005963223,0.0007322693,0.00097559625,0.00033249625],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00600427,0.0015820835,0.0016941985,0.0011659486,0.0007120683,0.0016836671,0.0023853863,0.0019852,0.006728468],"category_scores_gemma":[0.031987276,0.0010629877,0.0012473013,0.0011402125,0.0017598046,0.003680911,0.0034411456,0.0037469119,0.0015487772],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00043105686,0.00034543767,0.0028425374,0.00039822052,0.00012618455,0.00019521825,0.00073351053,0.6784489,0.0041853506,0.10178427,0.0050961827,0.20541315],"study_design_scores_gemma":[0.000024442572,0.0000479433,0.00012874836,0.000021586506,0.000008766718,0.000021485948,0.000028942852,0.96905065,0.00070290966,0.029213766,0.00073630374,0.000014474869],"about_ca_topic_score_codex":0.0050135255,"about_ca_topic_score_gemma":0.007720393,"teacher_disagreement_score":0.006728468,"about_ca_system_score_codex":0.001955719,"about_ca_system_score_gemma":0.0028134328,"threshold_uncertainty_score":0.031754017},"labels":[],"label_agreement":null},{"id":"W4396844176","doi":"10.1145/3589335.3651940","title":"ConvSDG: Session Data Generation for Conversational Search","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 de Montréal","funders":"","keywords":"Session (web analytics); Computer science; Information retrieval; World Wide Web","score_opus":0.17225527286408823,"score_gpt":0.35394881837973374,"score_spread":0.1816935455156455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396844176","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.022533253,0.0013691733,0.89929193,0.0004423804,0.0002841382,0.00070615974,0.0051840493,0.06618715,0.0040016808],"genre_scores_gemma":[0.26111284,0.00041490552,0.70275545,0.00078189594,0.0002267899,0.0016854533,0.020121984,0.0033925888,0.00950808],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989692,0.0003500635,0.00005588935,0.00035395188,0.0001791713,0.00009172529],"domain_scores_gemma":[0.99855036,0.0005881355,0.000052107833,0.0004856533,0.00023506235,0.00008866073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020878967,0.0014359013,0.0011964896,0.0015008057,0.00056926237,0.0008535758,0.0030980087,0.0015522506,0.0076860297],"category_scores_gemma":[0.005390718,0.00057851063,0.0012457655,0.0010643607,0.0006735971,0.0018397673,0.0024860485,0.0017126293,0.00473797],"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":[0.00079704757,0.0005164839,0.0022569394,0.0006689282,0.00021135072,0.0002820697,0.0006122119,0.0640495,0.023631241,0.0071862703,0.09914016,0.8006478],"study_design_scores_gemma":[0.00017747283,0.00019847487,0.0006831224,0.00003113698,0.000047064383,0.00022733869,0.00012470064,0.9468686,0.014649766,0.013553793,0.023386175,0.000052373085],"about_ca_topic_score_codex":0.00824831,"about_ca_topic_score_gemma":0.016869033,"teacher_disagreement_score":0.00824831,"about_ca_system_score_codex":0.0009445133,"about_ca_system_score_gemma":0.0014618217,"threshold_uncertainty_score":0.025712311},"labels":[],"label_agreement":null},{"id":"W4396883611","doi":"10.31234/osf.io/uc6d4","title":"Prompting sometimes invokes expert-like downward shifts in multimodal models’ conceptual hierarchies","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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; Psychology; Cognitive psychology; Epistemology; Cognitive science; Philosophy","score_opus":0.04430763271231802,"score_gpt":0.27350978364924466,"score_spread":0.22920215093692664,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4396883611","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":[0.9754111,0.000065403976,0.01757871,0.00017995662,0.00002247053,0.00006255286,0.000066985645,0.0012166718,0.005396063],"genre_scores_gemma":[0.9874516,0.00003303135,0.010763151,0.00016290804,0.000006960318,0.000068357025,0.0001441585,0.00010018496,0.0012696546],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99847335,0.00054177304,0.000102762075,0.0003906033,0.0003680485,0.00012349857],"domain_scores_gemma":[0.99140465,0.0050253314,0.0007756791,0.0018730296,0.00034599623,0.0005752907],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016684328,0.00048340007,0.00031783222,0.00022681206,0.0002616048,0.00076888804,0.0007104743,0.0012316251,0.0057647545],"category_scores_gemma":[0.016096039,0.00032420582,0.0002505238,0.0001094899,0.0005667136,0.0016503629,0.0017695113,0.0012223311,0.0008437772],"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":[0.00084716745,0.0004482005,0.027809763,0.00043794155,0.000036833193,0.0012863228,0.008539209,0.0019298182,0.89844406,0.003384297,0.0020746668,0.054761652],"study_design_scores_gemma":[0.0003646295,0.005960173,0.30495998,0.00016793868,0.00016673525,0.0065448643,0.00890102,0.061900903,0.54815453,0.02609314,0.03648376,0.00030228877],"about_ca_topic_score_codex":0.00064277527,"about_ca_topic_score_gemma":0.0009791488,"teacher_disagreement_score":0.0057647545,"about_ca_system_score_codex":0.0004371406,"about_ca_system_score_gemma":0.000296948,"threshold_uncertainty_score":0.019285023},"labels":[],"label_agreement":null},{"id":"W4398682455","doi":"10.7910/dvn/66hucd/igm3lb","title":"Turk Talk screenshots for tutorial.docx","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Speech and dialogue systems","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":"","keywords":"Computer science; Natural language processing; Artificial intelligence; Natural language","score_opus":0.027081709475199115,"score_gpt":0.2572203606394673,"score_spread":0.23013865116426818,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4398682455","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":[0.00016696908,0.00004826908,0.00014610795,0.00008362371,0.00010907596,0.00005902501,0.99440867,0.0020714838,0.0029066694],"genre_scores_gemma":[0.00049432425,0.000034449076,0.0004115421,0.000078469646,0.000035385947,0.00032290188,0.993397,0.00045165574,0.0047742496],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99882954,0.00023491718,0.0001096351,0.00029596142,0.0002535595,0.0002762763],"domain_scores_gemma":[0.9954228,0.0011055379,0.00018715276,0.0013125626,0.0014131013,0.00055888516],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0017760289,0.0030660785,0.0016366169,0.0044059134,0.0015929571,0.0032540346,0.0025826478,0.0015167465,0.4390105],"category_scores_gemma":[0.008838817,0.0007686133,0.0013219663,0.004628538,0.00060341053,0.0019214848,0.0032028398,0.0015870165,0.51789606],"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":[0.000022736565,0.000011706169,0.000087282606,0.00009702446,0.0000033261967,0.000004010908,0.0000068254917,0.000021677677,0.00003513065,0.0000672088,0.9985285,0.0011146673],"study_design_scores_gemma":[0.00021837706,0.00003806873,0.002879316,0.00022532025,0.000015610522,0.000063734646,0.00018160483,0.00038343586,0.0007593102,0.0009337747,0.9942674,0.00003415151],"about_ca_topic_score_codex":0.014078406,"about_ca_topic_score_gemma":0.038758013,"teacher_disagreement_score":0.5609895,"about_ca_system_score_codex":0.0013979359,"about_ca_system_score_gemma":0.0020106588,"threshold_uncertainty_score":0.8001834},"labels":[],"label_agreement":null},{"id":"W4399157779","doi":"10.1515/9781399522700","title":"Human Spoken Interaction as a Complex Adaptive System","year":2024,"lang":"en","type":"book","venue":"Edinburgh University Press eBooks","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":2,"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; Communication; Psychology","score_opus":0.045047258023292416,"score_gpt":0.2404503170206278,"score_spread":0.1954030589973354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399157779","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":[0.8722716,0.00062349404,0.05795727,0.0012238426,0.00003236401,0.00014543356,0.0003545853,0.0004729479,0.06691852],"genre_scores_gemma":[0.9888216,0.00011326238,0.0072599724,0.00005326681,0.0000057154716,0.00006195941,0.00009041223,0.00003312715,0.0035606704],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9991098,0.00038348907,0.00003388295,0.00016281243,0.00023769835,0.00007234437],"domain_scores_gemma":[0.9983724,0.0009807688,0.0001456021,0.00019648796,0.0001866073,0.00011821572],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00061428663,0.00015588169,0.00014168223,0.0008711909,0.0009001739,0.0033341076,0.00042456295,0.0005246331,0.0030492884],"category_scores_gemma":[0.003707762,0.00021295474,0.00015778086,0.00078669493,0.0031034932,0.0024917226,0.0016993524,0.0005821782,0.00049931085],"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":[0.00025126387,0.00017282195,0.123256736,0.0004685957,0.00013967454,0.0021081509,0.2620703,0.01268412,0.067796715,0.25117514,0.0056175618,0.2742589],"study_design_scores_gemma":[0.00005523815,0.0005649777,0.39396113,0.00046271426,0.00010308544,0.0027764235,0.1660139,0.069712035,0.013567723,0.20557527,0.14690739,0.00030017243],"about_ca_topic_score_codex":0.006725967,"about_ca_topic_score_gemma":0.0041990364,"teacher_disagreement_score":0.006725967,"about_ca_system_score_codex":0.001184166,"about_ca_system_score_gemma":0.0010551473,"threshold_uncertainty_score":0.013373613},"labels":[],"label_agreement":null},{"id":"W4399353928","doi":"10.1145/3626772.3657670","title":"Retrieval-Augmented Conversational Recommendation with Prompt-based Semi-Structured Natural Language State Tracking","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Toronto; University of Waterloo","funders":"","keywords":"Computer science; Natural language; Tracking (education); Natural (archaeology); Natural language processing; Artificial intelligence; State (computer science); Information retrieval; Programming language","score_opus":0.00979204426577812,"score_gpt":0.24361842729328542,"score_spread":0.2338263830275073,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4399353928","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":[0.037965618,0.00071527186,0.77112615,0.00043495034,0.00026341225,0.00066545274,0.0035439166,0.17628069,0.009004529],"genre_scores_gemma":[0.3115868,0.00027122267,0.6607686,0.00074866985,0.00014851958,0.0010307946,0.008314926,0.0025574383,0.014573011],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9980813,0.0007163146,0.00011688464,0.0006885104,0.0003104313,0.000086558466],"domain_scores_gemma":[0.99599093,0.0023925058,0.0002350991,0.0006166211,0.000571235,0.00019362678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019653582,0.0012771756,0.0010165612,0.00089097855,0.00053169,0.0014034456,0.0020877863,0.0012989431,0.006238982],"category_scores_gemma":[0.008478286,0.0005723321,0.000644997,0.0004862079,0.00044492356,0.0020113133,0.0018908565,0.0013427186,0.0058405832],"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":[0.0027105096,0.0007699908,0.004869639,0.0014958446,0.00029864197,0.0010431171,0.004131103,0.016737523,0.15505995,0.0070601143,0.06866965,0.73715395],"study_design_scores_gemma":[0.0004474035,0.0007582842,0.0037354112,0.00013958044,0.0002325581,0.0009751998,0.00081792055,0.81867456,0.080173634,0.014673013,0.07896127,0.00041112234],"about_ca_topic_score_codex":0.005055902,"about_ca_topic_score_gemma":0.0066118157,"teacher_disagreement_score":0.006238982,"about_ca_system_score_codex":0.0006375563,"about_ca_system_score_gemma":0.0009807639,"threshold_uncertainty_score":0.0208714},"labels":[],"label_agreement":null},{"id":"W4400142541","doi":"10.1145/3643834.3661596","title":"Does the Medium Matter? An Exploration of Voice-Interaction for Self-Explanations","year":2024,"lang":"en","type":"article","venue":"Designing Interactive Systems Conference","topic":"Speech and dialogue systems","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":"Computer science; Human–computer interaction","score_opus":0.06532379079561065,"score_gpt":0.3188612129080173,"score_spread":0.2535374221124066,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400142541","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":[0.9513266,0.0060191196,0.027673451,0.0024944916,0.000088853594,0.00026247484,0.00004715146,0.00008516541,0.012002645],"genre_scores_gemma":[0.99376124,0.00080687256,0.0047262134,0.0001037331,0.000020837237,0.00006156155,0.000012541338,0.00001228709,0.0004946581],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9911073,0.0071028345,0.0002979755,0.00028264348,0.0009005206,0.00030876207],"domain_scores_gemma":[0.8798478,0.11319564,0.0033218453,0.001144602,0.0017332301,0.00075688935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.013525415,0.0003871359,0.00045693223,0.0013571732,0.00091605267,0.0051423158,0.00074497116,0.0009718575,0.002814055],"category_scores_gemma":[0.03991797,0.00022488782,0.00070753886,0.00093951094,0.0019944287,0.0049163555,0.0017291995,0.0006987326,0.00019884139],"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":[0.002178276,0.00068515894,0.13418527,0.0046952483,0.00021680183,0.0016369657,0.2098274,0.00089909433,0.017786017,0.04994057,0.0010091779,0.57694006],"study_design_scores_gemma":[0.0007584579,0.009385184,0.3046325,0.009485337,0.0020921763,0.007510349,0.38393262,0.025878591,0.040298834,0.08970754,0.12587908,0.00043935818],"about_ca_topic_score_codex":0.00032868923,"about_ca_topic_score_gemma":0.00080073497,"teacher_disagreement_score":0.013525415,"about_ca_system_score_codex":0.00117099,"about_ca_system_score_gemma":0.001235758,"threshold_uncertainty_score":0.071530044},"labels":[],"label_agreement":null},{"id":"W4400285552","doi":"10.1121/10.0027725","title":"Real-time speech adaptations in conversations between human interlocutor and AI confederate","year":2024,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Communication; Adaptation (eye); Linguistics; Speech recognition; Psychology","score_opus":0.01713585071168028,"score_gpt":0.2741816383475904,"score_spread":0.25704578763591013,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400285552","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":[0.99626356,0.00013248359,0.0016831622,0.00002712357,0.000007818788,0.000025706984,0.000069543225,0.000034446297,0.0017561397],"genre_scores_gemma":[0.9972453,0.000060887167,0.0018903599,0.000044204142,0.000005761028,0.00002783967,0.00008420067,0.000012054664,0.00062929874],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99902093,0.00038017164,0.000038458827,0.0002473331,0.00021872288,0.0000942987],"domain_scores_gemma":[0.99821115,0.00085228356,0.00031029765,0.00014544315,0.00031174507,0.0001690059],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063611876,0.00026426077,0.00018608183,0.0004101989,0.0004982157,0.00096806587,0.0003330539,0.0005893315,0.0012207923],"category_scores_gemma":[0.006004754,0.00020306266,0.0001397008,0.0002019551,0.0008957317,0.0005210298,0.0009732595,0.00029330936,0.00034427276],"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":[0.0019670248,0.00017733232,0.14449926,0.0006445835,0.00016868369,0.0025349956,0.1523446,0.0018935085,0.60431504,0.0009910621,0.0010997099,0.08936412],"study_design_scores_gemma":[0.000037650407,0.0009182694,0.8672012,0.000116755764,0.00012806662,0.0028085702,0.06579881,0.006507284,0.046597272,0.0010076434,0.00863123,0.00024711704],"about_ca_topic_score_codex":0.004250155,"about_ca_topic_score_gemma":0.007738972,"teacher_disagreement_score":0.004250155,"about_ca_system_score_codex":0.00032990574,"about_ca_system_score_gemma":0.00029423586,"threshold_uncertainty_score":0.008450866},"labels":[],"label_agreement":null},{"id":"W4400285708","doi":"10.1121/10.0027726","title":"A new experimental design to study speech adaptations in spontaneous human-computer conversations","year":2024,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech and dialogue systems","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":"Computer science; Adaptation (eye); Linguistics; Speech recognition; Communication; Psychology; Philosophy; Neuroscience","score_opus":0.02954341382724935,"score_gpt":0.29002422113277615,"score_spread":0.2604808073055268,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400285708","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":[0.3273187,0.0010990846,0.5842985,0.0009326516,0.00370847,0.062160857,0.0017301915,0.0011812774,0.017570267],"genre_scores_gemma":[0.2656692,0.0005883212,0.5216858,0.0011109861,0.0005502068,0.20312767,0.0006395113,0.000325158,0.0063031213],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99161196,0.004060927,0.0010862169,0.0015913787,0.0011789756,0.00047052503],"domain_scores_gemma":[0.97981447,0.012548034,0.0016197037,0.0032982233,0.0018292688,0.0008903237],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00859006,0.00175795,0.0009445156,0.00073287304,0.0012910505,0.0014748535,0.0017817349,0.0020959377,0.01300275],"category_scores_gemma":[0.019310575,0.0009907995,0.0010006693,0.0004567783,0.0021343234,0.0015673424,0.0025932996,0.0023028564,0.001369814],"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":[0.025441179,0.0354247,0.0054554236,0.008763245,0.0005630372,0.00089826726,0.009337737,0.0066776224,0.65829897,0.052442435,0.005471769,0.19122553],"study_design_scores_gemma":[0.031968154,0.2844536,0.03437562,0.0014602192,0.0023889595,0.002198455,0.0033649756,0.035248626,0.2850773,0.08278389,0.2355505,0.00112969],"about_ca_topic_score_codex":0.0003097399,"about_ca_topic_score_gemma":0.00041439274,"teacher_disagreement_score":0.01300275,"about_ca_system_score_codex":0.00080589857,"about_ca_system_score_gemma":0.0016265552,"threshold_uncertainty_score":0.04542911},"labels":[],"label_agreement":null},{"id":"W4400373483","doi":"10.48550/arxiv.2407.00463","title":"Open-Source Conversational AI with SpeechBrain 1.0","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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":"Alliance de recherche numérique du Canada; Samsung; Grand Équipement National De Calcul Intensif; Natural Sciences and Engineering Research Council of Canada; Baidu","keywords":"Open source; Computer science; World Wide Web; Natural language processing; Programming language; Software","score_opus":0.056874365557047335,"score_gpt":0.19337369873693402,"score_spread":0.1364993331798867,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400373483","genre_codex":"software","genre_gemma":"software","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"software","genre_consensus":"software","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0058352207,0.000987958,0.25295547,0.00052284455,0.00081115484,0.0005309956,0.0167203,0.70139015,0.0202459],"genre_scores_gemma":[0.14382203,0.0013656479,0.48078516,0.0013987948,0.00053383183,0.0029953748,0.1396709,0.17983402,0.049594153],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9979867,0.0005601537,0.00016961741,0.00045787837,0.00064202136,0.00018350458],"domain_scores_gemma":[0.99643373,0.0015571674,0.00012025061,0.000796243,0.00073333975,0.00035931508],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024393084,0.0033508807,0.0014793398,0.0013663813,0.0010162712,0.0021232106,0.005594788,0.0019375198,0.053560425],"category_scores_gemma":[0.01239026,0.0016427321,0.0018967711,0.0009681378,0.0010406174,0.0041484986,0.00561056,0.0046502473,0.040317923],"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":[0.0016447192,0.00046154726,0.0013759743,0.004325867,0.0004655209,0.0006728843,0.0015764477,0.030396478,0.015634667,0.01856494,0.67586595,0.24901506],"study_design_scores_gemma":[0.0005844366,0.0003552705,0.0018065574,0.00044467338,0.00016819699,0.0007834753,0.00036895,0.3675368,0.034221858,0.047248125,0.54602504,0.00045668494],"about_ca_topic_score_codex":0.008724002,"about_ca_topic_score_gemma":0.008101835,"teacher_disagreement_score":0.053560425,"about_ca_system_score_codex":0.0009244666,"about_ca_system_score_gemma":0.0026267325,"threshold_uncertainty_score":0.17917746},"labels":[],"label_agreement":null},{"id":"W4401023814","doi":"10.24963/ijcai.2024/870","title":"Attention-based Conditional Random Field for Financial Fraud Detection","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Life-critical system; Critical system; Process management; Risk analysis (engineering); Software engineering; Engineering; Business; Programming language; Software","score_opus":0.009278590045317616,"score_gpt":0.23981352233386857,"score_spread":0.23053493228855096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401023814","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.12732166,0.0054240045,0.8405019,0.0022980012,0.00060693675,0.00029910752,0.0047445865,0.011963833,0.0068400805],"genre_scores_gemma":[0.82033926,0.0010457982,0.16643722,0.0006601122,0.0003246906,0.00019521841,0.006719727,0.00020994592,0.0040680044],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987557,0.00045908545,0.000074586635,0.00031086747,0.0002423339,0.00015752179],"domain_scores_gemma":[0.9966924,0.0020303,0.00034050367,0.00030245885,0.0005310688,0.00010318721],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003179934,0.0011247429,0.0010466145,0.0028304833,0.0005928786,0.0006594682,0.001757622,0.0013961709,0.0025707067],"category_scores_gemma":[0.009332694,0.00038617972,0.0010874501,0.0017594084,0.00056883553,0.0019274444,0.00086031965,0.0021079478,0.0011570101],"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":[0.00077785616,0.0005623535,0.009523656,0.0003129557,0.00017314962,0.0003017002,0.00012674434,0.38223332,0.005737735,0.009478894,0.026685476,0.56408614],"study_design_scores_gemma":[0.000013656608,0.000029076775,0.0011999147,0.00002037104,0.000016413862,0.000053990785,0.000008192476,0.98972416,0.0014935602,0.0063248775,0.0010982753,0.000017519049],"about_ca_topic_score_codex":0.021037376,"about_ca_topic_score_gemma":0.015543247,"teacher_disagreement_score":0.021037376,"about_ca_system_score_codex":0.001929001,"about_ca_system_score_gemma":0.0015010487,"threshold_uncertainty_score":0.041829824},"labels":[],"label_agreement":null},{"id":"W4401025108","doi":"10.24963/ijcai.2024/692","title":"FedAPA: Server-side Gradient-Based Adaptive Personalized Aggregation for Federated Learning on Heterogeneous Data","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"National Natural Science Foundation of China","keywords":"Debiasing; Term (time); Perception; Position (finance); Computer science; Position paper; Cognitive psychology; Psychology; Artificial intelligence; Social psychology; Business; World Wide Web; Neuroscience; Physics","score_opus":0.06499157901013528,"score_gpt":0.2866036818354525,"score_spread":0.2216121028253172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401025108","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0112187965,0.0002355757,0.98120016,0.00026155502,0.0000657075,0.00009137001,0.00021641857,0.0059233983,0.0007871372],"genre_scores_gemma":[0.54708713,0.00022647146,0.4461165,0.0006410599,0.00011927858,0.00035652003,0.0015008107,0.0006409654,0.0033111507],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981152,0.000645094,0.00011444907,0.00049909746,0.00042722365,0.0001988566],"domain_scores_gemma":[0.9962846,0.0013699996,0.00019044083,0.0013777384,0.00055154465,0.00022565684],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0041846456,0.0013306107,0.0016791678,0.0008777977,0.0009391382,0.0016013774,0.0034333789,0.0015012488,0.0021973085],"category_scores_gemma":[0.010355498,0.0006407089,0.0011342047,0.0011081157,0.001020634,0.0033759868,0.003488254,0.0028242723,0.0009883628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005209903,0.0004885819,0.0048757866,0.0001719186,0.0002499696,0.00022632038,0.0003201796,0.5542395,0.0054941517,0.019829778,0.019148126,0.39443463],"study_design_scores_gemma":[0.000017458242,0.000024980245,0.00011973241,0.000004787314,0.0000072300695,0.000036197092,0.0000147355495,0.9892468,0.0009765552,0.008808693,0.00073441543,0.000008414089],"about_ca_topic_score_codex":0.0059870887,"about_ca_topic_score_gemma":0.007625687,"teacher_disagreement_score":0.0059870887,"about_ca_system_score_codex":0.0013008863,"about_ca_system_score_gemma":0.0024675087,"threshold_uncertainty_score":0.022130787},"labels":[],"label_agreement":null},{"id":"W4401344867","doi":"10.1007/978-3-031-63596-0_11","title":"Constrained Robotic Navigation on Preferred Terrains Using LLMs and Speech Instruction: Exploiting the Power of Adverbs","year":2024,"lang":"en","type":"book-chapter","venue":"Springer proceedings in advanced robotics","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Terrain; Computer science; Power (physics); Artificial intelligence; Speech recognition; Geography; Cartography","score_opus":0.027909887911536563,"score_gpt":0.2538221758553164,"score_spread":0.22591228794377985,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401344867","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.13094804,0.00074230623,0.8059358,0.00028150663,0.00012334266,0.000047089634,0.00016904827,0.0030959898,0.058656834],"genre_scores_gemma":[0.85339314,0.00039403405,0.13517994,0.00007972481,0.000038668095,0.000055030498,0.00019170786,0.00056288845,0.010104872],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998543,0.000038433867,0.00000884533,0.00004912786,0.000030850955,0.000018388053],"domain_scores_gemma":[0.9995121,0.00025857758,0.000038656155,0.00010436077,0.000054714383,0.000031684773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024831863,0.00044796913,0.00059230055,0.00029812808,0.00043480203,0.001636296,0.0009485011,0.00057137257,0.0067547015],"category_scores_gemma":[0.0011773659,0.00035904953,0.0002697475,0.00042694795,0.00080555875,0.0023210205,0.0014646637,0.0006689972,0.0016458443],"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":[0.0010049313,0.00019727409,0.0018905336,0.00060668716,0.000051759656,0.00097466406,0.0022962098,0.09221207,0.24244094,0.18188876,0.0070098597,0.46942633],"study_design_scores_gemma":[0.00008997372,0.0003098224,0.001400326,0.00007236103,0.00006209303,0.00032756713,0.00087097153,0.8165449,0.043382213,0.11569036,0.02116812,0.000081269915],"about_ca_topic_score_codex":0.0018611292,"about_ca_topic_score_gemma":0.0031709536,"teacher_disagreement_score":0.0067547015,"about_ca_system_score_codex":0.00029469543,"about_ca_system_score_gemma":0.00041666845,"threshold_uncertainty_score":0.022596717},"labels":[],"label_agreement":null},{"id":"W4401440865","doi":"10.1016/j.jneuroling.2024.101227","title":"Heterogeneity of verbal and gestural functions in spoken discourse with MCI","year":2024,"lang":"en","type":"article","venue":"Journal of Neurolinguistics","topic":"Speech and dialogue systems","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":"Centre hospitalier universitaire de Québec","funders":"","keywords":"Nonverbal communication; Psychology; Linguistics; Communication; Cognitive psychology; Computer science; Philosophy","score_opus":0.012052005996190204,"score_gpt":0.2653339214764203,"score_spread":0.2532819154802301,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401440865","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":[0.9977754,0.00018874896,0.0001945747,0.000034941128,0.0000048297843,0.000009883553,0.00014119453,0.00001245654,0.0016380164],"genre_scores_gemma":[0.9995221,0.000042900272,0.000090027126,0.00001295741,0.000006936766,0.000010859712,0.00010199893,0.000007700616,0.00020451883],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9986827,0.0003103622,0.0002417622,0.0003074349,0.00026780777,0.00018997934],"domain_scores_gemma":[0.99413764,0.0037621597,0.00067484943,0.00037711454,0.00083672104,0.00021165611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011687569,0.0006162995,0.00071063347,0.0040023816,0.0006713629,0.0029325527,0.0006575293,0.0008423104,0.005069201],"category_scores_gemma":[0.0153140025,0.00024541953,0.00032637385,0.0012217474,0.0012752205,0.0019035764,0.0012132735,0.00045314681,0.00063855085],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0033159517,0.00039736414,0.66622216,0.0007165315,0.00057286775,0.012959695,0.07910153,0.0009875676,0.09490165,0.0031877581,0.0009591635,0.13667779],"study_design_scores_gemma":[0.000034592264,0.0003599149,0.9452678,0.00011565435,0.00023990229,0.01645444,0.025908213,0.0016776455,0.0054766624,0.0035133231,0.00088175165,0.000070011505],"about_ca_topic_score_codex":0.0069874255,"about_ca_topic_score_gemma":0.0047856146,"teacher_disagreement_score":0.0069874255,"about_ca_system_score_codex":0.00069848564,"about_ca_system_score_gemma":0.00049380667,"threshold_uncertainty_score":0.016958177},"labels":[],"label_agreement":null},{"id":"W4401503227","doi":"10.1075/lald.69.10per","title":"Varieties of DP recursion","year":2024,"lang":"en","type":"book-chapter","venue":"Language acquisition & language disorders","topic":"Speech and dialogue systems","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":"Recursion (computer science); Computer science; Programming language; Mathematics","score_opus":0.004844817815154216,"score_gpt":0.22022625467107582,"score_spread":0.2153814368559216,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401503227","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":[0.702759,0.0013491709,0.016871177,0.00059948885,0.000019188756,0.00003266811,0.0002142567,0.00021166887,0.27794343],"genre_scores_gemma":[0.9938106,0.00015836896,0.0017169385,0.000030987525,0.000005709784,0.000012246777,0.000044239157,0.000022340195,0.0041986597],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99947935,0.00024011017,0.000025065428,0.00008448691,0.000101589656,0.000069448266],"domain_scores_gemma":[0.9989427,0.0006564737,0.000091308815,0.00016124305,0.00009269773,0.00005560726],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063008844,0.00015418479,0.0002021757,0.00084020814,0.0006258231,0.0017822584,0.00031913086,0.00034595665,0.0036969816],"category_scores_gemma":[0.0014253217,0.0001562658,0.00018031454,0.00048336503,0.0031774805,0.0017122052,0.0014921267,0.0008400168,0.00032864098],"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":[0.000090260306,0.00003394077,0.01134149,0.00012331193,0.0000062292793,0.0016360257,0.031124264,0.0004980371,0.013595058,0.8658275,0.0012255526,0.074498326],"study_design_scores_gemma":[0.000047004185,0.0003951532,0.10251968,0.0004125942,0.000043910055,0.019211194,0.021217173,0.00658025,0.020064041,0.5940131,0.23538901,0.00010692754],"about_ca_topic_score_codex":0.000986074,"about_ca_topic_score_gemma":0.0011809595,"teacher_disagreement_score":0.0036969816,"about_ca_system_score_codex":0.00092031626,"about_ca_system_score_gemma":0.0003382107,"threshold_uncertainty_score":0.012367606},"labels":[],"label_agreement":null},{"id":"W4401609044","doi":"10.1109/icasspw62465.2024.10626978","title":"Skill: Similarity-Aware Knowledge Distillation for Speech Self-Supervised Learning","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Concordia University","funders":"","keywords":"Computer science; Similarity (geometry); Distillation; Artificial intelligence; Speech recognition; Machine learning; Natural language processing; Supervised learning; Artificial neural network","score_opus":0.016786078997190382,"score_gpt":0.2764085625626762,"score_spread":0.25962248356548584,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401609044","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.028356142,0.0005528552,0.9584663,0.00027667088,0.00009723943,0.00013600754,0.00029074383,0.009643428,0.0021805975],"genre_scores_gemma":[0.52365506,0.000224278,0.46644595,0.00060243555,0.00011912109,0.00036657185,0.0017652864,0.00073624833,0.006085146],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992242,0.00024819872,0.000034698238,0.00023374509,0.00019186903,0.00006729644],"domain_scores_gemma":[0.9985476,0.00069692,0.000084638355,0.00039664414,0.00019356073,0.00008058968],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015314149,0.0012260684,0.00096847,0.000738247,0.00063120795,0.0008484033,0.002792647,0.0014872915,0.0032088768],"category_scores_gemma":[0.0048484984,0.0004925599,0.0006878367,0.0006652169,0.0009772531,0.0021045434,0.002742985,0.0027754954,0.0011740056],"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":[0.00032797904,0.0004719681,0.0012289665,0.0002309536,0.00017458267,0.00010510649,0.00022015795,0.2653659,0.012910531,0.011983853,0.011912563,0.69506747],"study_design_scores_gemma":[0.000020370546,0.000055165372,0.000106274216,0.0000084573185,0.000009068794,0.000017314294,0.000013085991,0.9884409,0.003788795,0.0064611644,0.0010721356,0.000007333984],"about_ca_topic_score_codex":0.0037872707,"about_ca_topic_score_gemma":0.008047289,"teacher_disagreement_score":0.0037872707,"about_ca_system_score_codex":0.0007802474,"about_ca_system_score_gemma":0.001431334,"threshold_uncertainty_score":0.010734737},"labels":[],"label_agreement":null},{"id":"W4401943809","doi":"10.1109/cog60054.2024.10645616","title":"Voice-Augmented Virtual Reality Interface for Serious Games","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Calgary","funders":"","keywords":"Augmented reality; Virtual reality; Computer science; Human–computer interaction; Interface (matter); Computer-mediated reality; Mixed reality; Multimedia; Computer graphics (images)","score_opus":0.023603145211036333,"score_gpt":0.29444102648450654,"score_spread":0.2708378812734702,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4401943809","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.056621153,0.0023176176,0.8968411,0.00044577706,0.0005214956,0.0005812857,0.00043220972,0.010785738,0.0314535],"genre_scores_gemma":[0.60529053,0.0016621036,0.35804233,0.0007656646,0.000219567,0.0009571835,0.0008750922,0.0006972696,0.031490218],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99944884,0.00019127665,0.00004171387,0.000055776698,0.00021902012,0.000043456384],"domain_scores_gemma":[0.99954104,0.00022756636,0.000027260645,0.000047573118,0.00010785712,0.000048684935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005969612,0.0005740438,0.00028883546,0.00037836618,0.00025703976,0.0010872248,0.00084692275,0.0007322071,0.011319217],"category_scores_gemma":[0.0021228874,0.00018972646,0.0004159061,0.000148273,0.00027255501,0.00072238606,0.0011431734,0.00047798597,0.0019519131],"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":[0.0011627979,0.0002592278,0.0013147659,0.0011778367,0.00008318528,0.0012660221,0.0029607946,0.0035722752,0.25364,0.026856681,0.020450218,0.6872562],"study_design_scores_gemma":[0.0006830391,0.0046279565,0.016786495,0.0007316808,0.00037101,0.011316634,0.0017145303,0.09863527,0.11943276,0.018548144,0.72657394,0.000578524],"about_ca_topic_score_codex":0.00065008196,"about_ca_topic_score_gemma":0.0009491565,"teacher_disagreement_score":0.011319217,"about_ca_system_score_codex":0.00017635223,"about_ca_system_score_gemma":0.00027886854,"threshold_uncertainty_score":0.037866592},"labels":[],"label_agreement":null},{"id":"W4402209163","doi":"10.1521/jsyt.2024.43.1.84","title":"How Questioning Functions in Co-construction","year":2024,"lang":"en","type":"article","venue":"Journal of Systemic Therapies","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":3,"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":"Psychology; Epistemology; Social psychology; Philosophy","score_opus":0.012311530985476368,"score_gpt":0.23971321715198543,"score_spread":0.22740168616650908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402209163","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.19359972,0.0019735456,0.5869526,0.0067378436,0.00017370176,0.00052971876,0.000098817225,0.00096769293,0.2089664],"genre_scores_gemma":[0.9519004,0.00022890302,0.041662615,0.00018900725,0.00003252972,0.00023679006,0.00004933874,0.00019875665,0.00550166],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.93829745,0.052433938,0.0008411271,0.0035085992,0.0029342966,0.0019846552],"domain_scores_gemma":[0.9287439,0.05523362,0.0025166858,0.0097768055,0.0027196074,0.0010093949],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027033936,0.0012326017,0.00089141633,0.0047142105,0.0069531,0.013251703,0.0028553472,0.0029180632,0.006297279],"category_scores_gemma":[0.060715016,0.0010254048,0.0010105975,0.0034184307,0.044123787,0.026749207,0.012801584,0.003727172,0.0014730149],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00010966282,0.00006662166,0.0035651878,0.00018702583,0.000021301645,0.0003464105,0.3374059,0.0009949144,0.0025211915,0.602905,0.0008102058,0.051066525],"study_design_scores_gemma":[0.000057319296,0.00015801389,0.003180687,0.00037864843,0.000045362667,0.00129621,0.10206061,0.009129244,0.007864998,0.79282874,0.08291175,0.00008835082],"about_ca_topic_score_codex":0.0026232894,"about_ca_topic_score_gemma":0.0014331642,"teacher_disagreement_score":0.027033936,"about_ca_system_score_codex":0.0044773826,"about_ca_system_score_gemma":0.0026925476,"threshold_uncertainty_score":0.14297086},"labels":[],"label_agreement":null},{"id":"W4402364785","doi":"10.1016/j.tics.2024.08.005","title":"Tracking dynamic social impressions from multidimensional voice representation","year":2024,"lang":"en","type":"review","venue":"Trends in Cognitive Sciences","topic":"Speech and dialogue systems","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":"McGill University","funders":"","keywords":"Psychology; Representation (politics); Cognitive psychology; Cognitive science; Tracking (education); Communication","score_opus":0.29711471750422164,"score_gpt":0.4986432559090292,"score_spread":0.20152853840480756,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402364785","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":[0.0120641915,0.9445456,0.0317561,0.0011942189,0.001131182,0.00008096109,0.0008804438,0.0002863173,0.008060967],"genre_scores_gemma":[0.14399572,0.8068501,0.03699088,0.0010074727,0.0024861912,0.00024977472,0.0013888865,0.00008347476,0.006947536],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995504,0.000070026916,0.000028062059,0.00015723423,0.00017208433,0.00002216754],"domain_scores_gemma":[0.9976947,0.0015757512,0.0002376899,0.000073070194,0.0003791696,0.000039750394],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011076828,0.0009879468,0.0012212971,0.0024842669,0.00019066222,0.0019378194,0.0009752073,0.0014258723,0.0023701154],"category_scores_gemma":[0.0049159816,0.00030898547,0.00046664497,0.002373979,0.00054304814,0.0016408664,0.00080629677,0.000693662,0.001675809],"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":[0.00007438666,0.000030360352,0.0021734629,0.0030394031,0.00013754371,0.000035792655,0.00009726447,0.0005171486,0.002586404,0.001320766,0.0033156162,0.98667186],"study_design_scores_gemma":[0.0001894737,0.0011853949,0.20404747,0.02232277,0.003779967,0.0073837065,0.0026850342,0.05729295,0.03898179,0.07700415,0.58409715,0.0010301562],"about_ca_topic_score_codex":0.0022924817,"about_ca_topic_score_gemma":0.0035046607,"teacher_disagreement_score":0.0024842669,"about_ca_system_score_codex":0.00048193883,"about_ca_system_score_gemma":0.000617514,"threshold_uncertainty_score":0.007928848},"labels":[],"label_agreement":null},{"id":"W4402427290","doi":"10.1145/3663548.3688514","title":"Speech-based Mark for Data Sonification","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","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":"Sonification; Computer science; Auditory display; Speech recognition; Human–computer interaction","score_opus":0.09804828322374526,"score_gpt":0.3249681984659015,"score_spread":0.22691991524215627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402427290","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":[0.003900335,0.00024430646,0.98412675,0.00033207986,0.00029092736,0.00008427472,0.00017352264,0.0035050714,0.007342711],"genre_scores_gemma":[0.18696201,0.00056247116,0.79045266,0.00067955564,0.00027069642,0.00029728713,0.00071339414,0.0023191727,0.017742712],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981084,0.00050635525,0.00021952529,0.00032469857,0.0007330612,0.00010793162],"domain_scores_gemma":[0.99718213,0.0011846534,0.00013366694,0.0008991471,0.00049421337,0.0001063217],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021903608,0.0007455414,0.00048700965,0.00056161574,0.00056660746,0.001989312,0.0012405454,0.0012422665,0.006509951],"category_scores_gemma":[0.0042679766,0.00039445134,0.00062669395,0.00029345814,0.002539578,0.0027212414,0.0026418779,0.0016008705,0.0038325908],"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":[0.0003596683,0.00007198774,0.0006740428,0.0006883457,0.000038921677,0.0010273001,0.0031298485,0.0069008754,0.11126011,0.6540585,0.016050965,0.2057394],"study_design_scores_gemma":[0.00008248153,0.00024753768,0.0003929347,0.00022808614,0.000070166985,0.0025369432,0.00053750817,0.076852605,0.19234143,0.1941953,0.5323733,0.00014174459],"about_ca_topic_score_codex":0.00034244114,"about_ca_topic_score_gemma":0.0004352597,"teacher_disagreement_score":0.006509951,"about_ca_system_score_codex":0.00043417458,"about_ca_system_score_gemma":0.0005960961,"threshold_uncertainty_score":0.021777987},"labels":[],"label_agreement":null},{"id":"W4402452666","doi":"10.11159/mhci24.104","title":"Reducing Response Delays in Dialogue Systems Using the Predictive Performance of Large Language Models","year":2024,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Speech and dialogue systems","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":"Computer science; Language model; Artificial intelligence","score_opus":0.008956364262571213,"score_gpt":0.22039339850598128,"score_spread":0.21143703424341007,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402452666","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20762411,0.0006554625,0.7837484,0.00064316246,0.000112117385,0.00015842481,0.00011459877,0.0052525215,0.001691138],"genre_scores_gemma":[0.9144073,0.00013475298,0.08404108,0.00009412407,0.000059898834,0.00010681188,0.00010831797,0.00018966605,0.0008579965],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99745625,0.0013727748,0.00010339578,0.00034527303,0.00053882867,0.00018337312],"domain_scores_gemma":[0.98311424,0.0137692,0.00087153213,0.0008015071,0.0011730739,0.00027044184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0030021786,0.0013655924,0.00080114405,0.0005465213,0.0005587081,0.0013238896,0.0011573987,0.0011238004,0.0014488554],"category_scores_gemma":[0.02335685,0.0005070444,0.00032666055,0.0004127326,0.00054204185,0.0021884067,0.0013678976,0.001693156,0.00054358126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0036602502,0.0008528393,0.00581348,0.0004562935,0.00016290745,0.0003959078,0.0014661134,0.5047414,0.14762084,0.0045473897,0.0030479229,0.3272346],"study_design_scores_gemma":[0.00006891136,0.00040116807,0.0010684881,0.000013331916,0.000049099363,0.000054731114,0.00015487558,0.9680359,0.026928272,0.002110334,0.00107594,0.000038931685],"about_ca_topic_score_codex":0.0050587263,"about_ca_topic_score_gemma":0.004981802,"teacher_disagreement_score":0.0050587263,"about_ca_system_score_codex":0.00070797285,"about_ca_system_score_gemma":0.001324724,"threshold_uncertainty_score":0.015877247},"labels":[],"label_agreement":null},{"id":"W4402670735","doi":"10.18653/v1/2024.findings-acl.566","title":"Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Bootstrapping (finance); Task (project management); Human–computer interaction; Engineering; Systems engineering; Business","score_opus":0.014668264521313661,"score_gpt":0.24151347882425928,"score_spread":0.2268452143029456,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4402670735","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":[0.16888559,0.00023923503,0.8207253,0.00031821,0.00009345163,0.0004455423,0.00015934772,0.006681415,0.0024518573],"genre_scores_gemma":[0.82497704,0.000044002543,0.17169075,0.00020783457,0.000035270485,0.00056836964,0.00035552183,0.0002692926,0.0018519517],"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9974148,0.0014267896,0.000118497206,0.00057442894,0.00028838668,0.00017709153],"domain_scores_gemma":[0.9923016,0.005100913,0.00051656447,0.0010238024,0.0006676202,0.00038951487],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004319925,0.0013540109,0.001244404,0.0006349694,0.0005809247,0.0011641679,0.002016478,0.0012826255,0.002243536],"category_scores_gemma":[0.016884744,0.00069932186,0.0007691944,0.00025088905,0.0009823106,0.0016890728,0.003272497,0.001884677,0.0014202292],"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":[0.0013974048,0.0012045389,0.008284176,0.00039673378,0.00025465575,0.00039216867,0.002365496,0.57421654,0.03684546,0.0072427057,0.0043278416,0.36307228],"study_design_scores_gemma":[0.000033242573,0.000113058326,0.00029317546,0.0000108552595,0.000011212999,0.000026998121,0.000073778036,0.99156594,0.0042512915,0.0029765987,0.0006306025,0.000013217068],"about_ca_topic_score_codex":0.0015289999,"about_ca_topic_score_gemma":0.0020207076,"teacher_disagreement_score":0.004319925,"about_ca_system_score_codex":0.00071858836,"about_ca_system_score_gemma":0.0008370389,"threshold_uncertainty_score":0.022846222},"labels":[],"label_agreement":null},{"id":"W4403091139","doi":"10.36676/urr.v8.i4.1401","title":"Conversational AI: Transforming Human-Machine Interaction through Deep Learning","year":2021,"lang":"en","type":"article","venue":"Universal Research Reports","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Artificial intelligence; Deep learning; Cognitive science; Human–computer interaction; Psychology; Communication","score_opus":0.06338292119524713,"score_gpt":0.36608602085908737,"score_spread":0.30270309966384024,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403091139","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":[0.022257965,0.0006780062,0.9651299,0.0015469794,0.00012214958,0.00011390329,0.00010629191,0.0015412598,0.008503561],"genre_scores_gemma":[0.71421313,0.00069646206,0.27792057,0.00074874476,0.00009430255,0.00024634672,0.0002233028,0.00019977716,0.005657363],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99877256,0.00069432723,0.000043710806,0.00020495667,0.00018003845,0.000104384046],"domain_scores_gemma":[0.9978915,0.0015248006,0.0001221282,0.00020984041,0.0001525191,0.0000992332],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020464358,0.00059813575,0.00030732818,0.0004488824,0.0005872586,0.0016964864,0.0013412705,0.001066288,0.0030511606],"category_scores_gemma":[0.0062179915,0.00034832602,0.00045679227,0.00034685424,0.0013871434,0.002287161,0.002866473,0.0022478097,0.0007441215],"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":[0.00030026192,0.0004882993,0.004325205,0.000524466,0.00020388466,0.00037546724,0.004535939,0.28733683,0.033607353,0.107817024,0.010058465,0.5504268],"study_design_scores_gemma":[0.0000100243615,0.00005540333,0.00038616633,0.000048006703,0.000017929968,0.00005253096,0.00024496342,0.9168644,0.0047559054,0.06971187,0.007830353,0.000022362095],"about_ca_topic_score_codex":0.004415864,"about_ca_topic_score_gemma":0.005127033,"teacher_disagreement_score":0.004415864,"about_ca_system_score_codex":0.0009534178,"about_ca_system_score_gemma":0.001025233,"threshold_uncertainty_score":0.010822713},"labels":[],"label_agreement":null},{"id":"W4403501740","doi":"10.1080/13658816.2024.2415439","title":"Enhancing the accessibility of regionalization techniques through large language models: a case study in conversational agent guidance","year":2024,"lang":"en","type":"article","venue":"International Journal of Geographical Information Systems","topic":"Speech and dialogue systems","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":"Air Canada","funders":"","keywords":"Computer science; Geography; Data science; Human–computer interaction; Natural language processing","score_opus":0.026967273301084164,"score_gpt":0.32418558365742733,"score_spread":0.29721831035634316,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403501740","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":[0.54472756,0.0011608441,0.4043425,0.0066707935,0.0001398595,0.00092308596,0.0005391337,0.0040772376,0.037418995],"genre_scores_gemma":[0.80575365,0.00032605577,0.18665534,0.0007117341,0.000039930812,0.00041950523,0.00033384404,0.0005183855,0.0052414606],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.990625,0.008030756,0.00018679733,0.00043330158,0.000452174,0.00027189948],"domain_scores_gemma":[0.97055006,0.025845682,0.00057477166,0.0013199609,0.0010677959,0.0006417134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008212501,0.0010145024,0.000637111,0.0007022738,0.0021752643,0.0033656335,0.0022417307,0.0031896147,0.003828082],"category_scores_gemma":[0.024157671,0.00040399845,0.0007845146,0.00072317844,0.0022950012,0.0053969445,0.0040648663,0.0030179864,0.0011310428],"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":[0.0025726915,0.004297585,0.02320854,0.002576505,0.00027225813,0.0142264925,0.19274597,0.20665589,0.04217127,0.1680929,0.034896724,0.3082832],"study_design_scores_gemma":[0.0004757777,0.0011143344,0.0037252111,0.00036868494,0.0002102741,0.0021680444,0.04025434,0.73329884,0.022603653,0.05655604,0.13896292,0.00026192478],"about_ca_topic_score_codex":0.008007527,"about_ca_topic_score_gemma":0.01060259,"teacher_disagreement_score":0.008212501,"about_ca_system_score_codex":0.0016703869,"about_ca_system_score_gemma":0.0016159719,"threshold_uncertainty_score":0.043432415},"labels":[],"label_agreement":null},{"id":"W4403672388","doi":"10.18357/otessaj.2024.4.3.72","title":"Designing Cyberinfrastructure for Knowledge Sharing","year":2024,"lang":"en","type":"article","venue":"The Open/Technology in Education Society and Scholarship Association Journal","topic":"Speech and dialogue systems","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":"Simon Fraser University; University of Victoria; Dalhousie University","funders":"","keywords":"Cyberinfrastructure; Computer science; Data science; Knowledge sharing; World Wide Web; Knowledge management","score_opus":0.025669454900188557,"score_gpt":0.321365526373256,"score_spread":0.2956960714730674,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403672388","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":[0.12604211,0.00028792018,0.8153198,0.004398265,0.00010953374,0.00092996564,0.000097875025,0.0029073695,0.049907267],"genre_scores_gemma":[0.6402107,0.00017774894,0.34809822,0.00026125374,0.000050580238,0.0009956664,0.00028430554,0.0003494518,0.009572172],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98826736,0.00738665,0.00080805644,0.001390797,0.0014165734,0.00073058653],"domain_scores_gemma":[0.9662819,0.016883856,0.0021346326,0.009444994,0.0028786846,0.0023759673],"candidate_categories":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.013484542,0.0005340203,0.0004924515,0.0024950444,0.0049333456,0.010784099,0.0027271202,0.0023115329,0.007951076],"category_scores_gemma":[0.031548426,0.0009327049,0.0010119987,0.0018339377,0.006757591,0.023443393,0.014626284,0.0021355676,0.0022991071],"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":[0.00024944206,0.000767369,0.01184634,0.0006605171,0.00011578786,0.0013423746,0.06313206,0.013828865,0.012363721,0.6850202,0.007755687,0.20291759],"study_design_scores_gemma":[0.00018182247,0.00044978023,0.003947061,0.00047214533,0.000109317334,0.0011704679,0.033180457,0.16234455,0.012309314,0.55982924,0.22584085,0.00016488222],"about_ca_topic_score_codex":0.0018912174,"about_ca_topic_score_gemma":0.0017379789,"teacher_disagreement_score":0.9972729,"about_ca_system_score_codex":0.0025834488,"about_ca_system_score_gemma":0.0039595105,"threshold_uncertainty_score":0.07131392},"labels":[],"label_agreement":null},{"id":"W4403746629","doi":"10.48550/arxiv.2409.12068","title":"The repetition threshold for ternary rich words","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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","keywords":"Ternary operation; Repetition (rhetorical device); Mathematics; Linguistics; Arithmetic; Natural language processing; Computer science; Philosophy; Programming language","score_opus":0.0622020843587226,"score_gpt":0.19440777275047064,"score_spread":0.13220568839174804,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403746629","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":[0.63316506,0.002140879,0.31339347,0.0017700798,0.00019601287,0.00012408549,0.00090105966,0.0011973728,0.047111996],"genre_scores_gemma":[0.9698261,0.000292241,0.024716515,0.000276255,0.00015583319,0.00009122878,0.00035856452,0.00017816474,0.004105211],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99673754,0.00045851883,0.00027191718,0.00096975354,0.0010274268,0.00053489493],"domain_scores_gemma":[0.98810893,0.0075246305,0.0012680352,0.0013496903,0.0012233398,0.0005253522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013539792,0.0004841909,0.0009607556,0.0019901018,0.0017651747,0.0030627716,0.0011723489,0.0014297876,0.0066825305],"category_scores_gemma":[0.014882437,0.0006239429,0.0010707338,0.0010895468,0.0038699517,0.0055970596,0.0029081395,0.002246341,0.0017708138],"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":[0.00057189603,0.000053908527,0.003353452,0.00028787227,0.000048168604,0.00055781385,0.0018596386,0.01100078,0.025927506,0.9204761,0.0025555745,0.033307333],"study_design_scores_gemma":[0.000040064577,0.00011981646,0.0011603759,0.000060284397,0.000047219582,0.0005749553,0.0002944373,0.033811294,0.016086621,0.9422584,0.0054659727,0.00008057195],"about_ca_topic_score_codex":0.00095853145,"about_ca_topic_score_gemma":0.00062022154,"teacher_disagreement_score":0.0066825305,"about_ca_system_score_codex":0.0017029007,"about_ca_system_score_gemma":0.00094063504,"threshold_uncertainty_score":0.022355318},"labels":[],"label_agreement":null},{"id":"W4403752647","doi":"10.1080/09296174.2024.2416641","title":"Reference to Patients in Nurse Shift Handover Meetings: Exploring the Dynamics of Referring Expressions","year":2024,"lang":"en","type":"article","venue":"Journal of Quantitative Linguistics","topic":"Speech and dialogue systems","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 à Trois-Rivières","funders":"","keywords":"Handover; Dynamics (music); Computer science; Expression (computer science); Linguistics; Natural language processing; Psychology; Process management; Human–computer interaction; Computer network; Business; Programming language; Pedagogy; Philosophy","score_opus":0.07452752650817829,"score_gpt":0.33282496068705675,"score_spread":0.25829743417887846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403752647","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":[0.9600277,0.00031211774,0.03632638,0.0004803405,0.0000142406325,0.00003937909,0.00012466572,0.000086277025,0.0025889182],"genre_scores_gemma":[0.99476516,0.000104883016,0.0044995463,0.00002820232,0.000008960077,0.000021384638,0.00007709574,0.000020518408,0.00047410963],"study_design_codex":"observational","study_design_gemma":"qualitative","domain_scores_codex":[0.9977908,0.0014804797,0.00006278761,0.0002920562,0.00026053522,0.00011340855],"domain_scores_gemma":[0.9846287,0.011573271,0.002354587,0.00047292397,0.00061202334,0.00035855686],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0025886477,0.00027007767,0.00035056673,0.0012251922,0.0007534071,0.00144757,0.00066721754,0.0008162223,0.001544644],"category_scores_gemma":[0.029257936,0.00026721365,0.00029076205,0.0011979886,0.0010148735,0.0021577093,0.0017067216,0.00066135445,0.00034950022],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0019738746,0.00035725246,0.46928194,0.000665146,0.00036258574,0.00397559,0.119152024,0.09974278,0.034072585,0.062171526,0.0032748159,0.20496993],"study_design_scores_gemma":[0.00005106353,0.00036418237,0.31800538,0.00018525415,0.00012673068,0.0012867026,0.041058872,0.57660955,0.0070620794,0.04395902,0.011075401,0.00021576682],"about_ca_topic_score_codex":0.0063085333,"about_ca_topic_score_gemma":0.0055119577,"teacher_disagreement_score":0.0063085333,"about_ca_system_score_codex":0.0011739525,"about_ca_system_score_gemma":0.00065275683,"threshold_uncertainty_score":0.013690233},"labels":[],"label_agreement":null},{"id":"W4403794801","doi":"10.48550/arxiv.2409.17353","title":"Internalizing ASR with Implicit Chain of Thought for Efficient Speech-to-Speech Conversational LLM","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Speech and dialogue systems","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":"Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Speech recognition; Psychology; Indirect speech; Computer science; Linguistics; Cognitive psychology; Natural language processing; Philosophy","score_opus":0.047158186905353346,"score_gpt":0.20619985624076131,"score_spread":0.15904166933540798,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4403794801","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":[0.02784811,0.000901688,0.943743,0.00059870834,0.00030421975,0.00016607743,0.00077691197,0.022152927,0.0035083115],"genre_scores_gemma":[0.5984261,0.00049769745,0.38418084,0.00073127216,0.00037735578,0.00046107874,0.0034591989,0.0017257875,0.010140598],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9984559,0.0005547066,0.000098508,0.0005311866,0.00021684218,0.0001427638],"domain_scores_gemma":[0.9977481,0.0010830719,0.00012621196,0.0005641638,0.00031638765,0.0001621257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021245233,0.0021622756,0.0011382202,0.0008512423,0.0005566685,0.0020669529,0.001766903,0.0015296217,0.0062417733],"category_scores_gemma":[0.0072370656,0.00066139793,0.0015101568,0.00053263124,0.0010228124,0.0029987323,0.0030576133,0.0034760202,0.0060218433],"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":[0.0013101926,0.0005553496,0.0034946299,0.0004697012,0.00029937626,0.0004557413,0.0010977433,0.13422507,0.0686627,0.013502023,0.025063515,0.750864],"study_design_scores_gemma":[0.0000639509,0.00013246223,0.00045480387,0.000026937165,0.000060556857,0.00012832093,0.0001016346,0.9660271,0.014743145,0.011907097,0.0063112467,0.000042827545],"about_ca_topic_score_codex":0.003272189,"about_ca_topic_score_gemma":0.005488124,"teacher_disagreement_score":0.0062417733,"about_ca_system_score_codex":0.00086741464,"about_ca_system_score_gemma":0.0017849939,"threshold_uncertainty_score":0},"labels":[],"label_agreement":null},{"id":"W4404295312","doi":"10.1109/mmsp61759.2024.10743791","title":"Learned Multimodal Compression for Autonomous Driving","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; Compression (physics); Data compression; Human–computer interaction; Artificial intelligence","score_opus":0.026135885074742467,"score_gpt":0.2908942774544464,"score_spread":0.26475839237970394,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404295312","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.35770825,0.005645493,0.6008938,0.0017573939,0.00055050966,0.0002785102,0.008970563,0.0115945535,0.0126010515],"genre_scores_gemma":[0.86261994,0.00093854225,0.11485328,0.00035306378,0.0002245734,0.00019430835,0.014138122,0.00019953317,0.0064786416],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99953735,0.00009378265,0.000016409407,0.00010688305,0.00017556097,0.000070044895],"domain_scores_gemma":[0.999521,0.00016959118,0.000029862853,0.00010814583,0.00014591592,0.000025361562],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000538033,0.00090444373,0.0005304969,0.00094857975,0.00025543006,0.00045912992,0.00072950334,0.00070377893,0.0030615008],"category_scores_gemma":[0.002358994,0.00016222699,0.00043840735,0.0008263919,0.0003462614,0.0011303222,0.0009825568,0.0010012601,0.00094412325],"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":[0.0007898968,0.00022742542,0.0019809136,0.00019359858,0.00007913305,0.00020082686,0.000111889516,0.13133654,0.024485074,0.0028412975,0.016724505,0.8210289],"study_design_scores_gemma":[0.00006020094,0.00025388502,0.0031995461,0.000044264216,0.00003859376,0.00024449368,0.0001470877,0.94782215,0.02929123,0.010304221,0.008554235,0.000040138893],"about_ca_topic_score_codex":0.005937933,"about_ca_topic_score_gemma":0.0060357614,"teacher_disagreement_score":0.005937933,"about_ca_system_score_codex":0.00054825837,"about_ca_system_score_gemma":0.00066660286,"threshold_uncertainty_score":0.011806726},"labels":[],"label_agreement":null},{"id":"W4404740936","doi":"10.1109/gen4ds63889.2024.00005","title":"The Data-Wink Ratio: Emoji Encoder for Generating Semantically-Resonant Unit Charts","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Emoji; Computer science; Encoder; Unit (ring theory); Computer graphics (images); Speech recognition; Mathematics; World Wide Web; Operating system","score_opus":0.07012500074866271,"score_gpt":0.3155926803874036,"score_spread":0.24546767963874092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404740936","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":[0.022256384,0.0004294498,0.84785604,0.00046801422,0.00073090935,0.0004673737,0.010127156,0.10809741,0.009567327],"genre_scores_gemma":[0.13875693,0.00039853045,0.81909937,0.0004012947,0.0001990581,0.0018164376,0.012231704,0.015134717,0.011962027],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990951,0.00033062816,0.00007228387,0.0002116472,0.00022582107,0.000064508815],"domain_scores_gemma":[0.9955348,0.002760389,0.00020637696,0.0005713056,0.00075045956,0.00017664213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018521098,0.0018203562,0.0005928405,0.0015651694,0.00057396665,0.0018263924,0.0011900574,0.0007779544,0.024368195],"category_scores_gemma":[0.01565907,0.0005536284,0.0006399976,0.0010396477,0.0005891257,0.0024421006,0.002516123,0.0012645472,0.009493952],"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":[0.0018410478,0.00033960317,0.0038779627,0.0020278718,0.000121491656,0.0010379574,0.0059016626,0.0075714886,0.07448531,0.030053392,0.1680879,0.70465434],"study_design_scores_gemma":[0.00026719354,0.00056656,0.0066249934,0.0006217729,0.00014293691,0.0009531755,0.0027514186,0.42027494,0.17428485,0.064666145,0.32842574,0.00042026964],"about_ca_topic_score_codex":0.0007079695,"about_ca_topic_score_gemma":0.0014715063,"teacher_disagreement_score":0.024368195,"about_ca_system_score_codex":0.000421466,"about_ca_system_score_gemma":0.0005938442,"threshold_uncertainty_score":0.08151972},"labels":[],"label_agreement":null},{"id":"W4404783121","doi":"10.18653/v1/2024.emnlp-main.30","title":"EmphAssess : a Prosodic Benchmark on Assessing Emphasis Transfer in Speech-to-Speech Models","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Agence Nationale de la Recherche; École des Hautes Etudes en Sciences Sociales; Canadian Institute for Advanced Research","keywords":"Emphasis (telecommunications); Computer science; Benchmark (surveying); Speech recognition; Natural language processing; Artificial intelligence; Telecommunications","score_opus":0.03559975349177633,"score_gpt":0.29594565316346466,"score_spread":0.2603458996716883,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4404783121","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36925483,0.007023367,0.53316927,0.0012750903,0.00182281,0.0015642187,0.020625288,0.027698519,0.037566643],"genre_scores_gemma":[0.72913295,0.0015526895,0.20683576,0.00085213006,0.00042508222,0.0016060823,0.047366515,0.0036459058,0.00858287],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954608,0.002014703,0.00039775006,0.0007310641,0.0011794181,0.00021623625],"domain_scores_gemma":[0.98832613,0.007177868,0.00069685816,0.0011726116,0.002041466,0.00058500137],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0077090547,0.003484631,0.000944055,0.002136757,0.00087210827,0.0025138154,0.0021847195,0.0024142715,0.005933229],"category_scores_gemma":[0.028202044,0.000510635,0.0009479391,0.0008780994,0.00083764014,0.0030111063,0.0029917036,0.0021392035,0.0025528676],"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":[0.0040525533,0.0013658422,0.018912554,0.0027118574,0.0011391547,0.0007439962,0.0012164601,0.4034856,0.08492686,0.0064045265,0.04755512,0.4274855],"study_design_scores_gemma":[0.00047378454,0.0034825208,0.017442284,0.00031347232,0.00032153286,0.00074314186,0.00058238994,0.889735,0.055913936,0.010046221,0.02071356,0.00023218432],"about_ca_topic_score_codex":0.0048811464,"about_ca_topic_score_gemma":0.0059663095,"teacher_disagreement_score":0.0077090547,"about_ca_system_score_codex":0.00086960185,"about_ca_system_score_gemma":0.0012202866,"threshold_uncertainty_score":0.040769875},"labels":[],"label_agreement":null},{"id":"W4406124312","doi":"10.1093/iwc/iwae062","title":"Unboxing Manipulation Checks for Voice UX","year":2024,"lang":"en","type":"article","venue":"Interacting with Computers","topic":"Speech and dialogue systems","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":"York University","funders":"Japan Society for the Promotion of Science","keywords":"Computer science; Human–computer interaction; Speech recognition","score_opus":0.023521106765770898,"score_gpt":0.2767163200664645,"score_spread":0.2531952133006936,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406124312","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4153224,0.0041513974,0.47351366,0.009642157,0.00613707,0.020211795,0.0015982197,0.0036193263,0.065803915],"genre_scores_gemma":[0.7767572,0.0005371561,0.18727024,0.0032205756,0.0007148158,0.027208313,0.00046770033,0.00082117773,0.003002817],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.6938017,0.2352506,0.02196182,0.012262576,0.034123313,0.002599886],"domain_scores_gemma":[0.08976017,0.809416,0.03376626,0.03856995,0.027802154,0.0006854238],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.18690312,0.0020827616,0.0015038241,0.0038864734,0.0037775969,0.006086703,0.002844593,0.0028469407,0.01078389],"category_scores_gemma":[0.71183187,0.0010899199,0.0013493964,0.00243613,0.0074173477,0.0071434043,0.006452368,0.0046662916,0.0015568961],"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":[0.012196973,0.0025865645,0.0544511,0.015909433,0.0013127587,0.0017718228,0.106778026,0.0029302335,0.050781965,0.23611599,0.027432365,0.4877328],"study_design_scores_gemma":[0.0044971257,0.0154386135,0.14523476,0.024044879,0.0028695422,0.0021882248,0.041727364,0.045078874,0.1407761,0.29278,0.28347895,0.0018856176],"about_ca_topic_score_codex":0.0009362057,"about_ca_topic_score_gemma":0.0008384882,"teacher_disagreement_score":0.18690312,"about_ca_system_score_codex":0.00319618,"about_ca_system_score_gemma":0.003255866,"threshold_uncertainty_score":0.98845},"labels":[],"label_agreement":null},{"id":"W4406235772","doi":"10.1016/j.endend.2012.09.025","title":"10.1016/j.endend.2012.09.025","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Speech and dialogue systems","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":"Computer science","score_opus":0.007379795820305798,"score_gpt":0.17578483994289493,"score_spread":0.16840504412258914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406235772","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":[0.003418787,0.0068035973,0.006143868,0.0035206566,0.0015997034,0.000090872905,0.0024480186,0.003255012,0.97271943],"genre_scores_gemma":[0.009832601,0.0025258146,0.0032858194,0.0013465506,0.0002826273,0.00008043807,0.0017097859,0.0004122958,0.98052406],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996126,0.000025777957,0.00003079362,0.00014375364,0.00009834712,0.00008875522],"domain_scores_gemma":[0.99885845,0.0003504071,0.00012511307,0.00011483419,0.00021111555,0.00034006924],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0009795616,0.0017512109,0.00079613,0.0021207652,0.001344756,0.0051167407,0.0015564524,0.0067256517,0.94162196],"category_scores_gemma":[0.0019774823,0.0005960748,0.0006747793,0.0010546262,0.0013134461,0.0040623033,0.0018190182,0.0015952627,0.9262797],"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":[0.00018258572,0.0002865024,0.0034852296,0.00057964557,0.000037562342,0.00052569347,0.0002094374,0.00046350822,0.0013548338,0.009069129,0.28141472,0.70239115],"study_design_scores_gemma":[0.000056003835,0.0001035126,0.0031338853,0.0011585285,0.00005512364,0.0026715018,0.000531673,0.000618748,0.00067756145,0.0074548903,0.98349357,0.0000449692],"about_ca_topic_score_codex":0.0020617258,"about_ca_topic_score_gemma":0.002237393,"teacher_disagreement_score":0.05837804,"about_ca_system_score_codex":0.00075826526,"about_ca_system_score_gemma":0.0012292122,"threshold_uncertainty_score":0.08326918},"labels":[],"label_agreement":null},{"id":"W4406534850","doi":"10.1016/0967-0653(94)92371-x","title":"10.1016/0967-0653(94)92371-x","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Speech and dialogue systems","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":"Computer science","score_opus":0.007529774264981884,"score_gpt":0.17208517439403628,"score_spread":0.1645554001290544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4406534850","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":[0.0005501182,0.00041164676,0.0006177449,0.0004269191,0.00030889674,0.00013472736,0.00080879644,0.0010282585,0.9957129],"genre_scores_gemma":[0.00068070623,0.00025745813,0.00035433914,0.00031791197,0.00007063595,0.000075485004,0.000426125,0.00020550599,0.99761176],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991455,0.00006221674,0.000081712744,0.00031745958,0.0001921826,0.00020082873],"domain_scores_gemma":[0.99704903,0.00084245024,0.00015898325,0.00035728308,0.00062231225,0.00096994237],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0013828758,0.003768912,0.0023487033,0.0031410812,0.0035262539,0.004640954,0.004180731,0.0071539055,0.99164516],"category_scores_gemma":[0.0021803,0.0013758792,0.0015792812,0.0027280087,0.0030541962,0.0073918416,0.003989706,0.0032175668,0.99405885],"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":[0.0004841304,0.00028343016,0.0011582343,0.00084853877,0.00005280133,0.00044490685,0.00018997757,0.0005321736,0.0025385278,0.0059609823,0.46013054,0.52737576],"study_design_scores_gemma":[0.00008272015,0.00016989202,0.001079365,0.000492884,0.000023290782,0.0005374801,0.00026555482,0.00025190128,0.00045870978,0.0008351894,0.99576616,0.000036847596],"about_ca_topic_score_codex":0.0062592127,"about_ca_topic_score_gemma":0.0053251665,"teacher_disagreement_score":0.008354843,"about_ca_system_score_codex":0.0014247205,"about_ca_system_score_gemma":0.0011148385,"threshold_uncertainty_score":0.012445569},"labels":[],"label_agreement":null},{"id":"W4407221739","doi":"10.48550/arxiv.2502.03128","title":"Metis: A Foundation Speech Generation Model with Masked Generative Pre-training","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Speech and dialogue systems","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":"Metis; Generative grammar; Foundation (evidence); Training (meteorology); Speech recognition; Computer science; Psychology; Artificial intelligence; History; Geography; World Wide Web","score_opus":0.09950370094731856,"score_gpt":0.29843302871328803,"score_spread":0.19892932776596947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407221739","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":[0.0078027933,0.00028792414,0.984388,0.00021138352,0.00010591774,0.000108802815,0.00047571273,0.0039891917,0.0026302112],"genre_scores_gemma":[0.49024656,0.0005261471,0.48493823,0.00072576344,0.00021643068,0.0010596492,0.004259859,0.0017336273,0.016293652],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995223,0.00012312824,0.000026557946,0.00016112688,0.00010908766,0.000057742025],"domain_scores_gemma":[0.9992173,0.00041367565,0.000042185096,0.00012882997,0.00013735764,0.000060674858],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010945423,0.0011361121,0.00076786836,0.00046231903,0.00038699366,0.0009677445,0.002218101,0.0009812411,0.006178802],"category_scores_gemma":[0.0030739754,0.0006948426,0.0010959483,0.00037564445,0.00063731207,0.0013201527,0.002073281,0.001971101,0.0034374946],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00063617894,0.00018853646,0.0019343636,0.00029394106,0.0001964165,0.00036624525,0.00047478612,0.5927282,0.025022268,0.031500097,0.016893668,0.3297653],"study_design_scores_gemma":[0.000016196618,0.000048148206,0.00011674028,0.0000096596805,0.000012767243,0.00006001583,0.000011364585,0.9896771,0.002338428,0.0053328606,0.0023653824,0.0000113023725],"about_ca_topic_score_codex":0.003702056,"about_ca_topic_score_gemma":0.006649618,"teacher_disagreement_score":0.006178802,"about_ca_system_score_codex":0.00065463426,"about_ca_system_score_gemma":0.0012707205,"threshold_uncertainty_score":0.020670116},"labels":[],"label_agreement":null},{"id":"W4407251405","doi":"10.2139/ssrn.5128348","title":"Fasttalker: An Unified Framework for Generating Speech and Conversational Gestures from Text","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Speech and dialogue systems","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":"Gesture; Computer science; Speech recognition; Linguistics; Communication; Natural language processing; Psychology; Artificial intelligence; Philosophy","score_opus":0.01667713250356856,"score_gpt":0.2719421316703564,"score_spread":0.25526499916678785,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407251405","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":[0.0011132418,0.00010174344,0.9239188,0.000030789724,0.000075218704,0.00014647227,0.001554815,0.07199778,0.001061161],"genre_scores_gemma":[0.05309095,0.00034780026,0.90853125,0.0001630505,0.0001296975,0.00088148296,0.0091940975,0.018423995,0.009237599],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989342,0.00018427747,0.00008995591,0.0003285076,0.0003526534,0.000110530586],"domain_scores_gemma":[0.99882716,0.00054563,0.00006820729,0.000238354,0.00022859061,0.00009199711],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015772968,0.0027421217,0.0019785932,0.0018450103,0.0009571056,0.0035705534,0.0040625427,0.0021898951,0.03399615],"category_scores_gemma":[0.0043809596,0.0017149436,0.0020546273,0.0010813932,0.0008054785,0.0030555483,0.0033785196,0.0020463783,0.01583986],"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":[0.0017874255,0.00020178578,0.0012599471,0.001528847,0.00030202183,0.00090380484,0.0014339156,0.027944637,0.08041042,0.03482211,0.087022826,0.76238227],"study_design_scores_gemma":[0.00033704305,0.00031259237,0.0015804508,0.0002442545,0.00022595406,0.0010366283,0.00035740048,0.66082513,0.12192845,0.05494073,0.1578576,0.00035371515],"about_ca_topic_score_codex":0.004375235,"about_ca_topic_score_gemma":0.005632802,"teacher_disagreement_score":0.03399615,"about_ca_system_score_codex":0.00067140866,"about_ca_system_score_gemma":0.0011107732,"threshold_uncertainty_score":0.113728404},"labels":[],"label_agreement":null},{"id":"W4407304464","doi":"10.1109/access.2025.3540388","title":"BVQA: Connecting Language and Vision Through Multimodal Attention for Open-Ended Question Answering","year":2025,"lang":"en","type":"article","venue":"IEEE Access","topic":"Speech and dialogue systems","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":"Athabasca University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Question answering; Natural language processing; Closed-ended question; Artificial intelligence; Human–computer interaction; Linguistics; Philosophy","score_opus":0.029593799451984853,"score_gpt":0.386820533552708,"score_spread":0.35722673410072314,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407304464","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18298003,0.008693886,0.722086,0.0034524386,0.00077805604,0.0021307345,0.021163277,0.03946147,0.019254027],"genre_scores_gemma":[0.66072845,0.0011547465,0.2821283,0.002562919,0.00029477137,0.001545374,0.0388119,0.00054717803,0.012226349],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99860495,0.00050250604,0.000056444904,0.0005625491,0.00012921698,0.00014447606],"domain_scores_gemma":[0.99823546,0.0010288864,0.000090882386,0.00027334475,0.00026521363,0.000106158885],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019929733,0.0021380638,0.00090566144,0.0018081082,0.0007848664,0.0014432836,0.0028622523,0.0029085516,0.007863552],"category_scores_gemma":[0.007352241,0.00046813858,0.0018255676,0.0011590547,0.0009850529,0.003763468,0.0029816763,0.0028664663,0.0030610277],"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":[0.0011679508,0.00097478327,0.0063063423,0.001350339,0.0003206142,0.0006339087,0.0016216227,0.056868736,0.04407854,0.011834614,0.06955343,0.80528927],"study_design_scores_gemma":[0.00013338677,0.0004910103,0.0048160604,0.00012715552,0.00014348616,0.00033270882,0.0005609292,0.90962064,0.023245966,0.033246018,0.027196411,0.00008628144],"about_ca_topic_score_codex":0.020930858,"about_ca_topic_score_gemma":0.022315437,"teacher_disagreement_score":0.020930858,"about_ca_system_score_codex":0.0023771317,"about_ca_system_score_gemma":0.0010406738,"threshold_uncertainty_score":0.04161805},"labels":[],"label_agreement":null},{"id":"W4407398990","doi":"10.32388/39knz3","title":"Review of: \"Are Vision-Language Models Truly Understanding Multi-vision Sensor?\"","year":2025,"lang":"en","type":"peer-review","venue":"","topic":"Speech and dialogue systems","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":"Vision science; Computer science; Artificial intelligence; Computer vision; Cognitive science; Psychology","score_opus":0.08651338753806165,"score_gpt":0.35759027251411607,"score_spread":0.2710768849760544,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407398990","genre_codex":"commentary","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":[0.0011336629,0.1352813,0.006336078,0.56963325,0.2519953,0.0001974815,0.0026711144,0.0006500134,0.03210177],"genre_scores_gemma":[0.028379537,0.25574866,0.0066100904,0.27145436,0.24227028,0.00049162324,0.009247009,0.0020076006,0.18379085],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9962717,0.00084436795,0.00033010473,0.00039765876,0.0019448478,0.00021130004],"domain_scores_gemma":[0.88362134,0.020642633,0.002654704,0.002351193,0.086821295,0.0039088423],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00972442,0.000618086,0.0011115025,0.003408053,0.0013995443,0.0028302493,0.002133591,0.0028924579,0.029324727],"category_scores_gemma":[0.08011821,0.00049157726,0.0006490849,0.0021729418,0.001632004,0.004677669,0.0019197627,0.0035017063,0.026797771],"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":[0.00002321579,0.000005132327,0.00009263513,0.0006402888,0.000013029449,0.000027269296,0.00003777841,0.00004561707,0.00010665747,0.0012086389,0.95888215,0.038917672],"study_design_scores_gemma":[0.000011423708,0.00002268057,0.00060907216,0.0011843379,0.000022992106,0.00008821587,0.0000569722,0.00012095675,0.00018414739,0.001271223,0.9964133,0.0000146067705],"about_ca_topic_score_codex":0.0063593234,"about_ca_topic_score_gemma":0.010396313,"teacher_disagreement_score":0.029324727,"about_ca_system_score_codex":0.0024333966,"about_ca_system_score_gemma":0.0077387956,"threshold_uncertainty_score":0.09810102},"labels":[],"label_agreement":null},{"id":"W4407547300","doi":"10.31178/bwpl.26.2.5","title":"AN OVERVIEW OF GENERATIVE THIRD LANGUAGE ACQUISITION RESEARCH","year":2025,"lang":"en","type":"article","venue":"Bucharest Working Papers in Linguistics","topic":"Speech and dialogue systems","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":"University of Cambridge; McGill University","keywords":"Generative grammar; Linguistics; Computer science; Natural language processing; Artificial intelligence; Philosophy","score_opus":0.09087528004048123,"score_gpt":0.3953488440549833,"score_spread":0.30447356401450204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407547300","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":[0.0059012766,0.86450934,0.027690103,0.0044773375,0.00057626853,0.000056740897,0.00020405569,0.00025223216,0.096332625],"genre_scores_gemma":[0.07964343,0.86980766,0.022537269,0.0022780842,0.001211176,0.00014493204,0.0006516487,0.0002918486,0.023433857],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992562,0.00025828514,0.00007160804,0.00016299119,0.00018243304,0.00006860173],"domain_scores_gemma":[0.9981687,0.0014054842,0.00008514305,0.0001366156,0.00015224578,0.000051745596],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015235157,0.0007933174,0.0008138012,0.005007663,0.0009227136,0.0035180817,0.0013234238,0.0016816187,0.011223375],"category_scores_gemma":[0.002161203,0.0006488332,0.00078103965,0.0049401624,0.0024914688,0.0034553325,0.0018664296,0.0017715497,0.0040614777],"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":[0.00008779095,0.000104821505,0.0022027926,0.0061773635,0.000060351245,0.00050911197,0.0039610676,0.0013055701,0.0018973238,0.27885726,0.017798757,0.6870378],"study_design_scores_gemma":[0.000008795915,0.000058972582,0.0037112897,0.0039528976,0.00004017521,0.0021251482,0.00094477553,0.0010243395,0.0015432292,0.08599369,0.9005489,0.000047803656],"about_ca_topic_score_codex":0.0030988911,"about_ca_topic_score_gemma":0.00289738,"teacher_disagreement_score":0.011223375,"about_ca_system_score_codex":0.0026778588,"about_ca_system_score_gemma":0.0020235665,"threshold_uncertainty_score":0.03754592},"labels":[],"label_agreement":null},{"id":"W4407553617","doi":"10.3765/pe3dtd58","title":"Prosody across sentence types","year":2025,"lang":"en","type":"article","venue":"Proceedings from Semantics and Linguistic Theory","topic":"Speech and dialogue systems","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":"Trinity College","funders":"","keywords":"Prosody; Sentence; Natural language processing; Computer science; Linguistics; Artificial intelligence; Speech recognition; Philosophy","score_opus":0.007032443742859314,"score_gpt":0.24951281200384115,"score_spread":0.24248036826098185,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4407553617","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":[0.7158903,0.0025269787,0.016308777,0.0011450627,0.00043228,0.00026367718,0.006266763,0.0010530674,0.25611317],"genre_scores_gemma":[0.9856909,0.00045790744,0.0042762524,0.00043407362,0.00015144634,0.00023868745,0.0025232683,0.0005510786,0.005676417],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99828064,0.0006110513,0.00018498083,0.00036532088,0.00042267618,0.00013537813],"domain_scores_gemma":[0.99575776,0.0028292534,0.0002776843,0.0003037296,0.00070669776,0.0001249522],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012622591,0.00066290936,0.00048614026,0.0013953077,0.0007782981,0.003249531,0.00047559332,0.0007137022,0.013678138],"category_scores_gemma":[0.0077516777,0.0005059974,0.0003474203,0.0010446765,0.000708502,0.0031395718,0.0023120432,0.0011418082,0.002638115],"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":[0.004820899,0.0002514242,0.059874192,0.0033469142,0.00058615307,0.003004868,0.13286683,0.0014234849,0.32517818,0.07456206,0.021649152,0.37243578],"study_design_scores_gemma":[0.00050414685,0.0015432228,0.5454696,0.0017415666,0.0010203548,0.01007201,0.08274301,0.014975527,0.056938823,0.07799632,0.20628348,0.0007119578],"about_ca_topic_score_codex":0.0004902504,"about_ca_topic_score_gemma":0.00039950223,"teacher_disagreement_score":0.013678138,"about_ca_system_score_codex":0.00045748136,"about_ca_system_score_gemma":0.00016854408,"threshold_uncertainty_score":0.04575789},"labels":[],"label_agreement":null},{"id":"W4408113760","doi":"10.1121/10.0036052","title":"Voice assistant technology continues to underperform on children's speech","year":2025,"lang":"en","type":"article","venue":"JASA Express Letters","topic":"Speech and dialogue systems","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 Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Psychology","score_opus":0.00566815040736642,"score_gpt":0.2305283615674443,"score_spread":0.22486021116007787,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408113760","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":[0.983384,0.0025371094,0.002704013,0.00022916883,0.000058865186,0.000022982485,0.00036930546,0.00043925215,0.010255346],"genre_scores_gemma":[0.9871394,0.003241853,0.00446723,0.00016604278,0.000042226042,0.000028239374,0.0005658248,0.00015866444,0.0041905213],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9976399,0.00030018535,0.00027865393,0.000614677,0.00097556115,0.00019101423],"domain_scores_gemma":[0.9907194,0.0049140253,0.0011479765,0.00062458526,0.0021092412,0.00048486204],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028464454,0.0005517298,0.00053246855,0.00082335516,0.00037357566,0.0023282266,0.0004948133,0.00062820385,0.0031166836],"category_scores_gemma":[0.00875584,0.00024548647,0.00043727542,0.00042201296,0.000811642,0.0015311269,0.0010353733,0.00044875432,0.0025539594],"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":[0.00065323134,0.0001239175,0.3150148,0.0012655385,0.00020216142,0.0018372624,0.01845454,0.0009071854,0.14010216,0.0011802317,0.00415076,0.51610816],"study_design_scores_gemma":[0.00003379431,0.0031607011,0.81290394,0.0007232526,0.00039440868,0.0068056528,0.017965958,0.0024655082,0.09295068,0.000804293,0.06164841,0.00014336807],"about_ca_topic_score_codex":0.0037158432,"about_ca_topic_score_gemma":0.0053797355,"teacher_disagreement_score":0.0037158432,"about_ca_system_score_codex":0.00041252983,"about_ca_system_score_gemma":0.0005441121,"threshold_uncertainty_score":0.01505363},"labels":[],"label_agreement":null},{"id":"W4408354432","doi":"10.1109/icassp49660.2025.10889092","title":"What Are They Doing? Joint Audio-Speech Co-Reasoning","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Mila - Quebec Artificial Intelligence Institute; Concordia University","funders":"","keywords":"Joint (building); Computer science; Speech recognition; Engineering","score_opus":0.015094032679890327,"score_gpt":0.2614817200377479,"score_spread":0.24638768735785757,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408354432","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":[0.5641683,0.004914726,0.32320923,0.00814218,0.000912297,0.0007663078,0.042367186,0.013760502,0.0417593],"genre_scores_gemma":[0.85383564,0.00048509674,0.11331279,0.0010968735,0.000087723856,0.00015389087,0.026146272,0.0004858501,0.0043959464],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99565685,0.0017977188,0.0002282918,0.0014266586,0.00058624,0.00030438107],"domain_scores_gemma":[0.9899631,0.006269385,0.00067466195,0.0018991306,0.00067981525,0.00051383267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035517274,0.0016111895,0.0008004939,0.00062387896,0.00086300645,0.002332166,0.0017617564,0.0023203006,0.00639674],"category_scores_gemma":[0.021048408,0.00039532015,0.0018780938,0.0006109329,0.00082495215,0.0037087046,0.0016087146,0.0023184777,0.002195648],"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":[0.008625937,0.0020428353,0.13120645,0.0035674276,0.0017509343,0.001680731,0.0057323086,0.13336277,0.035038345,0.03817293,0.13098375,0.5078356],"study_design_scores_gemma":[0.00044342215,0.00067858206,0.023478124,0.00039128377,0.0005453884,0.0011867321,0.0035639044,0.77297634,0.027245823,0.10232318,0.066960946,0.00020627445],"about_ca_topic_score_codex":0.011562247,"about_ca_topic_score_gemma":0.017806115,"teacher_disagreement_score":0.011562247,"about_ca_system_score_codex":0.0011161349,"about_ca_system_score_gemma":0.0015799325,"threshold_uncertainty_score":0.022989929},"labels":[],"label_agreement":null},{"id":"W4408933666","doi":"10.1016/j.neucom.2025.130074","title":"FastTalker: An unified framework for generating speech and conversational gestures from text","year":2025,"lang":"en","type":"article","venue":"Neurocomputing","topic":"Speech and dialogue systems","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":"Gesture; Computer science; Natural language processing; Speech recognition; Artificial intelligence","score_opus":0.019291049257923104,"score_gpt":0.27386237707600436,"score_spread":0.25457132781808123,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408933666","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":[0.0018480921,0.00014423233,0.9362547,0.000039851802,0.00007592295,0.00014657242,0.0015066486,0.05885342,0.0011304829],"genre_scores_gemma":[0.06734293,0.0003635717,0.9091613,0.00018174492,0.00009305686,0.0007166385,0.0062243403,0.007369075,0.008547404],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99945134,0.00008662902,0.00003885197,0.0001747016,0.00017979176,0.00006865152],"domain_scores_gemma":[0.9994411,0.0002398371,0.000033914617,0.00009746293,0.0001312055,0.000056493136],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009667635,0.0021416112,0.0014363978,0.0014027521,0.00079183327,0.0023013745,0.0034066038,0.0016442453,0.023652356],"category_scores_gemma":[0.0025740785,0.0011351932,0.0015481005,0.00081308495,0.00055518455,0.0022754755,0.0022883127,0.0016088308,0.00857389],"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":[0.0015128979,0.00022596275,0.0012016654,0.001055597,0.00028171772,0.0007240545,0.00082471943,0.03970885,0.07313936,0.0229558,0.072561264,0.7858081],"study_design_scores_gemma":[0.00018848262,0.00021378379,0.001251858,0.00012310136,0.00013739264,0.0005755392,0.00019349006,0.82050294,0.078279115,0.031007629,0.06733373,0.00019294942],"about_ca_topic_score_codex":0.0063480767,"about_ca_topic_score_gemma":0.011389687,"teacher_disagreement_score":0.023652356,"about_ca_system_score_codex":0.0006435007,"about_ca_system_score_gemma":0.0010912805,"threshold_uncertainty_score":0.07912499},"labels":[],"label_agreement":null},{"id":"W4409371019","doi":"10.1038/s42003-025-07963-7","title":"The FinnBrain multimodal neonatal template and atlas collection","year":2025,"lang":"en","type":"article","venue":"Communications Biology","topic":"Speech and dialogue systems","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":"Mental Health Research Canada; Hospital for Sick Children; Montreal Neurological Institute and Hospital","funders":"Turun Yliopistollinen Keskussairaala; Turun Yliopisto; Hospital for Sick Children; Aalto-Yliopisto; Sickkids Research Institute; McGill University","keywords":"Atlas (anatomy); Computer science; Medicine; Anatomy","score_opus":0.017105026296877424,"score_gpt":0.29354282627434786,"score_spread":0.2764377999774704,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409371019","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025703857,0.0010283594,0.85127306,0.0007822458,0.0005146018,0.0033760406,0.06513132,0.01784915,0.03434134],"genre_scores_gemma":[0.050413426,0.0009033705,0.8610734,0.00052839314,0.00009722665,0.009521928,0.051424515,0.00808137,0.01795649],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986779,0.00022311912,0.00023366633,0.0003428667,0.0004322141,0.00009019273],"domain_scores_gemma":[0.9972517,0.00051295763,0.00022446034,0.00090827764,0.00094558136,0.00015703039],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0033441877,0.0010639238,0.0009076759,0.0029043949,0.0011801695,0.0017544066,0.002021725,0.0012375484,0.031100323],"category_scores_gemma":[0.007737683,0.00096665113,0.0008727733,0.0022229415,0.0006898229,0.0013258385,0.0020483278,0.0014896096,0.01439095],"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":[0.00093982555,0.00017499835,0.013477557,0.0017032013,0.00013389697,0.0036552686,0.0027155776,0.0083907815,0.074405536,0.044648763,0.30617654,0.5435781],"study_design_scores_gemma":[0.00007884147,0.0002575906,0.023238672,0.0007261683,0.00012908998,0.0075349896,0.00061459065,0.019464659,0.085190356,0.015113913,0.8474177,0.00023344923],"about_ca_topic_score_codex":0.009106569,"about_ca_topic_score_gemma":0.016142366,"teacher_disagreement_score":0.031100323,"about_ca_system_score_codex":0.0016010421,"about_ca_system_score_gemma":0.006132079,"threshold_uncertainty_score":0.10404098},"labels":[],"label_agreement":null},{"id":"W4409526822","doi":"10.5430/wjel.v15n5p390","title":"Mobile-Assisted Shadowing: Transforming Pronunciation for Arab English Learners","year":2025,"lang":"en","type":"article","venue":"World Journal of English Language","topic":"Speech and dialogue systems","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":"Ajman University","keywords":"Pronunciation; Computer science; Linguistics","score_opus":0.010182062907421187,"score_gpt":0.255023676210659,"score_spread":0.24484161330323784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409526822","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":[0.99367625,0.0002016354,0.0035958528,0.000093475326,0.000017507171,0.000048970025,0.000028276694,0.00008278122,0.0022551317],"genre_scores_gemma":[0.98176306,0.00038405068,0.01421774,0.000059679278,0.000013965744,0.00008080237,0.000051006096,0.000014061474,0.0034157005],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998356,0.00007809438,0.000008776472,0.000022148275,0.000026195288,0.000029022154],"domain_scores_gemma":[0.9996158,0.00018810516,0.000038183498,0.000032573134,0.000049581682,0.00007580302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004685422,0.00037475437,0.00018903,0.00012370347,0.0002686575,0.00043023442,0.00025696575,0.00030370767,0.0034250924],"category_scores_gemma":[0.0012483436,0.000101801415,0.00023810429,0.000069379385,0.00023952832,0.00043395755,0.0005414978,0.00022826213,0.00062268676],"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":[0.0013667166,0.0019485425,0.024619263,0.00094866165,0.000038466882,0.0014324719,0.025586536,0.00080572325,0.29462633,0.0006166225,0.0017901306,0.6462205],"study_design_scores_gemma":[0.0007135191,0.0484129,0.43206263,0.0006785274,0.00051695213,0.009876174,0.08812954,0.011943341,0.29285994,0.0028030875,0.11170592,0.00029741292],"about_ca_topic_score_codex":0.00049546134,"about_ca_topic_score_gemma":0.0013546391,"teacher_disagreement_score":0.0034250924,"about_ca_system_score_codex":0.00008474653,"about_ca_system_score_gemma":0.00029930798,"threshold_uncertainty_score":0.011458099},"labels":[],"label_agreement":null},{"id":"W4409576534","doi":"10.61091/jcmcc127a-116","title":"An Optimization Study of Attention Mechanism-Based Natural Language Generation Models in Multi-Round Conversations","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"Speech and dialogue systems","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":"Computer science; Mechanism (biology); Natural language generation; Natural (archaeology); Natural language processing; Natural language; Artificial intelligence; History; Physics","score_opus":0.023657450336670806,"score_gpt":0.2817597256151382,"score_spread":0.25810227527846735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409576534","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0910901,0.00076439936,0.9023553,0.0004635558,0.00005767108,0.00020869116,0.00007791067,0.00093089376,0.0040515955],"genre_scores_gemma":[0.8812784,0.00030474333,0.11345428,0.0001820313,0.00003674555,0.0002854345,0.00015556175,0.0001662987,0.004136505],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99870884,0.00052915636,0.00005594506,0.0003426369,0.00018092903,0.0001824982],"domain_scores_gemma":[0.997227,0.0019927016,0.0001731692,0.00014891662,0.00031147874,0.00014663948],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0029210465,0.0013271068,0.0010127197,0.0005750807,0.00063920394,0.0010707098,0.0016371179,0.0012244129,0.003089598],"category_scores_gemma":[0.0061867773,0.0007400443,0.0008126845,0.00043603257,0.000602514,0.0021711572,0.0012701403,0.001376867,0.00055308087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027128521,0.00021271825,0.001545469,0.00016716012,0.000081601225,0.00017611147,0.00027792205,0.8823805,0.007064532,0.011282217,0.001814064,0.094726466],"study_design_scores_gemma":[0.0000065422273,0.000034238667,0.000106591964,0.0000021571816,0.000011008705,0.00001439675,0.000012248195,0.99773395,0.0005587079,0.0013443008,0.00017153556,0.0000044426492],"about_ca_topic_score_codex":0.008231912,"about_ca_topic_score_gemma":0.007198179,"teacher_disagreement_score":0.008231912,"about_ca_system_score_codex":0.0019017906,"about_ca_system_score_gemma":0.0019987766,"threshold_uncertainty_score":0.016367972},"labels":[],"label_agreement":null},{"id":"W4409720257","doi":"10.1145/3706599.3716229","title":"Lost in Translation: A Cross-Cultural Examination of Linguistic Inaccessibility in HCI","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Saskatchewan; Carleton University","funders":"","keywords":"Translation (biology); Linguistics; Computer science; Natural language processing; Artificial intelligence; Philosophy; Chemistry","score_opus":0.03103174492960473,"score_gpt":0.3385680757677689,"score_spread":0.3075363308381641,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4409720257","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":[0.95621705,0.0048307553,0.008645916,0.004378139,0.00021881425,0.0000851995,0.000042481828,0.000043631746,0.025537986],"genre_scores_gemma":[0.99556726,0.0011627171,0.0013649047,0.0004871057,0.000037383572,0.000051118048,0.000023251645,0.00006941355,0.0012367367],"study_design_codex":"qualitative","study_design_gemma":"observational","domain_scores_codex":[0.94878834,0.03861476,0.002972786,0.002313149,0.0058672577,0.0014436261],"domain_scores_gemma":[0.93429667,0.045798022,0.004626173,0.005778188,0.00836651,0.0011344922],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.041430343,0.0007870421,0.000863178,0.006039104,0.010529205,0.014266791,0.0016402791,0.0014917295,0.0018684088],"category_scores_gemma":[0.068652555,0.0006448867,0.00064352766,0.0050222003,0.02150306,0.010336598,0.015199187,0.0036661462,0.00024873661],"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":[0.000027110702,0.000009114716,0.004873299,0.0001281152,0.000014596826,0.0002686687,0.9821812,0.000025396574,0.00035301642,0.0021080296,0.00013912478,0.009872455],"study_design_scores_gemma":[0.000007916842,0.00009285569,0.012710111,0.0005553512,0.00005226048,0.0015314799,0.9607281,0.0001968355,0.0007496109,0.0027083734,0.020620903,0.00004620732],"about_ca_topic_score_codex":0.007821363,"about_ca_topic_score_gemma":0.008000216,"teacher_disagreement_score":0.041430343,"about_ca_system_score_codex":0.0040228795,"about_ca_system_score_gemma":0.0036288141,"threshold_uncertainty_score":0.21910721},"labels":[],"label_agreement":null},{"id":"W4410298224","doi":"10.1109/hri61500.2025.10974224","title":"I Know You're Listening: Adaptive Voice for HRI","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Active listening; Computer science; Speech recognition; Human–computer interaction; Psychology; Communication","score_opus":0.022456981002300168,"score_gpt":0.27053481416820396,"score_spread":0.2480778331659038,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410298224","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":[0.117906414,0.006252505,0.7992106,0.002697347,0.0010254773,0.0006383725,0.00078188186,0.012509119,0.058978252],"genre_scores_gemma":[0.65453804,0.002052357,0.32167432,0.0013176367,0.00045825445,0.0003544461,0.00076687866,0.00069456594,0.018143535],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995396,0.00015728112,0.00002018658,0.00009451255,0.0001352609,0.00005319602],"domain_scores_gemma":[0.99901927,0.0005449366,0.000054576903,0.0001402859,0.00014930667,0.00009161851],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00096586253,0.00046472708,0.00028405635,0.00030084114,0.00040731678,0.0011500869,0.0010766176,0.0007140665,0.008466677],"category_scores_gemma":[0.002818123,0.00014193985,0.00026574184,0.0002565151,0.0005070185,0.0011364758,0.0011236233,0.00064623315,0.0032936118],"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":[0.00086015114,0.00028510054,0.0018294421,0.00066311506,0.00007011474,0.0003985589,0.0021640556,0.0042037503,0.13191397,0.006988346,0.013901147,0.8367223],"study_design_scores_gemma":[0.00047579527,0.0035164224,0.026518371,0.00082036265,0.0006496879,0.0056131645,0.005187587,0.31373647,0.20451832,0.052780412,0.3856853,0.0004981287],"about_ca_topic_score_codex":0.00051552383,"about_ca_topic_score_gemma":0.0014465036,"teacher_disagreement_score":0.008466677,"about_ca_system_score_codex":0.00022650843,"about_ca_system_score_gemma":0.00028924053,"threshold_uncertainty_score":0.028323889},"labels":[],"label_agreement":null},{"id":"W4410332612","doi":"10.18162/ritpu-2025-v22n1-08","title":"Conception et évaluation d’un agent conversationnel enrichi par la génération augmentée par récupération : effet sur l’acquisition des connaissances des personnes apprenantes, l’utilisabilité perçue et l’expérience d’interaction","year":2025,"lang":"fr","type":"article","venue":"Revue internationale des technologies en pédagogie universitaire","topic":"Speech and dialogue systems","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 TÉLUQ","funders":"","keywords":"Augment; Humanities; Psychology; Art; Philosophy","score_opus":0.04106665658654087,"score_gpt":0.28072243555418347,"score_spread":0.2396557789676426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410332612","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":[0.9474787,0.000508091,0.048398424,0.00012073781,0.00004001254,0.0008251946,0.00008137872,0.00036405423,0.0021833517],"genre_scores_gemma":[0.862483,0.0004980011,0.13002974,0.00005871086,0.000022133245,0.0011914171,0.00022208487,0.000068313755,0.0054266425],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.9989312,0.0005030748,0.00010725268,0.00020072974,0.00020641994,0.00005129782],"domain_scores_gemma":[0.997437,0.0013957854,0.00016651404,0.00024122934,0.0005896116,0.00016983031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024869482,0.0006066935,0.0005882919,0.00030712932,0.00056033087,0.0014572192,0.00070797553,0.0011390825,0.0030120139],"category_scores_gemma":[0.005021155,0.0003698515,0.0005895245,0.00014908421,0.0005960495,0.0012484173,0.0007642745,0.0004872562,0.00045824586],"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":[0.0070950915,0.0042796587,0.007801665,0.0023553527,0.000281719,0.0006661968,0.017182795,0.0060950597,0.6661991,0.0040586,0.0006898671,0.28329486],"study_design_scores_gemma":[0.0024400325,0.053491917,0.05078146,0.00038239214,0.0032174909,0.003144494,0.008214928,0.081205025,0.72904587,0.0016333027,0.06606893,0.00037418935],"about_ca_topic_score_codex":0.0015304505,"about_ca_topic_score_gemma":0.0010467278,"teacher_disagreement_score":0.0030120139,"about_ca_system_score_codex":0.0003755363,"about_ca_system_score_gemma":0.0008120915,"threshold_uncertainty_score":0.013152361},"labels":[],"label_agreement":null},{"id":"W4410887599","doi":"10.1109/isqed65160.2025.11014310","title":"Evaluating LLM-Based Communicative Agents for Verilog Design","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Intel Corporation","keywords":"Computer science; Verilog; Computer architecture; Embedded system; Field-programmable gate array","score_opus":0.22324039934045473,"score_gpt":0.42716511565994497,"score_spread":0.20392471631949025,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410887599","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":[0.6905199,0.00051620055,0.2775526,0.0007599062,0.00015351777,0.0009416273,0.0006416468,0.016363213,0.012551355],"genre_scores_gemma":[0.78451943,0.00010090205,0.21238351,0.00012653501,0.000012624855,0.00038439725,0.00058020867,0.00034229728,0.0015501222],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9959156,0.002534676,0.00021056963,0.00029319577,0.0008883547,0.00015754267],"domain_scores_gemma":[0.9855408,0.010857507,0.000590447,0.0016021415,0.0011202359,0.0002888031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063459803,0.0009921432,0.00035173542,0.00079472846,0.0004004578,0.0009279153,0.0018115185,0.0014583721,0.0022500993],"category_scores_gemma":[0.020907454,0.00050283805,0.00047397017,0.00035279765,0.0010216604,0.0014085585,0.0011067669,0.0012185879,0.0005159026],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0013549303,0.0014646086,0.00524473,0.00090889493,0.00014823752,0.00020189876,0.0012106816,0.77212995,0.028384233,0.0133025525,0.004364806,0.17128453],"study_design_scores_gemma":[0.00011934546,0.0004680121,0.00030515366,0.000019053452,0.000021192955,0.000026931013,0.000077184144,0.98355156,0.012207865,0.0013066211,0.0018827271,0.000014413057],"about_ca_topic_score_codex":0.0038305344,"about_ca_topic_score_gemma":0.0068633263,"teacher_disagreement_score":0.0063459803,"about_ca_system_score_codex":0.0022024035,"about_ca_system_score_gemma":0.0020438489,"threshold_uncertainty_score":0.03356117},"labels":[],"label_agreement":null},{"id":"W4410915170","doi":"10.1007/978-3-031-93806-1_14","title":"FastTalker: Jointly Generating Speech and Conversational Gestures from Text","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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":"Computer science; Gesture; Speech recognition; Natural language processing; Artificial intelligence; Speech synthesis; Human–computer interaction","score_opus":0.013212706258999223,"score_gpt":0.22623203590357116,"score_spread":0.21301932964457193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4410915170","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014322221,0.0004789597,0.9066028,0.00010419827,0.00038411721,0.0003226573,0.0022566803,0.06864022,0.006888163],"genre_scores_gemma":[0.11947943,0.00045720537,0.83323354,0.00021023375,0.00017678674,0.00081164605,0.007460363,0.009809185,0.02836169],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995745,0.00008333703,0.000019208946,0.00013895355,0.00014305902,0.00004095283],"domain_scores_gemma":[0.99944144,0.00035815776,0.000017791013,0.000058291327,0.00008091816,0.000043421594],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007102438,0.0020399448,0.0015554166,0.0007456679,0.0005381392,0.0014817804,0.00230275,0.0015236246,0.0302456],"category_scores_gemma":[0.0016560544,0.0009927966,0.0010158583,0.00056228874,0.00048721582,0.0017066736,0.002170843,0.0009198902,0.010909488],"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":[0.0010981896,0.00013685958,0.00049972604,0.0005964365,0.00014688492,0.00053062633,0.0004777081,0.015103377,0.13962413,0.0046934085,0.041975018,0.7951176],"study_design_scores_gemma":[0.0005267191,0.00058366515,0.0025802196,0.00013839736,0.0002194582,0.0012802562,0.00045861496,0.7082311,0.19030358,0.023586355,0.07188268,0.00020886736],"about_ca_topic_score_codex":0.0026564416,"about_ca_topic_score_gemma":0.0036513903,"teacher_disagreement_score":0.0302456,"about_ca_system_score_codex":0.0003713918,"about_ca_system_score_gemma":0.00048308267,"threshold_uncertainty_score":0.10118163},"labels":[],"label_agreement":null},{"id":"W4411019470","doi":"10.1109/ojcs.2025.3576725","title":"VoiceTalk: A No-Code Approach for Creating Voice-Controlled Smart Home Applications","year":2025,"lang":"en","type":"article","venue":"IEEE Open Journal of the Computer Society","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"China Medical University Hospital","keywords":"Computer science; Code (set theory); Programming language; Multimedia","score_opus":0.020876657839096528,"score_gpt":0.2766506871753561,"score_spread":0.2557740293362596,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411019470","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009143487,0.00021524902,0.8600464,0.00031034756,0.00035196246,0.00066601817,0.00031730422,0.10589725,0.02305199],"genre_scores_gemma":[0.15967804,0.000578369,0.6978463,0.0017408809,0.00031823042,0.0017164936,0.0034261823,0.06728029,0.067415185],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99671054,0.0005711311,0.00021201091,0.00044174102,0.0017635584,0.00030097787],"domain_scores_gemma":[0.99542075,0.0014243255,0.00026559792,0.0013451268,0.0011134108,0.0004307315],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019911884,0.001452564,0.0005542598,0.0008845949,0.0006870198,0.0027246561,0.0042604534,0.0015008614,0.01699215],"category_scores_gemma":[0.009646517,0.001154555,0.0009684537,0.00025077522,0.0012031266,0.003757325,0.0058691604,0.002259271,0.009294518],"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":[0.0013001822,0.00064229954,0.0025639578,0.0013894405,0.00016692115,0.002168915,0.0029229394,0.0070149573,0.22630502,0.05458717,0.1165156,0.5844227],"study_design_scores_gemma":[0.00025297704,0.00058929704,0.0018459659,0.0002905953,0.00014773762,0.00185866,0.00046284945,0.10535958,0.24135862,0.021630356,0.6259497,0.00025359422],"about_ca_topic_score_codex":0.00087875425,"about_ca_topic_score_gemma":0.0014855016,"teacher_disagreement_score":0.01699215,"about_ca_system_score_codex":0.0007595627,"about_ca_system_score_gemma":0.0010025053,"threshold_uncertainty_score":0.056844413},"labels":[],"label_agreement":null},{"id":"W4411117037","doi":"10.18653/v1/w14-4318","title":"Extractive Summarization and Dialogue Act Modeling on Email Threads: An Integrated Probabilistic Approach","year":2014,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Automatic summarization; Computer science; Probabilistic logic; World Wide Web; Information retrieval; Natural language processing; Artificial intelligence","score_opus":0.02792343823344051,"score_gpt":0.23795131053724813,"score_spread":0.21002787230380762,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411117037","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0055457233,0.00026254216,0.99248695,0.00018931512,0.000025009276,0.000058666556,0.00014992378,0.00091042573,0.00037143065],"genre_scores_gemma":[0.35472423,0.0007551345,0.6374984,0.00023097961,0.00047298212,0.0005343427,0.0017832652,0.00037766382,0.003623032],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9969496,0.001225569,0.0002538841,0.00084036705,0.00059421186,0.00013640933],"domain_scores_gemma":[0.99366647,0.0039955396,0.0007782328,0.0005514917,0.0008406349,0.00016751983],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003292934,0.0013202438,0.0013613222,0.0023423033,0.0006538654,0.0018619081,0.0019989202,0.0014319284,0.0016089734],"category_scores_gemma":[0.009743265,0.000811291,0.0017354938,0.0013370787,0.0006381512,0.003229981,0.0015643225,0.0017861165,0.0009640547],"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":[0.0005694892,0.00039254827,0.005787487,0.00070398184,0.00048030473,0.00030402883,0.0014341834,0.3262132,0.017879168,0.029876688,0.0067597115,0.6095993],"study_design_scores_gemma":[0.000013828229,0.000066455934,0.00083085895,0.000021313685,0.00006730686,0.000053039512,0.000062729894,0.9763857,0.0021269633,0.017944312,0.0024041887,0.00002324464],"about_ca_topic_score_codex":0.0034470966,"about_ca_topic_score_gemma":0.0061715594,"teacher_disagreement_score":0.0034470966,"about_ca_system_score_codex":0.00093357614,"about_ca_system_score_gemma":0.0016059865,"threshold_uncertainty_score":0.017414927},"labels":[],"label_agreement":null},{"id":"W4411117042","doi":"10.18653/v1/2005.sigdial-1.15","title":"Developing City Name Acquisition Strategies in Spoken Dialogue Systems Via User Simulation","year":2005,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Natural language processing; Human–computer interaction; Artificial intelligence","score_opus":0.029599037712071355,"score_gpt":0.2760545688091827,"score_spread":0.24645553109711138,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411117042","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.18787284,0.00008955088,0.80585706,0.00008340336,0.000012736458,0.00034776633,0.000037818085,0.0043807165,0.0013180192],"genre_scores_gemma":[0.65315425,0.00009174253,0.34480098,0.00005377215,0.0000077724835,0.00043248793,0.00012721393,0.00033018063,0.0010015264],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954332,0.00327169,0.00027445835,0.00043118492,0.00043945533,0.00015000733],"domain_scores_gemma":[0.9787081,0.018179785,0.00056947046,0.001247172,0.0009296709,0.00036587307],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004605371,0.0010170111,0.0007815336,0.00039179873,0.00049784494,0.0019474243,0.0024002953,0.0014457881,0.0023625721],"category_scores_gemma":[0.02004016,0.0008509252,0.0005050212,0.00016060231,0.0014304421,0.0024841193,0.0021904483,0.0010475059,0.000506833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0032241638,0.0015250728,0.014037162,0.0014706961,0.00039751932,0.0016733897,0.02302479,0.43482387,0.21618631,0.035432354,0.0016327227,0.26657197],"study_design_scores_gemma":[0.00020717704,0.0007409424,0.0006007664,0.000049028233,0.00009325564,0.00033747524,0.0010967058,0.89622897,0.08985766,0.0041926797,0.006505415,0.00009000326],"about_ca_topic_score_codex":0.0009415779,"about_ca_topic_score_gemma":0.0009797137,"teacher_disagreement_score":0.004605371,"about_ca_system_score_codex":0.0006613431,"about_ca_system_score_gemma":0.00083770393,"threshold_uncertainty_score":0.024355829},"labels":[],"label_agreement":null},{"id":"W4411119823","doi":"10.18653/v1/2025.wnut-1","title":"Proceedings of the Tenth Workshop on Noisy and User-generated Text","year":2025,"lang":"en","type":"paratext","venue":"","topic":"Speech and dialogue systems","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":"Social Sciences and Humanities Research Council of Canada; Centre National de la Recherche Scientifique; Centre National d’Etudes Spatiales; Vlaamse regering; European Commission; Ministry of Education, Culture, Sports, Science and Technology; Villum Fonden; National Science Foundation","keywords":"Computer science; Information retrieval; World Wide Web","score_opus":0.015474702512078633,"score_gpt":0.2398620609950959,"score_spread":0.22438735848301727,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411119823","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":[0.028767662,0.03951327,0.7475027,0.048602354,0.023780271,0.0014482031,0.014136671,0.023839405,0.07240953],"genre_scores_gemma":[0.11218633,0.023830762,0.38543668,0.008586531,0.009986181,0.0018136473,0.06608087,0.01703587,0.37504315],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.98987633,0.0046833507,0.0007818152,0.001857584,0.0022979954,0.00050293555],"domain_scores_gemma":[0.9674741,0.018764162,0.0005484664,0.005600955,0.0059523596,0.0016598728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01416506,0.0020384446,0.002985434,0.0032059404,0.0019792374,0.012766896,0.0042224755,0.0036496923,0.06414055],"category_scores_gemma":[0.028856352,0.001062357,0.0022669835,0.0032412105,0.0031397361,0.013867476,0.007820075,0.0039833616,0.038815897],"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":[0.0010967068,0.00035609477,0.0013814472,0.0013105937,0.0002481063,0.001764256,0.0033034564,0.003968796,0.010274066,0.012837914,0.47985512,0.48360336],"study_design_scores_gemma":[0.00009380836,0.00017699385,0.0021104298,0.0007470561,0.00013481404,0.001056495,0.0023666047,0.023966003,0.008741471,0.02569026,0.9347813,0.00013467575],"about_ca_topic_score_codex":0.005220948,"about_ca_topic_score_gemma":0.0070144087,"teacher_disagreement_score":0.06414055,"about_ca_system_score_codex":0.0019745897,"about_ca_system_score_gemma":0.0029567555,"threshold_uncertainty_score":0.21457154},"labels":[],"label_agreement":null},{"id":"W4411233265","doi":"10.1109/llm4code66737.2025.00030","title":"Mix-of-Language-Experts Architecture for Multilingual Programming","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Computer science; Architecture; Programming language; Natural language processing; Computer architecture; Artificial intelligence; Software engineering","score_opus":0.012303991649220391,"score_gpt":0.2947003821871274,"score_spread":0.282396390537907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411233265","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.026650075,0.00052536844,0.9535622,0.0002597118,0.00006702662,0.00008806946,0.00014019302,0.01627307,0.0024343699],"genre_scores_gemma":[0.5509963,0.00038726022,0.43527597,0.00064769696,0.00006981297,0.00030139872,0.0010047735,0.00097514427,0.0103416825],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99907124,0.00027353395,0.0000500593,0.00033233903,0.0001587674,0.00011413722],"domain_scores_gemma":[0.99893457,0.00044727523,0.00006476663,0.0002607864,0.00020342765,0.000089175664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017588197,0.0011952468,0.0008293461,0.0006650422,0.0005304142,0.0010162111,0.002925993,0.0014358152,0.005812014],"category_scores_gemma":[0.0038196815,0.0008606337,0.0011050523,0.0005374518,0.0008543029,0.0032993099,0.0031178794,0.0027861586,0.0029788157],"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":[0.0008220085,0.00047804893,0.0033698645,0.00029717092,0.00042167702,0.00034657124,0.00073070126,0.34600565,0.032545492,0.0140527515,0.00991159,0.59101844],"study_design_scores_gemma":[0.000017400993,0.00006854924,0.00019596984,0.000011705604,0.00003584997,0.00006492143,0.000045587367,0.98279035,0.0067430143,0.0074404576,0.0025641231,0.000022095272],"about_ca_topic_score_codex":0.0070385295,"about_ca_topic_score_gemma":0.014158914,"teacher_disagreement_score":0.0070385295,"about_ca_system_score_codex":0.0010335358,"about_ca_system_score_gemma":0.0013134349,"threshold_uncertainty_score":0.019443154},"labels":[],"label_agreement":null},{"id":"W4411464857","doi":"10.1007/s00146-025-02413-8","title":"Alexa, Google Assistant, and Siri’s language options: how voice assistants reproduce monoglossic language ideologies","year":2025,"lang":"en","type":"article","venue":"AI & Society","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":2,"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":"Social Sciences and Humanities Research Council of Canada","keywords":"Ideology; Computer science; Performing arts; Linguistics; World Wide Web; Visual arts; Art; Political science","score_opus":0.01109080690043218,"score_gpt":0.27196495601773246,"score_spread":0.2608741491173003,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411464857","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":[0.24250776,0.0005233788,0.107142106,0.005822076,0.00075934944,0.0000993438,0.00041871954,0.007559556,0.6351677],"genre_scores_gemma":[0.892179,0.00022819462,0.0306148,0.00076210755,0.00006690176,0.00005642011,0.00031993157,0.0026047365,0.073167905],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.99904495,0.00039349482,0.00002762646,0.00013733408,0.00026171468,0.0001348059],"domain_scores_gemma":[0.99749607,0.0011570972,0.000097582284,0.0006325235,0.0003987089,0.00021792194],"candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0012317431,0.0003587686,0.00022465101,0.00073489005,0.0017677626,0.0056216917,0.0009252848,0.0014133656,0.014638605],"category_scores_gemma":[0.0087513635,0.00031770772,0.00030748497,0.00046790903,0.0034345475,0.006524063,0.0032977154,0.001359744,0.005571639],"study_design_candidate":"qualitative","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005735455,0.000108876506,0.006447411,0.0001909292,0.000041398267,0.0008170685,0.05382758,0.0028960134,0.013992089,0.49171284,0.07232765,0.35706466],"study_design_scores_gemma":[0.00019133446,0.0001943038,0.005305877,0.00022817029,0.00014648648,0.0016197775,0.04249609,0.0313328,0.020535719,0.276588,0.6211011,0.00026039555],"about_ca_topic_score_codex":0.012971803,"about_ca_topic_score_gemma":0.019935867,"teacher_disagreement_score":0.99823225,"about_ca_system_score_codex":0.00087784044,"about_ca_system_score_gemma":0.0015056618,"threshold_uncertainty_score":0.048970997},"labels":[],"label_agreement":null},{"id":"W4411856963","doi":"10.5220/0013524000003979","title":"An NLP-Based Framework Leveraging Email and Multimodal User Data","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Polytechnique Montréal","funders":"","keywords":"Computer science; Natural language processing; Artificial intelligence; Information retrieval","score_opus":0.02857856996953394,"score_gpt":0.30189873515223553,"score_spread":0.2733201651827016,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4411856963","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":[0.007586827,0.00033190602,0.9570954,0.0003290881,0.00014643729,0.00027016288,0.0019272242,0.030157272,0.0021558069],"genre_scores_gemma":[0.12765753,0.0003160475,0.8563366,0.00034517798,0.00019494355,0.00041874725,0.006762241,0.0011813798,0.006787377],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99895144,0.00019664336,0.00007975788,0.0003501095,0.00033155337,0.00009042864],"domain_scores_gemma":[0.9987728,0.00045630828,0.000056700323,0.00021948149,0.00038113093,0.00011354852],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014852753,0.0011824701,0.001325047,0.002353122,0.0010894861,0.002200534,0.0018979333,0.0020695785,0.0059630587],"category_scores_gemma":[0.003555074,0.0005940104,0.0011509045,0.0019124338,0.00048645728,0.0025643276,0.002438437,0.001804955,0.005482235],"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":[0.0009483698,0.00080810173,0.002831143,0.00061300036,0.00026303917,0.0011227976,0.0005375105,0.046403877,0.0770929,0.01378485,0.047448315,0.8081462],"study_design_scores_gemma":[0.000034621364,0.000080069025,0.0009009325,0.000033596494,0.000088954504,0.00027873288,0.0001222341,0.9546659,0.015634658,0.011699459,0.01640414,0.000056745987],"about_ca_topic_score_codex":0.011779631,"about_ca_topic_score_gemma":0.01829803,"teacher_disagreement_score":0.011779631,"about_ca_system_score_codex":0.00074180664,"about_ca_system_score_gemma":0.002099711,"threshold_uncertainty_score":0.023422122},"labels":[],"label_agreement":null},{"id":"W4412378051","doi":"10.1145/3726302.3730335","title":"Tip of the Tongue Query Elicitation for Simulated Evaluation","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Microsoft (Canada)","funders":"National Institute of Standards and Technology","keywords":"Computer science; Tongue; Information retrieval; Query optimization; Artificial intelligence; Natural language processing; Linguistics","score_opus":0.01673934936747049,"score_gpt":0.3067126234972936,"score_spread":0.2899732741298231,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412378051","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":[0.4933088,0.0017384002,0.45014077,0.0012623008,0.00041919405,0.0070767477,0.009626084,0.014533005,0.021894654],"genre_scores_gemma":[0.7704482,0.00026270098,0.21221231,0.0005032738,0.000048036796,0.0068942923,0.006281441,0.0005229919,0.0028267025],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9918967,0.005846589,0.0004810564,0.00057759805,0.0009465974,0.0002514456],"domain_scores_gemma":[0.9636625,0.028870616,0.0008157663,0.0032678952,0.0027265253,0.0006567775],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0076337676,0.0014436371,0.000984112,0.00077107456,0.0004902462,0.0015021404,0.0024444433,0.001827201,0.0072103958],"category_scores_gemma":[0.03623712,0.00058706943,0.00075416017,0.0007989967,0.00082458195,0.0013506962,0.0023723668,0.0014606772,0.0019351587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.007263787,0.0047309725,0.010181235,0.0040339152,0.0003975955,0.00082637777,0.0026633188,0.71182716,0.041694928,0.018209256,0.04101791,0.15715365],"study_design_scores_gemma":[0.0005990775,0.0009362252,0.0009617663,0.00007220674,0.00003128077,0.00007785772,0.00020422289,0.977235,0.008105407,0.005938186,0.0057896157,0.000049131984],"about_ca_topic_score_codex":0.004687539,"about_ca_topic_score_gemma":0.006048978,"teacher_disagreement_score":0.0076337676,"about_ca_system_score_codex":0.0017823345,"about_ca_system_score_gemma":0.0014823935,"threshold_uncertainty_score":0.040371656},"labels":[],"label_agreement":null},{"id":"W4412742613","doi":"10.1109/iccsp64183.2025.11089189","title":"An AI Powered Voice Assistant for Enhanced User Interaction","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Computer science; Human–computer interaction","score_opus":0.012049478287288267,"score_gpt":0.3124178389158079,"score_spread":0.3003683606285196,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412742613","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":[0.09291981,0.0011068785,0.82411635,0.001219831,0.0009133164,0.00074379134,0.00031972895,0.019406192,0.059254147],"genre_scores_gemma":[0.5083087,0.0006730776,0.4034023,0.0015636393,0.00062230736,0.0007130062,0.00047579914,0.0009466403,0.08329459],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99911433,0.00027089877,0.000051344912,0.00013997676,0.0003598017,0.00006365381],"domain_scores_gemma":[0.99897516,0.00047298867,0.000047850364,0.00013452898,0.00024368952,0.0001258725],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087912654,0.0005721819,0.0004716918,0.00043000196,0.00061086094,0.0013165522,0.0011561045,0.00111774,0.015105694],"category_scores_gemma":[0.0027955647,0.00018875768,0.00031700186,0.0001816386,0.00039609987,0.0015276697,0.0021291927,0.0005692974,0.0048180036],"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":[0.0016742239,0.0005380868,0.0013277994,0.0006637316,0.00007800264,0.0019729945,0.0038373435,0.0027517406,0.27605024,0.021265497,0.02186201,0.66797835],"study_design_scores_gemma":[0.00065540994,0.0039473767,0.0045884224,0.00032274763,0.00034104064,0.010575082,0.0016465978,0.1397945,0.15444113,0.018980252,0.6643496,0.00035782225],"about_ca_topic_score_codex":0.00025105343,"about_ca_topic_score_gemma":0.0003998177,"teacher_disagreement_score":0.015105694,"about_ca_system_score_codex":0.00017259542,"about_ca_system_score_gemma":0.00041279674,"threshold_uncertainty_score":0.050533593},"labels":[],"label_agreement":null},{"id":"W4412874007","doi":"10.1007/978-3-031-98459-4_20","title":"Beyond Static Measures: Temporal Analysis of Lexical Alignment in Human-Human Learning With a Teachable Robot","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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","funders":"","keywords":"Computer science; Robot; Artificial intelligence; Human–computer interaction; Human–robot interaction; Natural language processing; Computer vision","score_opus":0.018535130373837708,"score_gpt":0.26561175185105806,"score_spread":0.24707662147722037,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412874007","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3879113,0.002662335,0.5936314,0.0004437153,0.00014510364,0.000065761844,0.0008597381,0.0015442623,0.01273636],"genre_scores_gemma":[0.9303061,0.00035906344,0.064809605,0.000050016475,0.00004996227,0.000044190852,0.00056373974,0.00035045264,0.0034668306],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9993717,0.00021189326,0.000037338938,0.00017103241,0.00014754773,0.00006055982],"domain_scores_gemma":[0.99691296,0.0020244666,0.0002899504,0.0002441336,0.0003734056,0.00015510649],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012180656,0.00032268808,0.0004524683,0.001902035,0.00055645395,0.0020043345,0.0007298225,0.0004691312,0.0042103105],"category_scores_gemma":[0.0067088758,0.00025082016,0.00031679642,0.0026913353,0.00060983596,0.0028442228,0.0009740471,0.00071691733,0.0010708139],"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":[0.0012619676,0.0003412535,0.022305237,0.0003305893,0.00018345399,0.0004255284,0.0016329002,0.031270813,0.06806362,0.04055144,0.0049158786,0.8287173],"study_design_scores_gemma":[0.00003437565,0.00033685233,0.06947474,0.0000798059,0.00010506657,0.0004057896,0.0023090267,0.78559196,0.02074023,0.1128607,0.007959649,0.00010178187],"about_ca_topic_score_codex":0.0033486534,"about_ca_topic_score_gemma":0.0040886793,"teacher_disagreement_score":0.0042103105,"about_ca_system_score_codex":0.00049646286,"about_ca_system_score_gemma":0.0005947522,"threshold_uncertainty_score":0.014084935},"labels":[],"label_agreement":null},{"id":"W4412888761","doi":"10.18653/v1/2025.findings-acl.111","title":"Drop Dropout on Single Epoch Language Model Pretraining","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Canadian Institute for Advanced Research","keywords":"Dropout (neural networks); Drop out; Computer science; Drop (telecommunication); Language model; Artificial intelligence; Machine learning; Economics; Telecommunications","score_opus":0.016536762691298768,"score_gpt":0.2648106750246286,"score_spread":0.2482739123333298,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4412888761","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":[0.086259656,0.0016825713,0.8624116,0.0014702193,0.0007062432,0.00024288309,0.0010066994,0.040710635,0.00550957],"genre_scores_gemma":[0.6892163,0.0006182582,0.28969687,0.0016394967,0.00015564362,0.0004597323,0.003607443,0.0025335269,0.0120727895],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906546,0.00031581023,0.000051702664,0.00022799929,0.00020018814,0.00013885602],"domain_scores_gemma":[0.9973888,0.001555198,0.00008991676,0.0005388927,0.00032215723,0.00010508294],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0021354507,0.0017265058,0.0009782116,0.0004788547,0.00057311193,0.0010304727,0.0022749212,0.0018536038,0.0069777872],"category_scores_gemma":[0.010453981,0.0006883302,0.0008948415,0.00041357582,0.00064525154,0.0021008044,0.0018443703,0.0039537544,0.0035564865],"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":[0.000963405,0.00047224705,0.0028278911,0.00049988466,0.00032882844,0.0006504718,0.00041339855,0.38810518,0.045859586,0.008239701,0.038780667,0.51285875],"study_design_scores_gemma":[0.00005043357,0.00015876991,0.0006113924,0.000034929148,0.00003603039,0.000086454595,0.000047172904,0.9661058,0.02375058,0.004021977,0.0050709974,0.000025466787],"about_ca_topic_score_codex":0.0062987097,"about_ca_topic_score_gemma":0.013065496,"teacher_disagreement_score":0.0069777872,"about_ca_system_score_codex":0.00092327385,"about_ca_system_score_gemma":0.001520035,"threshold_uncertainty_score":0.023343027},"labels":[],"label_agreement":null},{"id":"W4413925758","doi":"10.1109/icra55743.2025.11127531","title":"Robo-MUTUAL: Robotic Multimodal Task Specification via Unimodal Learning","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; Task (project management); Artificial intelligence; Human–computer interaction; Computer vision; Engineering; Systems engineering","score_opus":0.00956508267107371,"score_gpt":0.2367220622426354,"score_spread":0.2271569795715617,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4413925758","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.050259538,0.0007685532,0.92130923,0.00042540894,0.000120376644,0.00022895969,0.0010050735,0.01521216,0.010670696],"genre_scores_gemma":[0.65279937,0.00039513948,0.32594535,0.00064153067,0.00006820776,0.0007519074,0.0036826166,0.0012372291,0.014478732],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993774,0.00019659782,0.000021576247,0.00023196076,0.00009871399,0.00007366571],"domain_scores_gemma":[0.9994624,0.0002200408,0.000053440963,0.00016251675,0.00005658007,0.000044974127],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00092852773,0.0013182396,0.00048478416,0.00034821715,0.00039323804,0.00059659226,0.0013926883,0.00090777664,0.0063003064],"category_scores_gemma":[0.002886438,0.00036391208,0.00072106236,0.00024170177,0.0008664564,0.0014982675,0.0026741326,0.0015958141,0.001625521],"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":[0.0006921693,0.0004749048,0.002878624,0.0006426102,0.0001537942,0.00029427913,0.0005764101,0.2294854,0.052676197,0.016023723,0.022918224,0.6731837],"study_design_scores_gemma":[0.00005575215,0.0004084323,0.0017333073,0.00006914475,0.00003646419,0.00022101963,0.00018868031,0.9279881,0.029830867,0.025556698,0.013840337,0.00007124772],"about_ca_topic_score_codex":0.0026355016,"about_ca_topic_score_gemma":0.0061039897,"teacher_disagreement_score":0.0063003064,"about_ca_system_score_codex":0.0004859287,"about_ca_system_score_gemma":0.0009622767,"threshold_uncertainty_score":0.02107662},"labels":[],"label_agreement":null},{"id":"W4414015769","doi":"10.11159/mhci25.109","title":"Shared-Experience-Focused Utterance Generation in Dialogue Systems Using Prompt-Based LLM","year":2025,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Speech and dialogue systems","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":"Utterance; Computer science; Artificial intelligence","score_opus":0.014042657772519668,"score_gpt":0.22659530428226118,"score_spread":0.2125526465097415,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414015769","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":[0.06302158,0.00023779036,0.92582655,0.00018588049,0.00007608206,0.00050608313,0.00010827331,0.007551397,0.0024862995],"genre_scores_gemma":[0.51745474,0.00008532556,0.47935736,0.0001370545,0.00003366242,0.00057380315,0.00021466654,0.00032889834,0.0018144335],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966807,0.0021929168,0.00017168815,0.0004986186,0.0003432072,0.00011282684],"domain_scores_gemma":[0.9940919,0.0039506224,0.0005054479,0.0004913409,0.00066932495,0.0002913451],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0035962858,0.0008760389,0.0005028215,0.00038488474,0.00039450775,0.0010722771,0.0011866208,0.0009463117,0.004950903],"category_scores_gemma":[0.012121624,0.00036742206,0.0002926881,0.00019227479,0.00070717145,0.0017194337,0.0021170508,0.0006692414,0.0010619886],"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":[0.0040961057,0.0012696491,0.006313229,0.0030364003,0.00009005183,0.0024659617,0.025109256,0.061153933,0.3159582,0.029686281,0.008049201,0.5427717],"study_design_scores_gemma":[0.00083009177,0.0037117738,0.004703026,0.000366173,0.00013764449,0.0016691637,0.0046409653,0.7630279,0.14143302,0.027251733,0.05201577,0.00021274843],"about_ca_topic_score_codex":0.000262689,"about_ca_topic_score_gemma":0.00029204699,"teacher_disagreement_score":0.004950903,"about_ca_system_score_codex":0.0004661184,"about_ca_system_score_gemma":0.0007333069,"threshold_uncertainty_score":0.019019246},"labels":[],"label_agreement":null},{"id":"W4414117478","doi":"10.1017/9781108950855.008","title":"Embedding Discourse Spaces without <i>Say</i> Verbs","year":2025,"lang":"en","type":"book-chapter","venue":"Cambridge University Press eBooks","topic":"Speech and dialogue systems","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 British Columbia","funders":"","keywords":"Embedding; Semantics (computer science); Discourse analysis; Expressivity; Passive voice","score_opus":0.016329923447126044,"score_gpt":0.2253808784809159,"score_spread":0.20905095503378984,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414117478","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":[0.050989844,0.0043005566,0.29914606,0.0034768363,0.0008457516,0.000082120576,0.0002836929,0.0005851951,0.64029],"genre_scores_gemma":[0.8378548,0.0017076439,0.06929069,0.00030866088,0.0001957109,0.00013928101,0.00037266244,0.00048598245,0.08964466],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9988273,0.0007836038,0.00003757698,0.00012135066,0.00015600468,0.00007418555],"domain_scores_gemma":[0.99890983,0.0006816098,0.000057646954,0.00023279431,0.00008021613,0.00003786667],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093470386,0.00046563408,0.00021524905,0.00060717505,0.0014724728,0.004539097,0.0006187326,0.00087620754,0.0092035895],"category_scores_gemma":[0.0027047123,0.00024016564,0.00025783328,0.00085241476,0.0050121173,0.007197944,0.0024681613,0.0013550771,0.0017947776],"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":[0.000016326676,0.000007159243,0.00007054708,0.00009322905,0.0000023035977,0.000093262046,0.01608192,0.00025373575,0.0017421185,0.9593188,0.0024319405,0.019888548],"study_design_scores_gemma":[0.000009520192,0.000027378292,0.000412513,0.00027292737,0.000009747936,0.00039610895,0.015444584,0.0028106137,0.0046993527,0.4225342,0.5533644,0.000018611654],"about_ca_topic_score_codex":0.000808849,"about_ca_topic_score_gemma":0.0010962475,"teacher_disagreement_score":0.0092035895,"about_ca_system_score_codex":0.0011517407,"about_ca_system_score_gemma":0.0004938982,"threshold_uncertainty_score":0.030789077},"labels":[],"label_agreement":null},{"id":"W4414197327","doi":"10.1109/cvprw67362.2025.00056","title":"Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal Models","year":2025,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Benchmark (surveying); Comprehension; Vocabulary; Object (grammar); Benchmarking; Key (lock)","score_opus":0.04613760366182853,"score_gpt":0.32101897405613206,"score_spread":0.27488137039430355,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414197327","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":[0.37680915,0.020197581,0.32847106,0.010378631,0.0027134796,0.0015962208,0.03190678,0.16822705,0.05970007],"genre_scores_gemma":[0.68558174,0.0020068982,0.20401806,0.0050384896,0.0004729394,0.0011512651,0.07717639,0.010472236,0.014082035],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9826559,0.009724772,0.0009063719,0.003482053,0.0025579697,0.00067299686],"domain_scores_gemma":[0.964476,0.02090583,0.00090387627,0.0071127857,0.0057192994,0.0008821291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018251637,0.0041574696,0.0022493182,0.0031404928,0.001622315,0.005720255,0.0060976483,0.004008069,0.009941429],"category_scores_gemma":[0.07754095,0.0009652366,0.0020412167,0.0029176832,0.0019493864,0.010376683,0.006016554,0.0055487063,0.007693517],"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":[0.0017676285,0.0007283968,0.018220231,0.004458192,0.0010145666,0.0011830688,0.0022977493,0.09700255,0.016932694,0.011891585,0.2846072,0.5598961],"study_design_scores_gemma":[0.00033401165,0.0008676931,0.010118887,0.0010600978,0.0004152145,0.0010759624,0.003383128,0.8101196,0.031882294,0.023769025,0.11667184,0.00030223303],"about_ca_topic_score_codex":0.023004372,"about_ca_topic_score_gemma":0.028564753,"teacher_disagreement_score":0.023004372,"about_ca_system_score_codex":0.0043715937,"about_ca_system_score_gemma":0.004035451,"threshold_uncertainty_score":0.09652507},"labels":[],"label_agreement":null},{"id":"W4414720636","doi":"10.1007/978-981-96-7511-1_38","title":"Recipal: An AI-Based Multi-modal Recipe Generator","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Recipe; Generator (circuit theory); Macro; Upload; Product (mathematics); Bitwise operation","score_opus":0.022874164083001802,"score_gpt":0.25419540952279257,"score_spread":0.23132124543979077,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414720636","genre_codex":"methods","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":[0.0033971618,0.00014374155,0.87601066,0.00017255469,0.00023229739,0.00020387987,0.0016602267,0.10317117,0.015008292],"genre_scores_gemma":[0.10587851,0.00024002422,0.84020376,0.00046275812,0.00011280746,0.0006181342,0.0059567397,0.017188441,0.029338779],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951446,0.00009771355,0.000037549045,0.00013298159,0.0001795276,0.000037729566],"domain_scores_gemma":[0.9993094,0.00032072267,0.000023988452,0.00014704115,0.0001310083,0.00006785267],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007966176,0.0012949186,0.0007481509,0.0008520916,0.0006895001,0.00173828,0.0036127383,0.0013326457,0.058898877],"category_scores_gemma":[0.0027680616,0.0009044076,0.0010879303,0.00055376714,0.000982703,0.0029493761,0.002989787,0.0017585016,0.019635474],"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":[0.0013452263,0.00039241934,0.0008574149,0.0013012015,0.0001458708,0.0007944791,0.0007133213,0.03359049,0.055494796,0.13898063,0.16210455,0.6042797],"study_design_scores_gemma":[0.0003301469,0.00014750937,0.00035728214,0.00009257304,0.000070768016,0.00075213966,0.00014036181,0.6722302,0.05898308,0.09507985,0.17169562,0.00012049461],"about_ca_topic_score_codex":0.0012734169,"about_ca_topic_score_gemma":0.001673025,"teacher_disagreement_score":0.058898877,"about_ca_system_score_codex":0.00052676216,"about_ca_system_score_gemma":0.00066420075,"threshold_uncertainty_score":0.19703639},"labels":[],"label_agreement":null},{"id":"W4414968374","doi":"10.48550/arxiv.2509.03378","title":"Understanding and Improving Shampoo and SOAP via Kullback-Leibler Minimization","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Speech and dialogue systems","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":"RIKEN; University of Central Florida; Government of Canada; Canadian Institute for Advanced Research","keywords":"Shampoo; Overhead (engineering); Minification; Divergence (linguistics); SOAP","score_opus":0.10539097088597542,"score_gpt":0.2626024331985078,"score_spread":0.15721146231253236,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4414968374","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.005615617,0.0005503077,0.98675716,0.00087898463,0.00014138415,0.00007798345,0.00010454903,0.0026109132,0.003263097],"genre_scores_gemma":[0.22371748,0.0009951144,0.7608334,0.001997967,0.0002903729,0.00051468867,0.0008716086,0.002468512,0.008310902],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9973532,0.00094713387,0.00017919,0.0004635763,0.00086590525,0.00019102436],"domain_scores_gemma":[0.99301165,0.003978083,0.00040104438,0.001253415,0.0010445444,0.00031121512],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0052432446,0.0023624788,0.0016536982,0.00085334445,0.0009586867,0.0021274034,0.0031542478,0.0030691526,0.006734775],"category_scores_gemma":[0.022639588,0.0010847166,0.0012644785,0.00064549514,0.0027652187,0.004485737,0.0051895776,0.005481307,0.0034191278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037216605,0.00022074315,0.0020575565,0.0006500606,0.00016369302,0.00024353465,0.00028895176,0.5710494,0.0074308,0.1087005,0.02487903,0.28394353],"study_design_scores_gemma":[0.000044180182,0.00008364151,0.00014667622,0.000051432,0.000013847898,0.000060032122,0.000029761477,0.9396254,0.0022379684,0.054214004,0.0034674583,0.000025679888],"about_ca_topic_score_codex":0.0037441093,"about_ca_topic_score_gemma":0.0053343503,"teacher_disagreement_score":0.006734775,"about_ca_system_score_codex":0.0011731851,"about_ca_system_score_gemma":0.0042351293,"threshold_uncertainty_score":0.027729273},"labels":[],"label_agreement":null},{"id":"W4415284365","doi":"10.36227/techrxiv.176072275.50751098/v1","title":"Unlocking Multimodal Models with Lightweight Fine-Tuning","year":2025,"lang":"","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Field (mathematics); Multimodality; Multimodal interaction; Foundation (evidence); Key (lock)","score_opus":0.017251184829137775,"score_gpt":0.23517576386846228,"score_spread":0.2179245790393245,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415284365","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.009215211,0.0007695591,0.9857218,0.00028561833,0.000042918506,0.000035300738,0.00010016686,0.0018347416,0.001994657],"genre_scores_gemma":[0.58763283,0.0022644904,0.39857087,0.0010664095,0.00023566249,0.00053336064,0.00089671765,0.001326841,0.007472761],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928576,0.00024897666,0.000039508508,0.00018911654,0.00014032374,0.00009635593],"domain_scores_gemma":[0.998505,0.0008199804,0.00009226473,0.00036054614,0.00015560523,0.00006662611],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015918616,0.0017416045,0.0012022434,0.00056621287,0.0005107041,0.0016086616,0.0026379244,0.0015952543,0.0041119247],"category_scores_gemma":[0.007566481,0.0009208776,0.0013946096,0.00064435706,0.0014120796,0.003787866,0.0035840517,0.0038711724,0.002000779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001510247,0.000100184785,0.0010877876,0.0003084732,0.00016443776,0.00013505554,0.00031683396,0.67643774,0.011095665,0.04008483,0.005294173,0.26482385],"study_design_scores_gemma":[0.000007784483,0.000023778572,0.00010312121,0.000021541911,0.000014835942,0.000024813087,0.000022084121,0.974442,0.0011261619,0.02305341,0.0011483137,0.000012057211],"about_ca_topic_score_codex":0.004569954,"about_ca_topic_score_gemma":0.00629785,"teacher_disagreement_score":0.004569954,"about_ca_system_score_codex":0.00091927464,"about_ca_system_score_gemma":0.0011676679,"threshold_uncertainty_score":0.013755739},"labels":[],"label_agreement":null},{"id":"W4415428234","doi":"10.3233/faia251306","title":"Assessing and Improving the Multilingual Visual Word Sense Disambiguation Ability of Vision-Language Models","year":2025,"lang":"en","type":"book-chapter","venue":"Frontiers in artificial intelligence and applications","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Generalization; Task (project management); Set (abstract data type); Generative grammar; Lemma (botany); Word (group theory); Word-sense disambiguation; Generative model","score_opus":0.03518871009626741,"score_gpt":0.32282001148551753,"score_spread":0.28763130138925014,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415428234","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":[0.5944492,0.006242536,0.36739713,0.0009267833,0.00040705205,0.0001719397,0.0012179293,0.01145427,0.017733209],"genre_scores_gemma":[0.85609967,0.0009524884,0.13572976,0.00021304302,0.000073625975,0.00007162993,0.0020260029,0.0004576359,0.0043762224],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991842,0.0002838863,0.00003885003,0.00029711108,0.00012899794,0.000066939974],"domain_scores_gemma":[0.9976725,0.0016159009,0.00008229356,0.00026447172,0.00026390253,0.00010097079],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020722216,0.0016187377,0.0007025925,0.0010409778,0.00033428433,0.0020866124,0.0011351607,0.0011259661,0.003965335],"category_scores_gemma":[0.006695508,0.0004006147,0.00061079254,0.0006475658,0.0004505878,0.0026515082,0.0021098533,0.0013914502,0.0022147368],"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":[0.0005742293,0.00046160488,0.007959006,0.00045840268,0.00041850342,0.00021201136,0.00043308432,0.121768296,0.034929156,0.005356404,0.009307667,0.81812155],"study_design_scores_gemma":[0.000043920703,0.00039508243,0.0028561724,0.00004475639,0.00013961125,0.00019570053,0.00030514703,0.9546966,0.030803712,0.0067334613,0.0037182919,0.0000674365],"about_ca_topic_score_codex":0.0046196496,"about_ca_topic_score_gemma":0.0061146216,"teacher_disagreement_score":0.0046196496,"about_ca_system_score_codex":0.00069051416,"about_ca_system_score_gemma":0.0007818085,"threshold_uncertainty_score":0.013265431},"labels":[],"label_agreement":null},{"id":"W4415605817","doi":"10.12732/ijam.v38i8s.630","title":"OMNICHANNEL CONVERSATIONAL SEARCH: MAINTAINING CONTEXT AND CONSISTENCY ACROSS VOICE AND WEB INTERFACES","year":2025,"lang":"","type":"article","venue":"International Journal of Apllied Mathematics","topic":"Speech and dialogue systems","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":"Arbutus Biopharma (Canada)","funders":"","keywords":"Omnichannel; Cloud computing; Transaction log; Context (archaeology); Latency (audio); Churning; Session (web analytics); Consistency (knowledge bases); Context switch","score_opus":0.033892223632261596,"score_gpt":0.3124353668380898,"score_spread":0.27854314320582824,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415605817","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.23507033,0.0013036551,0.7208857,0.00066867424,0.00012319785,0.0007328991,0.00080689293,0.022162728,0.018245982],"genre_scores_gemma":[0.7739333,0.00028463278,0.21528952,0.00039831694,0.000088669614,0.00033474813,0.0009174018,0.0010407305,0.007712784],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9981937,0.00045806944,0.00013196739,0.00038780202,0.0005572161,0.00027121138],"domain_scores_gemma":[0.99695694,0.0010007261,0.00021785987,0.0010413971,0.00047739738,0.00030573367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019641202,0.00074800587,0.00075103185,0.00083618076,0.0012651405,0.0025516513,0.0021099015,0.0008563542,0.002989534],"category_scores_gemma":[0.006242365,0.00042694836,0.00054046366,0.00065424095,0.00085806096,0.00465414,0.005021195,0.00096731866,0.0013782838],"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":[0.005456559,0.0009712745,0.01495426,0.0010706858,0.000262788,0.0015112285,0.008674598,0.01935814,0.21826997,0.04800148,0.017428786,0.6640402],"study_design_scores_gemma":[0.0005286561,0.0018222851,0.009818162,0.00022147618,0.00046734812,0.0023493466,0.0064393007,0.61729395,0.15174885,0.09335274,0.115412295,0.0005455634],"about_ca_topic_score_codex":0.0046111452,"about_ca_topic_score_gemma":0.004838528,"teacher_disagreement_score":0.0046111452,"about_ca_system_score_codex":0.00051522715,"about_ca_system_score_gemma":0.0017248703,"threshold_uncertainty_score":0.010387421},"labels":[],"label_agreement":null},{"id":"W4416030402","doi":"10.48550/arxiv.2507.14063","title":"Collaborative Rational Speech Act: Pragmatic Reasoning for Multi-Turn Dialog","year":2025,"lang":"en","type":"preprint","venue":"ArXiv.org","topic":"Speech and dialogue systems","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":"Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Dialog box; Conversation; Speech act; Extension (predicate logic); Function (biology); Dialog system; Face (sociological concept)","score_opus":0.04170258767895742,"score_gpt":0.3110798380555782,"score_spread":0.2693772503766208,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4416030402","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0071093757,0.00023701818,0.98607534,0.00086339173,0.000058895217,0.000099263256,0.0000807217,0.00037032503,0.0051055946],"genre_scores_gemma":[0.56864434,0.00044875077,0.42528313,0.00039719182,0.00018767577,0.00040300022,0.00032833562,0.0002311658,0.0040764413],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9905151,0.005968299,0.0004381754,0.0012673858,0.0015027466,0.00030825962],"domain_scores_gemma":[0.98671836,0.009102679,0.0010261263,0.0018224639,0.000817153,0.0005131728],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009031197,0.0013918444,0.00089403236,0.0011001005,0.0013282893,0.004169203,0.0024485444,0.0026272007,0.004745015],"category_scores_gemma":[0.024810096,0.0008952022,0.0019827585,0.00064835657,0.0047434685,0.006431511,0.004802507,0.0036639313,0.0010377122],"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":[0.00027176194,0.00014603941,0.0013503612,0.00038284008,0.00018009296,0.000404044,0.002359622,0.1991647,0.005610623,0.711084,0.0037383894,0.07530751],"study_design_scores_gemma":[0.00003952278,0.00006077763,0.00021048896,0.00004748952,0.00004136563,0.00012472317,0.00015869702,0.6241024,0.0019923553,0.36765778,0.0055194465,0.000044885575],"about_ca_topic_score_codex":0.003840799,"about_ca_topic_score_gemma":0.0032053706,"teacher_disagreement_score":0.009031197,"about_ca_system_score_codex":0.002207958,"about_ca_system_score_gemma":0.0025754757,"threshold_uncertainty_score":0.047762096},"labels":[],"label_agreement":null},{"id":"W4417174389","doi":"10.36939/ir.202512091609","title":"Data-Driven Methodologies for Intelligent Systems","year":2025,"lang":"en","type":"dissertation","venue":"","topic":"Speech and dialogue systems","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 Winnipeg; Canadian Society for Immunology","funders":"","keywords":"Interpretability; Intelligent decision support system; Feature (linguistics); Modular design; Verifiable secret sharing; Chatbot; Model-based reasoning; Schema (genetic algorithms)","score_opus":0.22337481366617803,"score_gpt":0.401356381296836,"score_spread":0.17798156763065795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417174389","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":[0.0011660181,0.0038395352,0.9789868,0.002850818,0.0002527445,0.0001932769,0.00023110167,0.00045637717,0.012023398],"genre_scores_gemma":[0.073619284,0.005534436,0.9109302,0.00097596407,0.0004871946,0.0010504281,0.0006777984,0.0002932867,0.0064314227],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99431664,0.002678494,0.00059382606,0.0008229537,0.0013830881,0.00020508522],"domain_scores_gemma":[0.9886368,0.007794193,0.00032787374,0.0021140804,0.00094242755,0.00018459298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008315814,0.001669975,0.0012013059,0.002759573,0.0011837453,0.008052711,0.0036293608,0.0024811681,0.0056084725],"category_scores_gemma":[0.014248154,0.0010140346,0.002098747,0.0025114515,0.0063335593,0.0075202947,0.004433801,0.0047868756,0.0019689915],"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":[0.00001528958,0.00002863752,0.00018731496,0.00036201064,0.000052270436,0.00007732345,0.00029887861,0.014023979,0.00035642946,0.9551898,0.0021652903,0.027242778],"study_design_scores_gemma":[0.000017578173,0.00001717448,0.00005303008,0.00015400766,0.000021042411,0.000050530813,0.00012147368,0.04427405,0.00068470143,0.8984971,0.05609206,0.000017208795],"about_ca_topic_score_codex":0.003015567,"about_ca_topic_score_gemma":0.0020248091,"teacher_disagreement_score":0.008315814,"about_ca_system_score_codex":0.003622959,"about_ca_system_score_gemma":0.003464498,"threshold_uncertainty_score":0.04397875},"labels":[],"label_agreement":null},{"id":"W583694926","doi":"","title":"Implicitly influencing the interactive experience","year":2010,"lang":"en","type":"article","venue":"Research Repository UCD (University College Dublin)","topic":"Speech and dialogue systems","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":"Science Foundation Ireland","keywords":"Ninth; Computer science; Human–computer interaction; Autonomous agent; Multimedia; Knowledge management; Artificial intelligence","score_opus":0.028871073982542798,"score_gpt":0.2946771431916692,"score_spread":0.2658060692091264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W583694926","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":[0.4648575,0.0013079896,0.13245812,0.0046192394,0.0005848224,0.00015653532,0.00026336167,0.0007540723,0.39499846],"genre_scores_gemma":[0.98695207,0.00015616017,0.005319248,0.00017138562,0.00005035514,0.000060955525,0.00009208918,0.00019986776,0.006997823],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99454015,0.0029409258,0.000161618,0.00082881923,0.00095315167,0.000575252],"domain_scores_gemma":[0.9914826,0.004891256,0.00079852954,0.0010151404,0.0008730602,0.0009394515],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00207764,0.0006912572,0.00037496877,0.00062594324,0.0019833257,0.00833387,0.00096281775,0.002058727,0.016300384],"category_scores_gemma":[0.022949353,0.000559784,0.0004927894,0.00050782145,0.003500949,0.0067196595,0.006384856,0.0028379087,0.001373537],"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":[0.0016537961,0.0005155375,0.027907517,0.001161759,0.00024961037,0.0017625877,0.30368406,0.008987821,0.093177445,0.40747356,0.009553427,0.14387287],"study_design_scores_gemma":[0.00041755897,0.0012391601,0.06246567,0.00087832543,0.0010292022,0.0019801287,0.10280475,0.059391398,0.034226492,0.39548934,0.3395759,0.00050211867],"about_ca_topic_score_codex":0.0029711823,"about_ca_topic_score_gemma":0.0026048943,"teacher_disagreement_score":0.016300384,"about_ca_system_score_codex":0.0012123551,"about_ca_system_score_gemma":0.0009583648,"threshold_uncertainty_score":0.054530203},"labels":[],"label_agreement":null},{"id":"W586724576","doi":"10.1007/s10772-015-9280-x","title":"Mobile spoken dialogue system using parser dependencies and ontology","year":2015,"lang":"en","type":"article","venue":"International Journal of Speech Technology","topic":"Speech and dialogue systems","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 de Moncton; Université du Québec à Montréal","funders":"","keywords":"Computer science; Parsing; Sentence; Natural language processing; Mobile phone; Android (operating system); Artificial intelligence; Spoken language; Dependency (UML)","score_opus":0.029085445274014795,"score_gpt":0.27848607373452006,"score_spread":0.24940062846050526,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W586724576","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":[0.05472217,0.0005237845,0.83886296,0.00022356345,0.00022428847,0.00025082033,0.0038007288,0.096250996,0.0051406673],"genre_scores_gemma":[0.46602184,0.00029184498,0.51105803,0.0002465284,0.000076223194,0.00035085497,0.009092656,0.0031204112,0.009741642],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9996152,0.00006440964,0.00004504243,0.0001557567,0.00008742544,0.000032095926],"domain_scores_gemma":[0.99940026,0.00024572265,0.00003113282,0.00009043908,0.00019273256,0.000039759678],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00067521736,0.0006262372,0.0010821817,0.0008057024,0.0006020935,0.0012238008,0.0008366346,0.00064823765,0.0063862563],"category_scores_gemma":[0.0014304523,0.0005314261,0.0006419081,0.00048317295,0.00020385647,0.001979273,0.0011089399,0.0007802065,0.0029380904],"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":[0.0017903633,0.00044878438,0.0037823024,0.0009250576,0.00031134067,0.0013792121,0.0016885346,0.011496286,0.19670264,0.0151028745,0.03916004,0.7272126],"study_design_scores_gemma":[0.00041837193,0.00045978863,0.004875418,0.00014929152,0.00073641783,0.0014508168,0.0009880105,0.69640946,0.17697512,0.017874312,0.099351965,0.0003110749],"about_ca_topic_score_codex":0.004807733,"about_ca_topic_score_gemma":0.0047370885,"teacher_disagreement_score":0.0063862563,"about_ca_system_score_codex":0.00038665844,"about_ca_system_score_gemma":0.0013567739,"threshold_uncertainty_score":0.021364152},"labels":[],"label_agreement":null},{"id":"W619597047","doi":"10.1016/j.cognition.2015.05.001","title":"Privileged versus shared knowledge about object identity in real-time referential processing","year":2015,"lang":"en","type":"article","venue":"Cognition","topic":"Speech and dialogue systems","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 Toronto","funders":"Social Sciences and Humanities Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Referent; Psychology; Object (grammar); Identity (music); Perspective (graphical); Conversation; Cognitive psychology; Linguistics; Expression (computer science); Communication; Social psychology; Computer science; Artificial intelligence","score_opus":0.07021357740682718,"score_gpt":0.3250744623676971,"score_spread":0.2548608849608699,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W619597047","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":[0.9245051,0.0005447512,0.0609025,0.0002591303,0.000025505313,0.000029591845,0.000025373552,0.00009962344,0.013608492],"genre_scores_gemma":[0.9943363,0.00010796382,0.005001892,0.000020928224,0.000011138504,0.000014379601,0.000020032146,0.000024573033,0.00046281624],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99429613,0.002008741,0.00028660407,0.0012073043,0.0017117559,0.0004894586],"domain_scores_gemma":[0.98825747,0.0058053974,0.0019187067,0.00262018,0.0008530989,0.0005451672],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0055087125,0.00042747208,0.00054852106,0.0012999597,0.0010162982,0.0060936185,0.0009834114,0.0014328362,0.0021497018],"category_scores_gemma":[0.023649067,0.0007394126,0.00068006257,0.00069696887,0.004428008,0.009746937,0.005120514,0.0016023017,0.00027485925],"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":[0.0019142097,0.00019339102,0.038719457,0.00068164716,0.00024232228,0.0019958308,0.28508094,0.0030548945,0.3818482,0.09634547,0.000274906,0.18964875],"study_design_scores_gemma":[0.00019029247,0.0021016432,0.376207,0.00070899114,0.0009064184,0.0058447667,0.12998395,0.0435868,0.13439064,0.28803906,0.01737085,0.0006696314],"about_ca_topic_score_codex":0.0013440204,"about_ca_topic_score_gemma":0.0010899184,"teacher_disagreement_score":0.0060936185,"about_ca_system_score_codex":0.00079310196,"about_ca_system_score_gemma":0.00083927275,"threshold_uncertainty_score":0.029133141},"labels":[],"label_agreement":null},{"id":"W67986949","doi":"10.21437/icslp.2000-410","title":"A robust speech understanding system using conceptual relational grammar","year":2000,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Grammar; Natural language processing; Artificial intelligence; Linguistics","score_opus":0.15159685323898972,"score_gpt":0.24268960155563907,"score_spread":0.09109274831664935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W67986949","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":[0.0374645,0.00018273466,0.9188679,0.00025921623,0.00007417573,0.00027562075,0.00079070247,0.037781227,0.0043038013],"genre_scores_gemma":[0.24956945,0.00013933849,0.740214,0.00032639466,0.00006591489,0.00043698974,0.0026419354,0.00094330916,0.005662763],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988263,0.00019382869,0.00009283077,0.00051272335,0.00031410024,0.00006013438],"domain_scores_gemma":[0.99905616,0.0003100927,0.00006969481,0.00029084156,0.00020771558,0.000065558066],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013367642,0.0004946075,0.0008502991,0.00047934684,0.00042106843,0.0014379703,0.0015004455,0.0012695997,0.006535648],"category_scores_gemma":[0.0028353648,0.00043019897,0.0004797516,0.00028372317,0.0006472375,0.0027553022,0.0012647706,0.0009980049,0.0049117664],"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":[0.00047479724,0.000358015,0.0014509645,0.00036603562,0.000102838705,0.0005576676,0.00097009586,0.013644106,0.53532195,0.028002134,0.01387132,0.40488002],"study_design_scores_gemma":[0.0003333361,0.0013270992,0.0042913584,0.00006273147,0.0003106335,0.0021499437,0.00036306345,0.52172244,0.36314175,0.020473257,0.08551664,0.00030776262],"about_ca_topic_score_codex":0.0014749195,"about_ca_topic_score_gemma":0.0008180891,"teacher_disagreement_score":0.006535648,"about_ca_system_score_codex":0.00045830503,"about_ca_system_score_gemma":0.00087744195,"threshold_uncertainty_score":0.021863937},"labels":[],"label_agreement":null},{"id":"W6911804847","doi":"10.5281/zenodo.14887640","title":"S'initier aux bonnes pratiques d'utilisation des agents conversationnels (Copilot et ChatGPT)","year":2025,"lang":"fr","type":"article","venue":"Open MIND","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Identification (biology); Community participation; Identifier; Control (management)","score_opus":0.14602078743657576,"score_gpt":0.37281949052446456,"score_spread":0.2267987030878888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6911804847","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":[0.06146045,0.00041011814,0.864248,0.0032567151,0.0010600883,0.0013589092,0.00039855883,0.019613089,0.04819397],"genre_scores_gemma":[0.31186035,0.0004661363,0.5641937,0.0013028708,0.00041274037,0.0018676267,0.00062432943,0.0032035261,0.11606868],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99648607,0.0016352189,0.00015427782,0.00058774307,0.00086819066,0.00026844812],"domain_scores_gemma":[0.99293983,0.0037442895,0.000315179,0.0009943625,0.0015408613,0.00046539234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00481432,0.001311884,0.0008076937,0.000585797,0.0015541746,0.0048460006,0.0016099832,0.0033346922,0.037567873],"category_scores_gemma":[0.012999556,0.00084229436,0.00072284846,0.0003894776,0.0018005976,0.0051051653,0.0033133784,0.004625426,0.01625464],"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":[0.0034439666,0.0008164274,0.003338771,0.0021253345,0.00011185946,0.0025486157,0.044564545,0.005350566,0.3045245,0.11413167,0.037765104,0.48127878],"study_design_scores_gemma":[0.00056486175,0.001569713,0.0050770314,0.000787032,0.00018716126,0.0026706725,0.010255582,0.0938371,0.24219462,0.026933974,0.61545265,0.00046965946],"about_ca_topic_score_codex":0.003191019,"about_ca_topic_score_gemma":0.003255747,"teacher_disagreement_score":0.037567873,"about_ca_system_score_codex":0.00092673575,"about_ca_system_score_gemma":0.0021915117,"threshold_uncertainty_score":0.12567711},"labels":[],"label_agreement":null},{"id":"W6912402350","doi":"10.5281/zenodo.3724618","title":"Boards for Automated Referential Communication Task","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Speech and dialogue systems","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":"Task (project management); Task analysis; Order (exchange); Models of communication","score_opus":0.026953706528561022,"score_gpt":0.24941038060940687,"score_spread":0.22245667408084585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6912402350","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":[0.6133369,0.00082431705,0.20241718,0.0018653085,0.0041050804,0.032143172,0.007867166,0.012220792,0.12522002],"genre_scores_gemma":[0.53868437,0.0005163619,0.2587535,0.0030320864,0.00075251627,0.105414964,0.009180192,0.0044541103,0.07921202],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974462,0.00054418127,0.00024978194,0.00077287643,0.0006952158,0.00029173266],"domain_scores_gemma":[0.99409086,0.00299774,0.00051463593,0.0010983367,0.0007357117,0.0005627531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00247616,0.0021178317,0.0013556974,0.000541527,0.001105117,0.0017251413,0.0018734317,0.002271869,0.060708083],"category_scores_gemma":[0.015041767,0.0008809302,0.0005638806,0.00036818717,0.0008760134,0.0036658677,0.0038947838,0.0029057774,0.016857712],"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":[0.019559538,0.018048285,0.0070895036,0.0037271816,0.00015535367,0.0014234149,0.0144637935,0.0061571533,0.40147218,0.04814733,0.11928811,0.36046815],"study_design_scores_gemma":[0.017609963,0.024336398,0.09322242,0.0011656381,0.000450619,0.0023851756,0.004484036,0.061715048,0.10051877,0.09921899,0.5937894,0.0011035741],"about_ca_topic_score_codex":0.0005663281,"about_ca_topic_score_gemma":0.0006960204,"teacher_disagreement_score":0.060708083,"about_ca_system_score_codex":0.0004993682,"about_ca_system_score_gemma":0.0009966185,"threshold_uncertainty_score":0.20308876},"labels":[],"label_agreement":null},{"id":"W6925108376","doi":"10.17176/20181005-173239-0","title":"The Constitutional Inheritance of the Royal Baby: A Speculation","year":2013,"lang":"en","type":"article","venue":"intR2Dok (Staatsbibliothek zu Berlin)","topic":"Speech and dialogue systems","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":"Surprise; State (computer science); Inheritance (genetic algorithm); Speculation; Certainty; Queen (butterfly); Prime minister; Arrow; Parliament","score_opus":0.010052144407753382,"score_gpt":0.2173692601950162,"score_spread":0.20731711578726283,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6925108376","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":[0.035725977,0.0092260195,0.0038399885,0.41489622,0.0021578565,0.00003683514,0.00029022596,0.000053717416,0.53377324],"genre_scores_gemma":[0.86596346,0.004995115,0.0012779294,0.064577945,0.0045964876,0.000056770135,0.000109430235,0.0000802999,0.058342587],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99588996,0.0014492397,0.00009335438,0.0009217518,0.00071411027,0.00093167834],"domain_scores_gemma":[0.99521506,0.0028339382,0.00033916536,0.00057581865,0.00059796206,0.00043801274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063884417,0.00030284462,0.0004927675,0.0008165035,0.0053761187,0.007506495,0.0019544351,0.008488802,0.02999902],"category_scores_gemma":[0.014793696,0.0004075389,0.0006764057,0.0010921677,0.033017736,0.016783647,0.0038582308,0.008570708,0.0028206205],"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":[0.0000057807138,0.000005483377,0.00007855261,0.000010121077,0.0000015064339,0.000053253643,0.0007473637,0.000023466746,0.000025620724,0.9916488,0.0063956995,0.0010044714],"study_design_scores_gemma":[0.000029917303,0.000021218997,0.0007916958,0.00022032064,0.000011892158,0.00019438166,0.003146088,0.0001997926,0.00014557723,0.83730274,0.1579106,0.000025712085],"about_ca_topic_score_codex":0.02366831,"about_ca_topic_score_gemma":0.014553861,"teacher_disagreement_score":0.02999902,"about_ca_system_score_codex":0.009404567,"about_ca_system_score_gemma":0.0050686286,"threshold_uncertainty_score":0.1003567},"labels":[],"label_agreement":null},{"id":"W6939592456","doi":"10.6084/m9.figshare.19297790","title":"Additional file 2 of Perceptions of physical activity and sedentary behaviour guidelines among end-users and stakeholders: a systematic review","year":2022,"lang":"en","type":"article","venue":"Figshare","topic":"Speech and dialogue systems","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":"Physical activity; Perception; Table (database); Data collection; Sedentary lifestyle","score_opus":0.08751686055230738,"score_gpt":0.2909812317145068,"score_spread":0.2034643711621994,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6939592456","genre_codex":"dataset","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":[0.00038363074,0.0004092258,0.0004600764,0.00040264454,0.00006674753,0.0028746403,0.9941705,0.00014885387,0.0010836918],"genre_scores_gemma":[0.022889212,0.003981395,0.024708813,0.0039133755,0.00035040986,0.2474739,0.6662962,0.000798501,0.029588273],"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","domain_scores_codex":[0.9961392,0.00075972977,0.0016514951,0.0005170916,0.00064359774,0.00028889903],"domain_scores_gemma":[0.89954764,0.080149196,0.007850438,0.001772164,0.009890537,0.00079005683],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008313529,0.0017219966,0.003530395,0.009416921,0.0011534562,0.0025358372,0.0021423479,0.001897851,0.79312676],"category_scores_gemma":[0.10210705,0.0012049903,0.0032852008,0.013438966,0.0005623973,0.0044388026,0.0019734267,0.0012157311,0.038891785],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010033955,0.00008615185,0.001928446,0.5103657,0.0006842182,0.00016313176,0.00057047175,0.0004770467,0.00021759719,0.0020860354,0.4612683,0.0211495],"study_design_scores_gemma":[0.022030095,0.0008303973,0.042925905,0.32795334,0.0065223277,0.00087775,0.0026837192,0.0018053312,0.001104652,0.015972653,0.5768054,0.0004884536],"about_ca_topic_score_codex":0.009853824,"about_ca_topic_score_gemma":0.02291254,"teacher_disagreement_score":0.79312676,"about_ca_system_score_codex":0.0036460615,"about_ca_system_score_gemma":0.010015409,"threshold_uncertainty_score":0.29507953},"labels":[],"label_agreement":null},{"id":"W6958587819","doi":"10.6084/m9.figshare.25376111","title":"Additional file 1 of FLI1 induces erythroleukemia through opposing effects on UBASH3A and UBASH3B expression","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Speech and dialogue systems","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 Health Network","funders":"","keywords":"Expression (computer science); Cell culture; Gene expression; Embryonic stem cell; DNA; Fusion protein","score_opus":0.02289852905274074,"score_gpt":0.23978820908480347,"score_spread":0.21688968003206274,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6958587819","genre_codex":"dataset","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":[0.00029645895,0.000038736565,0.001076536,0.00009201518,0.00008017942,0.000090897905,0.9952005,0.0013755569,0.0017490855],"genre_scores_gemma":[0.008233953,0.0002146672,0.0075956085,0.0004790442,0.00009069086,0.001631487,0.9659575,0.0033831126,0.0124139665],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9992725,0.000090774345,0.00008111702,0.00020522517,0.00021464055,0.0001356546],"domain_scores_gemma":[0.99105597,0.0066578235,0.00030918626,0.0007027058,0.0008137502,0.0004604883],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0012246112,0.0015779119,0.0019218965,0.0021351725,0.0015383644,0.0018888958,0.0025323876,0.0017354393,0.9093568],"category_scores_gemma":[0.011192777,0.0012645718,0.0012573901,0.002829459,0.00039338256,0.0018425199,0.0011375633,0.001721291,0.29146025],"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":[0.0006960317,0.00024969404,0.001491674,0.0031898506,0.00006466353,0.00017370933,0.000105814775,0.00065390125,0.0028014807,0.0014966663,0.9748004,0.014276041],"study_design_scores_gemma":[0.0052535,0.00077205285,0.028041054,0.002445294,0.00024391258,0.0012435502,0.00043298717,0.0037758485,0.013207668,0.01541552,0.92881143,0.000357146],"about_ca_topic_score_codex":0.0049237134,"about_ca_topic_score_gemma":0.008663875,"teacher_disagreement_score":0.9093568,"about_ca_system_score_codex":0.0010914505,"about_ca_system_score_gemma":0.0015748515,"threshold_uncertainty_score":0.1292916},"labels":[],"label_agreement":null},{"id":"W6959013929","doi":"10.6084/m9.figshare.c.4369562","title":"Cerebral mechanism of celecoxib for treating knee pain: study protocol for a randomized controlled parallel trial","year":2019,"lang":"en","type":"other","venue":"Figshare","topic":"Speech and dialogue systems","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":"Celecoxib; Placebo; Osteoarthritis; Visual analogue scale; Clinical trial; Clinical endpoint; Randomized controlled trial","score_opus":0.04258755243709869,"score_gpt":0.3054992605878388,"score_spread":0.26291170815074005,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6959013929","genre_codex":"protocol","genre_gemma":"protocol","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"protocol","genre_consensus":"protocol","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.003131285,0.0005854258,0.0014743144,0.00022047653,0.00052208593,0.99193746,0.0011395569,0.00010173845,0.00088762614],"genre_scores_gemma":[0.0032875612,0.00027675368,0.0016686723,0.0002161789,0.0001088981,0.99363387,0.00024611977,0.000008025274,0.0005539584],"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","domain_scores_codex":[0.9883681,0.0063814195,0.0013011107,0.0012613179,0.0013568393,0.0013312399],"domain_scores_gemma":[0.99216014,0.0016417372,0.0016802908,0.0010942899,0.001938734,0.0014847773],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.021117384,0.006572719,0.012627964,0.0020925177,0.0030957637,0.003241428,0.0031384274,0.0052593704,0.074199356],"category_scores_gemma":[0.019132903,0.0025562309,0.00512169,0.0031237125,0.0032315135,0.0030178013,0.0017965552,0.0060575535,0.012843243],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.9525015,0.009318024,0.0005164483,0.010589376,0.0018073187,0.00013021185,0.00012363744,0.00080597255,0.0013604913,0.0015325648,0.0068241656,0.014490306],"study_design_scores_gemma":[0.97123116,0.016198805,0.00093248626,0.0008593075,0.00074392615,0.000026918151,0.000031622225,0.000657352,0.00018171442,0.0009442851,0.008156515,0.00003594405],"about_ca_topic_score_codex":0.0015087044,"about_ca_topic_score_gemma":0.0038218305,"teacher_disagreement_score":0.074199356,"about_ca_system_score_codex":0.0032319592,"about_ca_system_score_gemma":0.011213151,"threshold_uncertainty_score":0.24822158},"labels":[],"label_agreement":null},{"id":"W6968249812","doi":"10.5281/zenodo.14887641","title":"S'initier aux bonnes pratiques d'utilisation des agents conversationnels (Copilot et ChatGPT)","year":2025,"lang":"fr","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Speech and dialogue systems","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 Laval","funders":"","keywords":"Identification (biology); Community participation; Identifier; Control (management)","score_opus":0.09572151653909712,"score_gpt":0.3033767773456696,"score_spread":0.20765526080657248,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6968249812","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":[0.03083326,0.00037386478,0.9048194,0.0021658249,0.0010132833,0.0010293974,0.00043821998,0.027889602,0.031437192],"genre_scores_gemma":[0.24506138,0.0005384819,0.6080285,0.0013288042,0.0005666515,0.00182203,0.00094138976,0.0062396703,0.13547307],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9966605,0.0014362307,0.00015622171,0.00060362933,0.0008596228,0.00028390368],"domain_scores_gemma":[0.99446,0.0027823448,0.00023075953,0.0009747784,0.0011911886,0.00036092213],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0044679753,0.0016338145,0.0010301865,0.0005741992,0.0013788469,0.0047545815,0.0017738896,0.0035018274,0.045749225],"category_scores_gemma":[0.010241784,0.00092960324,0.00080185133,0.00034911177,0.0015860663,0.0046174643,0.0031941193,0.004505278,0.022330672],"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":[0.004938661,0.00069168647,0.002584964,0.002072679,0.00014445069,0.0028719276,0.021499217,0.0068420297,0.3305042,0.104679905,0.058194567,0.46497574],"study_design_scores_gemma":[0.00056364905,0.0010160289,0.002857903,0.0005553671,0.0001641316,0.0022539867,0.0038750244,0.10802982,0.24711505,0.020492624,0.61270946,0.00036697128],"about_ca_topic_score_codex":0.0029343576,"about_ca_topic_score_gemma":0.002804592,"teacher_disagreement_score":0.045749225,"about_ca_system_score_codex":0.00083568325,"about_ca_system_score_gemma":0.001724345,"threshold_uncertainty_score":0.15304637},"labels":[],"label_agreement":null},{"id":"W6968657375","doi":"10.5281/zenodo.3724619","title":"Boards for Automated Referential Communication Task","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Speech and dialogue systems","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":"Task (project management); Task analysis; Order (exchange); Models of communication","score_opus":0.026953706528561022,"score_gpt":0.24941038060940687,"score_spread":0.22245667408084585,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6968657375","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":[0.6133369,0.00082431705,0.20241718,0.0018653085,0.0041050804,0.032143172,0.007867166,0.012220792,0.12522002],"genre_scores_gemma":[0.53868437,0.0005163619,0.2587535,0.0030320864,0.00075251627,0.105414964,0.009180192,0.0044541103,0.07921202],"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","domain_scores_codex":[0.9974462,0.00054418127,0.00024978194,0.00077287643,0.0006952158,0.00029173266],"domain_scores_gemma":[0.99409086,0.00299774,0.00051463593,0.0010983367,0.0007357117,0.0005627531],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00247616,0.0021178317,0.0013556974,0.000541527,0.001105117,0.0017251413,0.0018734317,0.002271869,0.060708083],"category_scores_gemma":[0.015041767,0.0008809302,0.0005638806,0.00036818717,0.0008760134,0.0036658677,0.0038947838,0.0029057774,0.016857712],"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":[0.019559538,0.018048285,0.0070895036,0.0037271816,0.00015535367,0.0014234149,0.0144637935,0.0061571533,0.40147218,0.04814733,0.11928811,0.36046815],"study_design_scores_gemma":[0.017609963,0.024336398,0.09322242,0.0011656381,0.000450619,0.0023851756,0.004484036,0.061715048,0.10051877,0.09921899,0.5937894,0.0011035741],"about_ca_topic_score_codex":0.0005663281,"about_ca_topic_score_gemma":0.0006960204,"teacher_disagreement_score":0.060708083,"about_ca_system_score_codex":0.0004993682,"about_ca_system_score_gemma":0.0009966185,"threshold_uncertainty_score":0.20308876},"labels":[],"label_agreement":null},{"id":"W6976777988","doi":"10.6068/dp14ba826dc4235","title":"Trend 1999 - 2002. Statistics Canada. CANSIM: Business Performance and Ownership - Corporate Taxation | Country: Canada | Table: Financial and taxation statistics for enterprises, by North American Industry Classification System (NAICS) | Variable: Return on capital employed, General merchandise stores | Units: , 1999-2002. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-020.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Speech and dialogue systems","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":"Taxable income; Economic statistics; Official statistics; Census; Business statistics; Summary statistics; Descriptive statistics; Government (linguistics); Personal income; Per capita","score_opus":0.030630654390494973,"score_gpt":0.22468883527131,"score_spread":0.19405818088081503,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976777988","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":[0.0000616319,0.000053398733,0.0000277815,0.00014728545,0.000029449337,0.000015615951,0.9984365,0.000066084685,0.0011621773],"genre_scores_gemma":[0.00095992384,0.0003005522,0.0004209257,0.0001525318,0.000020322954,0.000114861105,0.99210536,0.00012662719,0.0057988646],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99473464,0.0003115257,0.00050809723,0.00058259524,0.0026733344,0.0011898777],"domain_scores_gemma":[0.9540124,0.0014028682,0.0013907382,0.0011782247,0.04014372,0.0018720588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022223948,0.0024186003,0.002593202,0.010460829,0.0033206376,0.005660437,0.004962996,0.0014903758,0.08003051],"category_scores_gemma":[0.01924814,0.0018247153,0.0019537366,0.04531164,0.00063297484,0.0028082298,0.0023526005,0.0031901395,0.053708423],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022434606,0.0000068524014,0.0010371323,0.0001856606,0.000018213881,0.0000073052865,0.000019185512,0.000114677736,0.000008267465,0.00044143116,0.9964945,0.0016442353],"study_design_scores_gemma":[0.00012229157,0.000011125437,0.024956763,0.00075545255,0.000059415197,0.000026401438,0.0004485322,0.00055324304,0.00019859271,0.00069263,0.97208935,0.00008623804],"about_ca_topic_score_codex":0.9948724,"about_ca_topic_score_gemma":0.99267596,"teacher_disagreement_score":0.08003051,"about_ca_system_score_codex":0.06446323,"about_ca_system_score_gemma":0.15280455,"threshold_uncertainty_score":0.46771562},"labels":[],"label_agreement":null},{"id":"W6976832036","doi":"10.6084/m9.figshare.25749012","title":"Universal Rapid Weather Prediction Model (Sonagi Model) Forecast Current Result","year":2024,"lang":"en","type":"dataset","venue":"Figshare","topic":"Speech and dialogue systems","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":"National weather service; Weather forecasting; Current (fluid); Weather prediction; Numerical weather prediction; Tropical cyclone forecast model; Global Forecast System","score_opus":0.05313725307862524,"score_gpt":0.26255663862356277,"score_spread":0.20941938554493753,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6976832036","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":[0.0015707971,0.0001341768,0.000557515,0.00013535185,0.00011165862,0.000034267734,0.9930226,0.0028625198,0.0015710752],"genre_scores_gemma":[0.0025392957,0.000049742157,0.0009149934,0.000030962343,0.000013519405,0.00006134369,0.99535817,0.00009890663,0.0009330262],"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99938107,0.000100230536,0.00006690268,0.00022889803,0.0001395654,0.00008327935],"domain_scores_gemma":[0.99899346,0.00019964561,0.000057402598,0.00032840116,0.00034813667,0.00007299247],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00074149313,0.0022921667,0.00095167616,0.0016453172,0.0005464572,0.0011407438,0.0020274394,0.0017409963,0.023225596],"category_scores_gemma":[0.003325423,0.00044237595,0.0014901721,0.0015714458,0.00027535183,0.0013419847,0.0010667758,0.0015501863,0.061643433],"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":[0.00011527962,0.00004899403,0.0026740253,0.0003617604,0.000040598457,0.000031265103,0.000019994897,0.0021368084,0.00025650626,0.0002556532,0.9870712,0.0069878264],"study_design_scores_gemma":[0.0005385574,0.0001456772,0.020568913,0.00038318915,0.00013134081,0.00023271672,0.00022630552,0.03655743,0.0031817644,0.0027267956,0.93516964,0.00013775063],"about_ca_topic_score_codex":0.032592684,"about_ca_topic_score_gemma":0.06059362,"teacher_disagreement_score":0.032592684,"about_ca_system_score_codex":0.0010224842,"about_ca_system_score_gemma":0.0011545654,"threshold_uncertainty_score":0.0776974},"labels":[],"label_agreement":null},{"id":"W6987961142","doi":"","title":"Voice Code: An Innovative Speech Interface for Programming-by-Voice","year":2006,"lang":"en","type":"article","venue":"NPARC","topic":"Speech and dialogue systems","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":"Usability; Interface (matter); Syntax; User interface; Code (set theory); Program code; Component (thermodynamics)","score_opus":0.01922772739176576,"score_gpt":0.278869509080042,"score_spread":0.25964178168827623,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6987961142","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":[0.005389857,0.0003207273,0.9318792,0.00030936458,0.00039927952,0.00026450935,0.0003386953,0.05024523,0.010853222],"genre_scores_gemma":[0.14930592,0.0009437163,0.7806591,0.0018628443,0.0008014824,0.0014733557,0.0023140078,0.017949224,0.044690404],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9986583,0.0004029631,0.00008298248,0.00020060869,0.0005616073,0.00009360718],"domain_scores_gemma":[0.99715376,0.0016728549,0.000118618016,0.00030501085,0.00050214084,0.00024759184],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015418468,0.0011067721,0.0006130049,0.00071657,0.00052906654,0.002145006,0.0017951183,0.0015489829,0.023481313],"category_scores_gemma":[0.006822669,0.0004060266,0.0004527377,0.00037233316,0.00096434035,0.0028483395,0.0028768773,0.0014734622,0.008413046],"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":[0.001759089,0.0002555156,0.0012731234,0.0010939047,0.00009991067,0.0009481857,0.0039005103,0.0027648422,0.12866193,0.05610279,0.10436608,0.6987741],"study_design_scores_gemma":[0.00039173788,0.00081350625,0.0015110901,0.00034364942,0.00015505336,0.003560749,0.00070102303,0.10580694,0.11230236,0.03780602,0.7362652,0.000342641],"about_ca_topic_score_codex":0.0006490289,"about_ca_topic_score_gemma":0.00064980844,"teacher_disagreement_score":0.023481313,"about_ca_system_score_codex":0.0002706169,"about_ca_system_score_gemma":0.0006019283,"threshold_uncertainty_score":0.07855278},"labels":[],"label_agreement":null},{"id":"W6995855998","doi":"","title":"Proceedings of the 6. International Workshop on the Language-Action Perspective on Communication Modelling : (LAP 2001), July 2001, Montreal, Canada","year":2001,"lang":"en","type":"article","venue":"RWTH Publications (RWTH Aachen)","topic":"Speech and dialogue systems","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":"Perspective (graphical); Work (physics); Key (lock)","score_opus":0.04902381211746662,"score_gpt":0.27383134476343235,"score_spread":0.22480753264596573,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W6995855998","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":[0.017538248,0.035111245,0.73736686,0.026849525,0.013029143,0.0007262856,0.0037934275,0.0052555194,0.16032982],"genre_scores_gemma":[0.12539878,0.03271229,0.24248254,0.0029717928,0.0030706543,0.0008344659,0.014140969,0.004397532,0.573991],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9984268,0.00076543883,0.00007003403,0.00024284465,0.00027965085,0.00021530113],"domain_scores_gemma":[0.9963973,0.0013547712,0.00007634704,0.00047889774,0.0011910349,0.0005017192],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0046491376,0.0022065078,0.002164803,0.0010118571,0.0028606183,0.010238552,0.0031706747,0.002282461,0.07929864],"category_scores_gemma":[0.0066127796,0.0015463495,0.0015890108,0.0014135486,0.0034326287,0.0055395155,0.0039845137,0.0042958213,0.018905587],"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":[0.0007205901,0.00042525987,0.0018281402,0.00071308087,0.00016603242,0.00051889016,0.0053350963,0.0063442932,0.005410898,0.059704367,0.6025369,0.31629643],"study_design_scores_gemma":[0.00013980154,0.00011902973,0.0037863501,0.00077828317,0.00025773174,0.0005398542,0.0021358775,0.023616102,0.0043475665,0.05070425,0.9134287,0.00014646801],"about_ca_topic_score_codex":0.28210473,"about_ca_topic_score_gemma":0.35676157,"teacher_disagreement_score":0.28210473,"about_ca_system_score_codex":0.006446068,"about_ca_system_score_gemma":0.008827969,"threshold_uncertainty_score":0.56092536},"labels":[],"label_agreement":null},{"id":"W7002391173","doi":"","title":"New Horizons Band, on New Horizons Radio - 2015 NCRA Awards","year":2014,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Speech and dialogue systems","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":"New horizons; Period (music); Focus (optics); Musical; Entertainment","score_opus":0.00650307510440571,"score_gpt":0.19262342996539653,"score_spread":0.18612035486099082,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7002391173","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":[0.0018356292,0.00066746265,0.00043392775,0.0038016012,0.0073914155,0.0001450211,0.001958972,0.00075242243,0.98301363],"genre_scores_gemma":[0.0019102766,0.00011965646,0.00008054459,0.00020014678,0.00036135566,0.000027019147,0.00037759542,0.000118834825,0.9968046],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99925584,0.000052905227,0.000017854194,0.00008599946,0.0003611398,0.00022620274],"domain_scores_gemma":[0.9985684,0.00007747136,0.00003002234,0.000066986184,0.00039613224,0.0008609058],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0012151344,0.0005705993,0.00036512068,0.0011760393,0.0030737328,0.0057760146,0.00079583947,0.0015190192,0.6103693],"category_scores_gemma":[0.0024562355,0.00020539353,0.00027932756,0.0006208769,0.00037384123,0.0020870923,0.0029631923,0.0018442649,0.34276897],"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":[0.000046213067,0.000040535306,0.00011851583,0.000026106201,9.125681e-7,0.00004863179,0.00006380548,0.000019766656,0.0001858843,0.0016702455,0.97062945,0.027149953],"study_design_scores_gemma":[0.0000046350438,0.000017637389,0.00059022463,0.000026060477,7.1716664e-7,0.000018284374,0.00011960607,0.000035749876,0.00006851095,0.00018325215,0.9989318,0.0000036622812],"about_ca_topic_score_codex":0.008283212,"about_ca_topic_score_gemma":0.04060555,"teacher_disagreement_score":0.38963068,"about_ca_system_score_codex":0.0016812505,"about_ca_system_score_gemma":0.002190806,"threshold_uncertainty_score":0.55576086},"labels":[],"label_agreement":null},{"id":"W7007903641","doi":"","title":"Adaptive training simulation using speech interaction for training navy officers","year":2016,"lang":"en","type":"article","venue":"NPARC","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":true,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Navy; Officer; Session (web analytics); Leverage (statistics); Software deployment; Context (archaeology); Training (meteorology); Variety (cybernetics); Adaptive learning","score_opus":0.1477311359592093,"score_gpt":0.3242305348380384,"score_spread":0.17649939887882907,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7007903641","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":[0.5551572,0.00033654322,0.4010663,0.0005861819,0.00020420917,0.00069592893,0.00033095584,0.0048378203,0.03678491],"genre_scores_gemma":[0.91797835,0.00022204747,0.07049311,0.000092452436,0.000029481373,0.00032742246,0.00021357335,0.00008874655,0.010554917],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99979585,0.0000828734,0.000011031928,0.000030990843,0.000056462548,0.000022764598],"domain_scores_gemma":[0.9996463,0.00021164486,0.00001895963,0.000023989263,0.000047823687,0.000051286974],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029870536,0.00043083113,0.0001742593,0.00024599984,0.00025010758,0.0006545225,0.00052348344,0.0005307756,0.0070003043],"category_scores_gemma":[0.0011695487,0.00014577957,0.0002550694,0.00011380594,0.00025770845,0.00035181423,0.0010084084,0.00030038485,0.00086693995],"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":[0.0022561485,0.0015503331,0.009740243,0.0007144946,0.00009568634,0.0015262392,0.0050930735,0.30770952,0.22732835,0.006581734,0.009233198,0.428171],"study_design_scores_gemma":[0.00025484033,0.0024707369,0.010416179,0.00015467597,0.00009937134,0.00067933934,0.0014156054,0.88446635,0.05724065,0.0036203554,0.039065205,0.00011668853],"about_ca_topic_score_codex":0.0022739973,"about_ca_topic_score_gemma":0.0027066024,"teacher_disagreement_score":0.0070003043,"about_ca_system_score_codex":0.0002250736,"about_ca_system_score_gemma":0.00046469056,"threshold_uncertainty_score":0.023418307},"labels":[],"label_agreement":null},{"id":"W7015218210","doi":"","title":"Speech-Enabled Mobile Field Applications","year":2004,"lang":"en","type":"article","venue":"NPARC","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"National Research Council Canada; Acadia University","keywords":"Field (mathematics); Usability; Mobile phone; Phone; Mobile technology; Mobile computing","score_opus":0.009328961512471253,"score_gpt":0.23539459681811806,"score_spread":0.2260656353056468,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7015218210","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":[0.20585121,0.010451901,0.5992968,0.0024392775,0.0011917871,0.0014074733,0.0025689467,0.030215273,0.14657728],"genre_scores_gemma":[0.7114917,0.0053041037,0.18442056,0.001164998,0.00074723596,0.0007752205,0.0019067995,0.0005094266,0.09367997],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.99961543,0.00011249453,0.000022335573,0.00006617799,0.00014623397,0.000037357167],"domain_scores_gemma":[0.9989278,0.00053262623,0.000037234116,0.000082619794,0.00035022895,0.00006948405],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00058903586,0.0006336132,0.00033951277,0.00071543833,0.00048715167,0.0011266624,0.00074924686,0.0009521654,0.018909661],"category_scores_gemma":[0.0014145148,0.00020200825,0.00021494571,0.00048524252,0.00021347009,0.00092262443,0.00085273286,0.00039913625,0.0053578224],"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":[0.0014937279,0.0002972853,0.002021453,0.0015151975,0.00004127293,0.0016735942,0.0022318673,0.003906883,0.16849639,0.010502069,0.04156663,0.76625365],"study_design_scores_gemma":[0.00047835248,0.0027864256,0.008687918,0.0007483984,0.00020376682,0.00709122,0.0031716726,0.06475444,0.17437893,0.011467702,0.7260039,0.00022735407],"about_ca_topic_score_codex":0.00071241206,"about_ca_topic_score_gemma":0.0007921178,"teacher_disagreement_score":0.018909661,"about_ca_system_score_codex":0.0002631066,"about_ca_system_score_gemma":0.00023307784,"threshold_uncertainty_score":0.063259125},"labels":[],"label_agreement":null},{"id":"W7015899733","doi":"","title":"Voice and Multimodal Access to AEC Project Information","year":2003,"lang":"en","type":"article","venue":"NPARC","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":true,"route_about_ca":false,"ca_institutions":"","funders":"National Research Council Canada; Stanford Bio-X; Industry Canada","keywords":"Laptop; Mobile device; Mobile Web; Web application; Mobile telephony; Mobile technology; Wireless; Mobile computing","score_opus":0.021258899079428965,"score_gpt":0.27412308961614423,"score_spread":0.25286419053671527,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7015899733","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":[0.27945355,0.008030155,0.48024964,0.0036476343,0.00058951636,0.00034060655,0.0010232214,0.0035116547,0.22315402],"genre_scores_gemma":[0.9120774,0.0027512694,0.057014238,0.0005812044,0.00047197362,0.00018897021,0.0005238875,0.00017069528,0.026220229],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9983765,0.0007066998,0.00009787074,0.000186387,0.0004848933,0.00014774266],"domain_scores_gemma":[0.99583226,0.002306791,0.00044266568,0.00043207413,0.00083039486,0.00015581171],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012076136,0.0003458773,0.00032121016,0.0011780484,0.00050908444,0.0020934925,0.00046930293,0.0010273982,0.006883093],"category_scores_gemma":[0.009059638,0.00017954271,0.00019290023,0.0009947707,0.0006379584,0.0022869438,0.0019570962,0.0005152745,0.0015571624],"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":[0.0007227615,0.00011467967,0.0052117156,0.00085703353,0.000056551322,0.001734277,0.008868919,0.003472965,0.07128005,0.038659092,0.013494545,0.8555275],"study_design_scores_gemma":[0.00024045935,0.0014057547,0.061812937,0.0018619833,0.00036470033,0.013820367,0.018436035,0.13261975,0.10846614,0.13955252,0.52076894,0.00065035577],"about_ca_topic_score_codex":0.0007467232,"about_ca_topic_score_gemma":0.0008737692,"teacher_disagreement_score":0.006883093,"about_ca_system_score_codex":0.00028583742,"about_ca_system_score_gemma":0.00029100748,"threshold_uncertainty_score":0.023026228},"labels":[],"label_agreement":null},{"id":"W7030125421","doi":"","title":"Mimosa - Bucolique CD","year":2002,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Speech and dialogue systems","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":"Disclaimer; Fair use; Statute; Lyrics; Balance (ability); Section (typography); Performance art; Copyright Act","score_opus":0.00666035710744069,"score_gpt":0.17711948369673985,"score_spread":0.17045912658929915,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7030125421","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":[0.00089441036,0.00069610565,0.00084447156,0.00096675666,0.0028788352,0.00010159703,0.0030905486,0.0033079872,0.9872192],"genre_scores_gemma":[0.0026084601,0.00024921395,0.000411384,0.00030359413,0.0004807042,0.00005124319,0.0017251495,0.0006528543,0.9935175],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99930346,0.000044123946,0.000017288052,0.00013544344,0.00034825166,0.00015150484],"domain_scores_gemma":[0.99859065,0.000078680874,0.00003357009,0.00016879063,0.00069586746,0.00043239296],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006637874,0.0009967402,0.0006507492,0.0017668072,0.0031241,0.0071758046,0.0012591628,0.0013015957,0.7840066],"category_scores_gemma":[0.002148436,0.00036743958,0.00046531484,0.0015395883,0.00038030415,0.0024011221,0.0035023184,0.001347339,0.5935245],"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":[0.00006244258,0.00001655697,0.00004529993,0.000037347985,0.0000011781988,0.000034313154,0.00004344797,0.000021016098,0.00037238907,0.0017991184,0.9699211,0.027645692],"study_design_scores_gemma":[0.000006633072,0.0000052210207,0.0002122078,0.000015377647,7.023604e-7,0.000028400455,0.00004195978,0.00003278504,0.00006267732,0.00013530259,0.99945503,0.0000036696129],"about_ca_topic_score_codex":0.015040581,"about_ca_topic_score_gemma":0.040048357,"teacher_disagreement_score":0.7840066,"about_ca_system_score_codex":0.0021677106,"about_ca_system_score_gemma":0.0018663398,"threshold_uncertainty_score":0.30808836},"labels":[],"label_agreement":null},{"id":"W7037570102","doi":"","title":"Eramosa River Trail 3 Bridges Panorama, Guelph ON Canada","year":2024,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"Speech and dialogue systems","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":"Reef; Excavation; Bank; Abutment; Alluvium; Levee; Railway line; Terrace (agriculture); Precast concrete","score_opus":0.006312060573124359,"score_gpt":0.17669007840330636,"score_spread":0.170378017830182,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7037570102","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":[0.043354884,0.0025910626,0.0008301429,0.0028354302,0.00052143086,0.00024024153,0.008920771,0.00048591575,0.9402201],"genre_scores_gemma":[0.05079314,0.0010664542,0.0011862456,0.0006385098,0.00002319676,0.00005399357,0.0023346778,0.00015225557,0.9437515],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9995739,0.000018111206,0.000006942381,0.00010368221,0.00014781098,0.00014960681],"domain_scores_gemma":[0.9994879,0.00001726045,0.000015177295,0.00002242169,0.00028022984,0.00017704662],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00016329583,0.00046724052,0.00023943241,0.0005936439,0.0063886475,0.0018884895,0.0005773646,0.0006341753,0.18097661],"category_scores_gemma":[0.00059094466,0.0004474617,0.00017975614,0.00086613913,0.0006484452,0.0005274201,0.0015400787,0.0007936417,0.021857597],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024798283,0.000089750756,0.019985488,0.00029848778,0.000025751446,0.0012639872,0.0019650667,0.00038626505,0.0034680264,0.015226375,0.7648291,0.19221371],"study_design_scores_gemma":[0.000015824213,0.000029212857,0.039677724,0.00015481804,0.0000071939185,0.00022357354,0.0015791102,0.0001341438,0.000348296,0.00034349982,0.95746934,0.000017287044],"about_ca_topic_score_codex":0.90798485,"about_ca_topic_score_gemma":0.9910602,"teacher_disagreement_score":0.18097661,"about_ca_system_score_codex":0.010561639,"about_ca_system_score_gemma":0.021980941,"threshold_uncertainty_score":0.6054271},"labels":[],"label_agreement":null},{"id":"W7097566049","doi":"","title":"Professional Experience","year":2011,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Event (particle physics); Zoom; Perception; Tracking (education); Window (computing)","score_opus":0.053980142321587224,"score_gpt":0.25623534036167156,"score_spread":0.20225519804008435,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7097566049","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":[0.01296623,0.0036276516,0.007031491,0.023187885,0.00479197,0.00016902,0.00096352876,0.00074481836,0.9465174],"genre_scores_gemma":[0.0447177,0.0024752156,0.0031333196,0.005978004,0.0006785714,0.000101511905,0.0006567876,0.00022885509,0.9420301],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.997148,0.00069341704,0.0001394896,0.00035284442,0.0010742594,0.0005921036],"domain_scores_gemma":[0.99170846,0.000414146,0.00021700638,0.00048398375,0.0020660234,0.005110342],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0025659415,0.00053045014,0.00047809372,0.0011573078,0.0035180568,0.005044373,0.0011701783,0.0014107542,0.40558952],"category_scores_gemma":[0.006548568,0.00025262544,0.00039441258,0.0010994697,0.0012569334,0.0028451493,0.005533328,0.0020216433,0.19953008],"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":[0.000085077445,0.00040994873,0.0025344966,0.00022418896,0.000007976246,0.0005710201,0.007568648,0.00011662359,0.00086990325,0.019459765,0.74378616,0.22436614],"study_design_scores_gemma":[0.000006446518,0.00004937019,0.0010009228,0.00010940842,0.0000018102195,0.00053875905,0.0036875657,0.000057716403,0.00011892005,0.0021926493,0.9922281,0.00000834329],"about_ca_topic_score_codex":0.002757797,"about_ca_topic_score_gemma":0.008090492,"teacher_disagreement_score":0.5944105,"about_ca_system_score_codex":0.0020082844,"about_ca_system_score_gemma":0.00537501,"threshold_uncertainty_score":0.8478544},"labels":[],"label_agreement":null},{"id":"W7099464208","doi":"","title":"Université de Montréal,","year":2007,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Work (physics); Center (category theory); Research center; Politics","score_opus":0.005399800930429118,"score_gpt":0.17976940355324167,"score_spread":0.17436960262281256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7099464208","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":[0.0033692606,0.028907925,0.0024197723,0.0091349855,0.002084093,0.00009836567,0.019288685,0.00072885107,0.93396795],"genre_scores_gemma":[0.023415223,0.013020585,0.0024259132,0.0010192256,0.00026630666,0.00009724158,0.0062487847,0.00045896013,0.95304775],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978294,0.00021787298,0.000075131415,0.0008204272,0.0007055834,0.00035148716],"domain_scores_gemma":[0.9981565,0.00032378468,0.00011314152,0.0002534841,0.00073979463,0.0004133662],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00087919313,0.0017694532,0.0014914171,0.0019968448,0.003176473,0.0076266,0.002128916,0.0019548433,0.59399676],"category_scores_gemma":[0.0036739083,0.0005519255,0.000580003,0.003785999,0.0017245649,0.0032235538,0.0025303038,0.0020786745,0.21236144],"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":[0.00028511518,0.00012028497,0.0036393374,0.000976127,0.00008023328,0.0011489309,0.0014066327,0.00065135513,0.0013991232,0.1109208,0.6003033,0.27906877],"study_design_scores_gemma":[0.000020931735,0.00001803957,0.003108092,0.0002120601,0.000012583564,0.00023795264,0.00032022438,0.0001436386,0.0002859192,0.0038025342,0.9918114,0.000026656127],"about_ca_topic_score_codex":0.26252457,"about_ca_topic_score_gemma":0.332941,"teacher_disagreement_score":0.7374754,"about_ca_system_score_codex":0.008202219,"about_ca_system_score_gemma":0.009617924,"threshold_uncertainty_score":0.5791143},"labels":[],"label_agreement":null},{"id":"W7112404773","doi":"","title":"Extending an interoperable platform to facilitate the creation of multilingual and multimodal NLP applications","year":2013,"lang":"en","type":"article","venue":"Research Explorer (The University of Manchester)","topic":"Speech and dialogue systems","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":"Open Text (Canada)","funders":"Engineering and Physical Sciences Research Council","keywords":"Interoperability; Feature (linguistics); Semantics (computer science); Semantic interoperability","score_opus":0.11879516844262727,"score_gpt":0.3081394766782208,"score_spread":0.1893443082355935,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7112404773","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":[0.021370178,0.00047506767,0.8378977,0.001639848,0.00057973224,0.0012467189,0.0018531148,0.11381509,0.021122547],"genre_scores_gemma":[0.14223167,0.00073321705,0.77946985,0.0011028704,0.00024242961,0.0020942402,0.016762327,0.022497904,0.034865454],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99687165,0.0008215865,0.00037646442,0.00066880975,0.00093345536,0.00032806856],"domain_scores_gemma":[0.994945,0.0014343727,0.00015967916,0.0020745322,0.0008330841,0.00055339665],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0063233613,0.0014024549,0.00091379444,0.0018769957,0.0018189325,0.0054258006,0.003772683,0.0028824594,0.014361686],"category_scores_gemma":[0.011205592,0.0013913739,0.0015524456,0.0012551144,0.0011512071,0.013990557,0.018667711,0.0047558453,0.011224316],"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":[0.0024765735,0.0024620788,0.006181336,0.0014684047,0.00038846247,0.0048568784,0.011032283,0.008422992,0.11945639,0.100968055,0.14029165,0.6019949],"study_design_scores_gemma":[0.00046914816,0.000416432,0.002414695,0.0005335914,0.00024840006,0.0016056324,0.0014653767,0.11282672,0.07047889,0.06521981,0.7439463,0.00037499025],"about_ca_topic_score_codex":0.0027830047,"about_ca_topic_score_gemma":0.003472289,"teacher_disagreement_score":0.014361686,"about_ca_system_score_codex":0.00061132456,"about_ca_system_score_gemma":0.0018886854,"threshold_uncertainty_score":0.048044622},"labels":[],"label_agreement":null},{"id":"W7114898986","doi":"10.1145/3747327.3783913","title":"10.1145/3747327.3783913","year":2000,"lang":"en","type":"article","venue":"Time to knit","topic":"Speech and dialogue systems","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); Component (thermodynamics); Modality (human–computer interaction); Affect (linguistics)","score_opus":0.005764925963838844,"score_gpt":0.16684781941917837,"score_spread":0.16108289345533952,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7114898986","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":[0.0017625844,0.005285346,0.011005584,0.0012471019,0.002057948,0.0004929725,0.016658153,0.0204212,0.94106907],"genre_scores_gemma":[0.002949673,0.0020748249,0.0017106177,0.0007119567,0.0001504582,0.00021680655,0.0077760685,0.002365899,0.98204374],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992349,0.000053671734,0.000066421526,0.00022715717,0.00025386785,0.00016390237],"domain_scores_gemma":[0.9982297,0.0004210514,0.000083488834,0.0005442002,0.00039114183,0.00033041518],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0018594034,0.003958232,0.002821809,0.0030220053,0.0027245407,0.005140623,0.003159028,0.0063443026,0.95448977],"category_scores_gemma":[0.0037483824,0.0021916025,0.0013791827,0.008652555,0.0016520064,0.011299175,0.0066796164,0.0029197107,0.97239965],"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":[0.00025926973,0.00014500988,0.00037102067,0.0006001254,0.000040086517,0.00018921729,0.000096188785,0.0005330997,0.0012358832,0.004977039,0.70446694,0.2870862],"study_design_scores_gemma":[0.00004070086,0.000034203065,0.0007053781,0.00025556362,0.000042323976,0.00013921957,0.00007786709,0.0006540743,0.0005295057,0.0011377492,0.9963477,0.00003566753],"about_ca_topic_score_codex":0.01876582,"about_ca_topic_score_gemma":0.013194252,"teacher_disagreement_score":0.045510232,"about_ca_system_score_codex":0.0025895394,"about_ca_system_score_gemma":0.0011467153,"threshold_uncertainty_score":0.06491482},"labels":[],"label_agreement":null},{"id":"W7124176142","doi":"10.65109/rtds4918","title":"A Pragmatic Approach to Build Conversation Protocols Using Social Commitments","year":2004,"lang":"","type":"article","venue":"","topic":"Speech and dialogue systems","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; Université Laval","funders":"","keywords":"Conversation; Conversation analysis; Agency (philosophy); Context (archaeology); Key (lock)","score_opus":0.06742156670692966,"score_gpt":0.3236817608114514,"score_spread":0.2562601941045217,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7124176142","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":[0.0017648124,0.000052666535,0.9905425,0.00055249676,0.00008276614,0.00015706074,0.00007300353,0.00058517564,0.0061894935],"genre_scores_gemma":[0.11617639,0.00013955914,0.8729959,0.000287463,0.000119184246,0.00095419405,0.00032093003,0.0007005522,0.008305786],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.98946524,0.00577097,0.0007467991,0.001105376,0.002437773,0.00047388044],"domain_scores_gemma":[0.9867849,0.0067691742,0.00042818786,0.0036340733,0.0018287885,0.0005549031],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008998019,0.0013573884,0.001133427,0.0019006495,0.0045021013,0.005285537,0.0044115684,0.0031063964,0.012415708],"category_scores_gemma":[0.025105376,0.0024377587,0.0034631703,0.0013038849,0.006652605,0.009855764,0.0101216985,0.0062897946,0.0039772573],"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":[0.000035178975,0.00004258979,0.00014277273,0.0001671591,0.000040766234,0.00010146033,0.0017215381,0.005376642,0.0016542021,0.96306014,0.0024803984,0.025177145],"study_design_scores_gemma":[0.000050104318,0.00007952594,0.00010907114,0.00013254558,0.00012422836,0.00016191466,0.0008641466,0.0954945,0.005718147,0.84516275,0.052008178,0.00009488726],"about_ca_topic_score_codex":0.0036181663,"about_ca_topic_score_gemma":0.004184785,"teacher_disagreement_score":0.012415708,"about_ca_system_score_codex":0.0017890357,"about_ca_system_score_gemma":0.0033685844,"threshold_uncertainty_score":0.04758668},"labels":[],"label_agreement":null},{"id":"W7125770938","doi":"10.21428/594757db.d4fa15c1","title":"Conversation Alignment for Task-Oriented Dialogue Agents","year":2024,"lang":"en","type":"article","venue":"","topic":"Speech and dialogue systems","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; Queen's University","funders":"","keywords":"Conversation; Component (thermodynamics); Scope (computer science); Hyperparameter; Test (biology); Dialog system; Beam search","score_opus":0.021806409318928664,"score_gpt":0.2636772030765954,"score_spread":0.24187079375766676,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7125770938","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.037316363,0.00020851627,0.9422691,0.00028925607,0.00007069312,0.00046046122,0.00016006017,0.016598085,0.0026274438],"genre_scores_gemma":[0.40194097,0.00007494163,0.59337115,0.0002685711,0.000041239186,0.000655405,0.00049669604,0.0013575419,0.0017933939],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9814324,0.0106849745,0.0013640093,0.0023987007,0.0034196484,0.00070016825],"domain_scores_gemma":[0.95899224,0.025632247,0.0028039906,0.00479371,0.0063115666,0.0014663291],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.014299323,0.001555205,0.0015371039,0.0016422637,0.0022778031,0.0038528133,0.0033149645,0.0021661485,0.0064184405],"category_scores_gemma":[0.07429349,0.0011885581,0.0011551374,0.0006759971,0.002053766,0.005385316,0.0060720146,0.0027592396,0.002870184],"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":[0.0027049254,0.0009181681,0.013862842,0.0012777089,0.0003093194,0.0009515668,0.01580553,0.09518057,0.08441236,0.045586962,0.01212597,0.7268641],"study_design_scores_gemma":[0.00012705722,0.00048712938,0.0015209117,0.0001335371,0.00007343879,0.00040059548,0.0014984964,0.89413,0.042249966,0.043401398,0.015818194,0.0001592172],"about_ca_topic_score_codex":0.0038364395,"about_ca_topic_score_gemma":0.0031852801,"teacher_disagreement_score":0.014299323,"about_ca_system_score_codex":0.0013938639,"about_ca_system_score_gemma":0.0031809062,"threshold_uncertainty_score":0.075622916},"labels":[],"label_agreement":null},{"id":"W7126418383","doi":"10.18653/v1/2024.scichat-1.8","title":"Advancing Open-Domain Conversational Agents - Designing an Engaging System for Natural Multi-Turn Dialogue","year":2024,"lang":"","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Trinity College","funders":"Trinity College Dublin; Science Foundation Ireland","keywords":"Natural (archaeology); Action (physics); Natural language; Agency (philosophy); Conversation; Process (computing)","score_opus":0.04667935234266134,"score_gpt":0.30934520724608733,"score_spread":0.262665854903426,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7126418383","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.06130206,0.00013984645,0.92382914,0.0004525705,0.00008764439,0.00056227564,0.00012695273,0.00653245,0.0069670156],"genre_scores_gemma":[0.5011476,0.00010423894,0.4878022,0.00023893197,0.000060950835,0.00063223485,0.0004352694,0.0005076614,0.00907092],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9978745,0.001198101,0.00009010453,0.00039898948,0.0003330031,0.000105373714],"domain_scores_gemma":[0.9969997,0.0016146587,0.00013714039,0.00045248607,0.00040429266,0.00039165883],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0038776097,0.0007101528,0.0005135958,0.00043131295,0.001167554,0.002461426,0.0019678767,0.0013842856,0.004498967],"category_scores_gemma":[0.009203342,0.0004934495,0.0005167476,0.0001483587,0.0014774667,0.0032835873,0.004694946,0.0019273546,0.0021477889],"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":[0.0015461076,0.0016901656,0.009708231,0.0011443433,0.00024767226,0.0011454084,0.027068453,0.15040524,0.2017975,0.10636827,0.016786078,0.4820925],"study_design_scores_gemma":[0.00012253954,0.00063355005,0.0009873095,0.000092806695,0.000066059685,0.0004125637,0.0018724927,0.8682721,0.043887284,0.026120443,0.057433654,0.000099226934],"about_ca_topic_score_codex":0.0017275459,"about_ca_topic_score_gemma":0.0018921269,"teacher_disagreement_score":0.004498967,"about_ca_system_score_codex":0.0007445698,"about_ca_system_score_gemma":0.0012915006,"threshold_uncertainty_score":0.020506978},"labels":[],"label_agreement":null},{"id":"W7131207645","doi":"10.1109/icoiics67115.2025.11390415","title":"AI Driven Trolley System with SMS Alerts for Seamless Customer Interaction","year":2025,"lang":"","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Short Message Service; Mobile phone; Phone; Service (business); Feature (linguistics); Customer service; Push technology; SMS banking; Service provider","score_opus":0.012850898032453146,"score_gpt":0.26637032402825755,"score_spread":0.2535194259958044,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7131207645","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22055343,0.0014770658,0.6694554,0.0015323254,0.00094589335,0.0011359828,0.0025556933,0.067891866,0.034452442],"genre_scores_gemma":[0.7863027,0.0004413122,0.17950177,0.00074561976,0.00020992497,0.00039852128,0.002565329,0.00034928287,0.029485496],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9994067,0.00012356498,0.000037351787,0.00014646148,0.00021672311,0.00006916187],"domain_scores_gemma":[0.99908316,0.0003547198,0.00009519298,0.00011610373,0.00028038098,0.00007048841],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00045870538,0.0008295635,0.00063212815,0.0008696889,0.00045399732,0.0010219874,0.0011825756,0.0012112153,0.008014268],"category_scores_gemma":[0.0020715483,0.00022693991,0.000504618,0.0005797142,0.00022525543,0.001037781,0.0006778144,0.0010123632,0.008136706],"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":[0.0016132027,0.0013841803,0.009967795,0.00056359195,0.00015557674,0.0007373457,0.0005228183,0.03437137,0.07752107,0.0025544602,0.03777397,0.8328346],"study_design_scores_gemma":[0.000105925596,0.0009569303,0.0095312735,0.00006583144,0.00009275474,0.00078689755,0.00020441854,0.9194714,0.03862353,0.001935584,0.028115796,0.00010969967],"about_ca_topic_score_codex":0.0054134303,"about_ca_topic_score_gemma":0.006108729,"teacher_disagreement_score":0.008014268,"about_ca_system_score_codex":0.000483155,"about_ca_system_score_gemma":0.0007040614,"threshold_uncertainty_score":0.026810348},"labels":[],"label_agreement":null},{"id":"W7133511723","doi":"10.1109/wf-pst65083.2025.00019","title":"Designing and Generating Conversational Agents in the Safe Transportation Sector Using DSL","year":2025,"lang":"","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Digital subscriber line; Key (lock); Domain (mathematical analysis); Component (thermodynamics)","score_opus":0.06345633038815422,"score_gpt":0.28522357634051626,"score_spread":0.22176724595236202,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7133511723","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0046080616,0.00006424261,0.9882647,0.00023680751,0.000049309216,0.00022788001,0.00033114728,0.0046142647,0.0016034929],"genre_scores_gemma":[0.09075922,0.00022514051,0.9034134,0.0002568683,0.000025031102,0.000535306,0.0010887183,0.001239448,0.0024569184],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99867344,0.0005257614,0.00016971194,0.0002697601,0.00029029214,0.0000710342],"domain_scores_gemma":[0.99764156,0.0013296177,0.00019403388,0.00033325478,0.00037904258,0.00012249824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0020812538,0.00084196776,0.00041201714,0.00067521096,0.0005070193,0.002188816,0.0016611591,0.0012237367,0.0028144806],"category_scores_gemma":[0.005811749,0.000891938,0.0010561736,0.00029869712,0.0011620723,0.0017446373,0.0024332984,0.0019369473,0.0015313821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00036545962,0.00041615535,0.004358452,0.0014688881,0.0001538776,0.0016810629,0.0050029214,0.37474516,0.06609306,0.29020742,0.018324882,0.2371827],"study_design_scores_gemma":[0.000091796195,0.00009160983,0.00018173394,0.00009877104,0.000048585083,0.00037581273,0.0002643046,0.8482535,0.035966735,0.03085951,0.08371647,0.000051076637],"about_ca_topic_score_codex":0.0032627285,"about_ca_topic_score_gemma":0.0040441807,"teacher_disagreement_score":0.0032627285,"about_ca_system_score_codex":0.0009894741,"about_ca_system_score_gemma":0.0018040068,"threshold_uncertainty_score":0.011006892},"labels":[],"label_agreement":null},{"id":"W7151522101","doi":"10.70675/379f95e1z6db2z46bczb78dz36a0f296fea2","title":"Systèmes de questions-réponses interactifs à grande échelle","year":2022,"lang":"","type":"dissertation","venue":"","topic":"Speech and dialogue systems","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":"Conversation; Ivory tower; Research methodology","score_opus":0.014107372813392692,"score_gpt":0.2854751908794575,"score_spread":0.2713678180660648,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7151522101","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.014553727,0.00070979,0.9504352,0.0010408902,0.00017706191,0.0006896952,0.0013891303,0.016318493,0.014685964],"genre_scores_gemma":[0.20412326,0.0012182705,0.7489925,0.00085757044,0.00017705052,0.0015984453,0.0049128225,0.0020574871,0.036062628],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9927826,0.0025154888,0.0006661353,0.0020909098,0.001701143,0.0002436065],"domain_scores_gemma":[0.9861428,0.007764469,0.00063872436,0.0023202472,0.0027246636,0.00040920285],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007209003,0.0019113881,0.0015287473,0.0030755363,0.0019122597,0.0075404653,0.0039983676,0.0032914618,0.023529055],"category_scores_gemma":[0.023183683,0.0015162578,0.0025181153,0.0022333325,0.0031172822,0.010939753,0.004443734,0.0028189404,0.0099577755],"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":[0.0013726568,0.0006919726,0.012522999,0.004209625,0.00061816873,0.0016663115,0.016145762,0.050044537,0.05604333,0.37765172,0.02414075,0.45489222],"study_design_scores_gemma":[0.00018198095,0.0005635381,0.007215537,0.0009783905,0.00047171843,0.0013559442,0.0036658745,0.34780172,0.054642994,0.25031325,0.33233878,0.00047024924],"about_ca_topic_score_codex":0.009369901,"about_ca_topic_score_gemma":0.0066080675,"teacher_disagreement_score":0.023529055,"about_ca_system_score_codex":0.002298745,"about_ca_system_score_gemma":0.0028380423,"threshold_uncertainty_score":0.07871252},"labels":[],"label_agreement":null},{"id":"W7160043136","doi":"10.1109/iccv51701.2025.00137","title":"Controlling Multimodal Llms Via Reward-Guided Decoding","year":2025,"lang":"","type":"article","venue":"","topic":"Speech and dialogue systems","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":"Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Decoding methods; Encoding (memory); Key (lock); Action (physics)","score_opus":0.021463569073309027,"score_gpt":0.2809587149882836,"score_spread":0.2594951459149746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7160043136","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":[0.07248868,0.0002883168,0.9095328,0.00043292606,0.00027218883,0.00008148427,0.000106360385,0.006842426,0.009954835],"genre_scores_gemma":[0.92842513,0.00007436734,0.06557943,0.00013003395,0.00005756283,0.00006530354,0.000062899024,0.00062950666,0.004975675],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995198,0.00014189235,0.000028796874,0.00010777968,0.00012327691,0.00007829503],"domain_scores_gemma":[0.9983512,0.0010884587,0.00010394988,0.00011646065,0.00023762051,0.00010226814],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006317764,0.0007986972,0.00063177856,0.00026380364,0.00042326495,0.0013271549,0.0008451242,0.0007929338,0.005686899],"category_scores_gemma":[0.0055576516,0.00027132296,0.00019682081,0.00018151898,0.0004778484,0.0011250392,0.0014823412,0.0012640258,0.0017890953],"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":[0.0018646843,0.0003234659,0.0020692807,0.0002966923,0.00006254911,0.00051017123,0.0007729355,0.15326399,0.37844458,0.024669424,0.0065868306,0.4311354],"study_design_scores_gemma":[0.000038839924,0.00009377035,0.00029697313,0.00001722302,0.000013764323,0.0000668095,0.00005094148,0.94447714,0.04419096,0.00877551,0.0019523973,0.0000256798],"about_ca_topic_score_codex":0.0013904686,"about_ca_topic_score_gemma":0.0022200097,"teacher_disagreement_score":0.005686899,"about_ca_system_score_codex":0.00037143464,"about_ca_system_score_gemma":0.0006473915,"threshold_uncertainty_score":0.01902461},"labels":[],"label_agreement":null},{"id":"W836999996","doi":"10.18653/v1/w15-4640","title":"The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems","year":2015,"lang":"en","type":"preprint","venue":"","topic":"Speech and dialogue systems","field":"Computer Science","cited_by":232,"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; McGill University","funders":"Samsung; Natural Sciences and Engineering Research Council of Canada; Samsung Advanced Institute of Technology","keywords":"Computer science; Benchmark (surveying); Dialog box; Microblogging; Task (project management); Artificial intelligence; Natural language processing; Social media; Resource (disambiguation); World Wide Web; Geography","score_opus":0.17529303825563777,"score_gpt":0.39027150414263845,"score_spread":0.21497846588700067,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W836999996","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":[0.0763943,0.011541841,0.027213028,0.002465836,0.0026521636,0.0017341293,0.83632,0.019965244,0.021713546],"genre_scores_gemma":[0.06674842,0.0010837581,0.030411517,0.00041326153,0.00028899405,0.0021996947,0.8915497,0.0011026772,0.0062019033],"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9961128,0.0016085752,0.0003620936,0.0006466763,0.00095162884,0.00031816622],"domain_scores_gemma":[0.9946832,0.0021431588,0.0002959451,0.001047257,0.0012621855,0.0005681357],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023557104,0.0028088947,0.001721808,0.0036627548,0.002709169,0.0020174838,0.002360523,0.003202057,0.00978261],"category_scores_gemma":[0.010842223,0.00060911366,0.00084618106,0.0037365207,0.0010187213,0.0024482042,0.0037595546,0.0026392166,0.0115445815],"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":[0.00085450977,0.0007186223,0.0025874823,0.0022931965,0.00013188546,0.00050351355,0.001181458,0.0036181412,0.0037202614,0.0032770736,0.914489,0.066624895],"study_design_scores_gemma":[0.0007407621,0.00046133125,0.024472618,0.00078630535,0.00016409333,0.001267769,0.0023242887,0.05491409,0.011523179,0.009114733,0.8938584,0.00037230988],"about_ca_topic_score_codex":0.01616824,"about_ca_topic_score_gemma":0.026281787,"teacher_disagreement_score":0.01616824,"about_ca_system_score_codex":0.0018500922,"about_ca_system_score_gemma":0.0025217421,"threshold_uncertainty_score":0.03272611},"labels":[],"label_agreement":null},{"id":"W88458750","doi":"10.1007/978-3-642-30353-1_24","title":"Learning Observation Models for Dialogue POMDPs","year":2012,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Speech and dialogue systems","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":"Université Laval","funders":"","keywords":"Partially observable Markov decision process; Computer science; Artificial intelligence; Quality (philosophy); Machine learning; Markov model; Epistemology; Markov chain","score_opus":0.043564802280104356,"score_gpt":0.24765216075679833,"score_spread":0.20408735847669396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W88458750","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":[0.009427076,0.0002564669,0.9885703,0.00017788273,0.000027061955,0.000048072667,0.00024164446,0.00070718577,0.00054427935],"genre_scores_gemma":[0.58656645,0.0008700117,0.40320182,0.00023362046,0.00017341804,0.0006840297,0.0033981577,0.00042421205,0.0044482676],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99855214,0.0004988048,0.00010848455,0.0004829133,0.00021766825,0.00013998982],"domain_scores_gemma":[0.9860096,0.012265553,0.00043158725,0.000618291,0.0004207774,0.00025412993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028577703,0.0014112802,0.0021008772,0.0009607761,0.0007371503,0.0018542478,0.0028665836,0.0016811019,0.0058566118],"category_scores_gemma":[0.015694644,0.0018601913,0.0020512745,0.0010938264,0.0013292056,0.0037885555,0.0035183593,0.0051562614,0.0011058041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040316783,0.00015314849,0.0023953575,0.0002845169,0.0001607306,0.000108368135,0.00036809535,0.7910952,0.0008178727,0.041532464,0.0028901985,0.15979086],"study_design_scores_gemma":[0.000022616498,0.000016003902,0.00009535614,0.000015550007,0.0000126724,0.0000076254605,0.00001553665,0.9661941,0.0001464826,0.033182718,0.00028425167,0.0000071856607],"about_ca_topic_score_codex":0.010610701,"about_ca_topic_score_gemma":0.015769403,"teacher_disagreement_score":0.010610701,"about_ca_system_score_codex":0.0019157823,"about_ca_system_score_gemma":0.0017399647,"threshold_uncertainty_score":0.021097898},"labels":[],"label_agreement":null},{"id":"W937110539","doi":"","title":"Commentary on van Laar","year":2001,"lang":"nl","type":"article","venue":"Scholarship at UWindsor (University of Windsor)","topic":"Speech and dialogue systems","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 Windsor","funders":"","keywords":"Computer science","score_opus":0.024643348137026396,"score_gpt":0.22419093161899217,"score_spread":0.19954758348196577,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W937110539","genre_codex":"commentary","genre_gemma":"commentary","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"commentary","genre_consensus":"commentary","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010060367,0.0036064875,0.00004093578,0.9499321,0.042705774,0.000007484965,0.000043869,0.000012653214,0.0035500359],"genre_scores_gemma":[0.0017981012,0.00096798653,0.000052382555,0.96917737,0.017141478,0.00003434801,0.000015567955,0.000047334663,0.010765376],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9802658,0.0052800435,0.0013695188,0.0038739673,0.005124233,0.0040862923],"domain_scores_gemma":[0.94447213,0.038727578,0.0019548044,0.0015103894,0.008704398,0.0046306257],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.018515507,0.0016200945,0.0034813194,0.0023366248,0.021551406,0.018676065,0.007908496,0.106882,0.01875973],"category_scores_gemma":[0.10201476,0.0022175817,0.0027898042,0.0028522573,0.015512355,0.012085535,0.008573796,0.12188206,0.010848434],"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":[0.000013370347,0.0000027961162,0.000021675303,0.000043424367,0.000009352022,0.00009837942,0.0005281573,0.000009317766,0.00001591429,0.0057379096,0.99263257,0.00088713237],"study_design_scores_gemma":[0.000032527132,0.000008415028,0.00016706856,0.0005540051,0.000027839504,0.00010421794,0.0014368072,0.000034853154,0.00008206641,0.0054797027,0.99203557,0.00003691675],"about_ca_topic_score_codex":0.06769019,"about_ca_topic_score_gemma":0.116045386,"teacher_disagreement_score":0.106882,"about_ca_system_score_codex":0.016264645,"about_ca_system_score_gemma":0.026048018,"threshold_uncertainty_score":0.13459241},"labels":[],"label_agreement":null}]}