{"meta":{"query_hash":"11a49fd77d9b","filters":{"venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast"},"cohort_total":10,"direct_labels_cover":0,"predictions_cover":10,"exported":10,"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/11a49fd77d9b","api":"https://metacan.xera.ac/api/v1/cohort?venue=Global+Oceans+2020%3A+Singapore+%E2%80%93+U.S.+Gulf+Coast"},"results":[{"id":"W3153019485","doi":"10.1109/ieeeconf38699.2020.9389215","title":"Semisubmersible Offshore Structure in an Extreme Wave Domain with Itinerant Ice Pieces","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Wind and Air Flow Studies","field":"Environmental 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":"Community Sector Council Newfoundland and Labrador","funders":"","keywords":"Submarine pipeline; Code (set theory); Marine engineering; Domain (mathematical analysis); Time domain; Geology; Meteorology; Computer science; Engineering; Physics; Oceanography; Mathematics","score_opus":0.01608998228631029,"score_gpt":0.21042671829568665,"score_spread":0.19433673600937637,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153019485","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":[0.9911067,0.000031174386,0.0040407404,0.00007730613,0.000010136384,0.000017900731,0.00016035717,0.000042559284,0.004513024],"genre_scores_gemma":[0.9968748,0.000029669402,0.0018233653,0.000020579302,0.0000061297546,0.000012466454,0.00018556911,0.000010082441,0.001037256],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99993396,0.00001314212,0.0000032406967,0.0000108014365,0.000015608884,0.000023306819],"domain_scores_gemma":[0.9997446,0.00010363654,0.000052955995,0.000020393976,0.0000378068,0.000040675517],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00013883192,0.00025611042,0.00023941461,0.00033775554,0.00030210032,0.00051772257,0.00038934045,0.0006093459,0.0013025773],"category_scores_gemma":[0.00049437745,0.00016551052,0.00030513448,0.00023391246,0.00052782794,0.00024818868,0.0004539834,0.00037862637,0.00012558636],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00019296345,0.0001909645,0.017063722,0.00003620065,0.00002370228,0.0007584733,0.000085085856,0.9703406,0.005173338,0.0023082471,0.00053679716,0.0032898919],"study_design_scores_gemma":[0.000031878913,0.000079106314,0.006129058,0.0000075347507,0.0000058800138,0.00007376881,0.00013799689,0.99196774,0.00073529966,0.00048654666,0.00033625006,0.000008984986],"about_ca_topic_score_codex":0.011750646,"about_ca_topic_score_gemma":0.0073012086,"teacher_disagreement_score":0.011750646,"about_ca_system_score_codex":0.00027771012,"about_ca_system_score_gemma":0.00047656972,"threshold_uncertainty_score":0.023364484},"labels":[],"label_agreement":null},{"id":"W3153244583","doi":"10.1109/ieeeconf38699.2020.9389165","title":"Machine Vision Techniques for Situational Awareness and Path Planning in Model Test Basin Ice-Covered Waters","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Underwater Vehicles and Communication Systems","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Interfacing; Situation awareness; Software; Computer science; Process (computing); Situation analysis; Geographic information system; Systems engineering; Situational ethics; Test (biology); Field (mathematics); Engineering; Remote sensing; Geology; Operating system; Aerospace engineering","score_opus":0.019850258046825664,"score_gpt":0.25548120541722963,"score_spread":0.23563094737040396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153244583","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.008122945,0.0002229729,0.9895459,0.00006548436,0.000026010175,0.000033729586,0.000043495875,0.00060119893,0.0013382323],"genre_scores_gemma":[0.31147933,0.0006369671,0.6852942,0.00007180457,0.00004245902,0.00016015525,0.0002451661,0.0001339097,0.0019360454],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99976236,0.00006515473,0.000012617072,0.000047017176,0.00007980078,0.00003297922],"domain_scores_gemma":[0.9997392,0.0001272399,0.000022859354,0.00003687049,0.000064757325,0.00000908283],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000462836,0.0005319278,0.0005441067,0.0010956248,0.00045673343,0.00071553956,0.00058548356,0.0006124183,0.0014945371],"category_scores_gemma":[0.0012823049,0.00037266326,0.00064431224,0.0011311145,0.00042427322,0.0008655562,0.0005079766,0.00089185644,0.0004301934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000054811542,0.00007829318,0.00074492703,0.00012346142,0.000059129634,0.00011183634,0.00015759408,0.55933195,0.013534749,0.011313944,0.0026033856,0.41188592],"study_design_scores_gemma":[0.000005532961,0.000022403341,0.00042824293,0.000008945595,0.000006774989,0.000038118094,0.00003771797,0.99006516,0.0025007494,0.0049039964,0.0019744483,0.000007889102],"about_ca_topic_score_codex":0.008433808,"about_ca_topic_score_gemma":0.009773243,"teacher_disagreement_score":0.008433808,"about_ca_system_score_codex":0.000555033,"about_ca_system_score_gemma":0.00069965015,"threshold_uncertainty_score":0.016769469},"labels":[],"label_agreement":null},{"id":"W3153404293","doi":"10.1109/ieeeconf38699.2020.9389077","title":"A Method to Mitigate the Influence of Rain on Wind Direction Estimation From X-band Marine Radar Images","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","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":"Memorial University of Newfoundland","funders":"","keywords":"Radar; Remote sensing; Pixel; Radar imaging; Precipitation; Computer science; Standard deviation; Wind speed; Geology; Meteorology; Artificial intelligence; Geography; Mathematics; Telecommunications; Statistics","score_opus":0.00828391348347173,"score_gpt":0.22817425901970081,"score_spread":0.21989034553622908,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3153404293","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04727026,0.0003395467,0.9510504,0.00007303577,0.00010593191,0.000046750516,0.00005044106,0.00038531018,0.0006783532],"genre_scores_gemma":[0.30728045,0.0005147686,0.6893909,0.00010620945,0.00010483821,0.000054393084,0.00021948316,0.000051584302,0.0022772863],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998292,0.00001723494,0.000012510246,0.000042372827,0.00008320902,0.00001553594],"domain_scores_gemma":[0.99964416,0.00006003068,0.000070559065,0.000068220004,0.00014136228,0.000015736545],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037650866,0.0005048147,0.0003181451,0.0005337127,0.00022844372,0.00028446584,0.00057347363,0.0003157191,0.0005503535],"category_scores_gemma":[0.0008649939,0.00022494764,0.00032329993,0.00039696443,0.00021782337,0.0008075413,0.00045913187,0.0005334571,0.00026182362],"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":[0.00020186404,0.00011615979,0.004276383,0.00021574042,0.00010548647,0.000102190796,0.00014885684,0.030866463,0.2293154,0.0016390837,0.0012142884,0.731798],"study_design_scores_gemma":[0.000057260848,0.0004591161,0.015295371,0.000038214657,0.00012748488,0.0007575055,0.000103447564,0.76761144,0.20405082,0.001278913,0.010152168,0.000068182446],"about_ca_topic_score_codex":0.0011671304,"about_ca_topic_score_gemma":0.00298307,"teacher_disagreement_score":0.0011671304,"about_ca_system_score_codex":0.00013326082,"about_ca_system_score_gemma":0.00035424548,"threshold_uncertainty_score":0.0023206472},"labels":[],"label_agreement":null},{"id":"W3154000445","doi":"10.1109/ieeeconf38699.2020.9389297","title":"Modeling VHF Scatter from FY and MY Sea Ice Ridges","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","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":"Memorial University of Newfoundland","funders":"","keywords":"Ridge; Geology; Sea ice; Scattering; Remote sensing; Range (aeronautics); Meteorology; Climatology; Geography; Aerospace engineering; Optics","score_opus":0.01332360618822743,"score_gpt":0.2053797433175313,"score_spread":0.1920561371293039,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154000445","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":[0.91299546,0.00009626723,0.08234799,0.00008800049,0.000022216995,0.000026747899,0.00023092118,0.00016275031,0.004029592],"genre_scores_gemma":[0.9941287,0.00006673308,0.0046191537,0.000011764472,0.000010338252,0.000009004903,0.00014357232,0.000016650192,0.0009939981],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999114,0.000016975866,0.000003900329,0.000016518003,0.000022290957,0.000028895103],"domain_scores_gemma":[0.99981064,0.00008814902,0.000027074846,0.000019038527,0.000038890295,0.000016230868],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026871843,0.0003647985,0.00020287801,0.0003367675,0.00022471849,0.00054981787,0.00033074815,0.00045334795,0.00044770722],"category_scores_gemma":[0.0005162866,0.00020823363,0.0005486306,0.0002758566,0.00025483628,0.00036709875,0.00025387618,0.00021220905,0.00012799073],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000052989504,0.000034891935,0.014062276,0.000015051553,0.00001811883,0.00007627367,0.000076060984,0.97110254,0.0068058013,0.0009599484,0.00017604895,0.006619975],"study_design_scores_gemma":[0.0000035817488,0.000011032921,0.0027088777,0.0000016978968,0.0000041364774,0.000024291172,0.000017489336,0.99636,0.00058825524,0.00016153925,0.00011534741,0.0000037081759],"about_ca_topic_score_codex":0.021651508,"about_ca_topic_score_gemma":0.011857076,"teacher_disagreement_score":0.021651508,"about_ca_system_score_codex":0.00047853962,"about_ca_system_score_gemma":0.0003937099,"threshold_uncertainty_score":0.043050945},"labels":[],"label_agreement":null},{"id":"W3154001479","doi":"10.1109/ieeeconf38699.2020.9389414","title":"Second-Order Correction to the HF Radar Cross-Section of the Ocean Surface at Electromagnetically-High Sea States","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Ocean Waves and Remote Sensing","field":"Earth and Planetary Sciences","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":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Radar cross-section; Radar; Cross section (physics); Surface wave; Physics; Wind wave; Surface (topology); Geology; Optics; Oceanography; Scattering; Geometry; Mathematics; Telecommunications; Engineering","score_opus":0.006206577628958589,"score_gpt":0.2024644574632041,"score_spread":0.1962578798342455,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154001479","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0797866,0.00072977674,0.90881425,0.0005811173,0.0009196808,0.00007043442,0.0003019006,0.0013726158,0.00742355],"genre_scores_gemma":[0.78271705,0.0015909451,0.18614128,0.0004543662,0.00028474646,0.000108060165,0.00085488206,0.0008221328,0.027026499],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99955255,0.00006140505,0.000017300907,0.000060268503,0.00022812851,0.00008023942],"domain_scores_gemma":[0.99921775,0.00016666281,0.00009088154,0.00014640306,0.0003512074,0.000027171121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00071336556,0.0007624559,0.00030613362,0.00066844525,0.00031696953,0.000557466,0.0006324165,0.00044864218,0.0024069278],"category_scores_gemma":[0.0024185542,0.00019339085,0.00078905234,0.0005577533,0.00030660446,0.00067285186,0.0005987107,0.0010494825,0.00063521124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00022373162,0.00019272356,0.029052801,0.0004899359,0.00026988625,0.0008238346,0.00033888145,0.41789272,0.22582391,0.048980337,0.007325011,0.26858622],"study_design_scores_gemma":[0.000018226923,0.000103259794,0.030498283,0.000047071935,0.00006679969,0.0010080542,0.00010040653,0.86281824,0.0824044,0.0068254406,0.016013097,0.00009674759],"about_ca_topic_score_codex":0.0077092415,"about_ca_topic_score_gemma":0.012407933,"teacher_disagreement_score":0.0077092415,"about_ca_system_score_codex":0.0007468747,"about_ca_system_score_gemma":0.0012366469,"threshold_uncertainty_score":0.015328705},"labels":[],"label_agreement":null},{"id":"W3154232124","doi":"10.1109/ieeeconf38699.2020.9389049","title":"Course-Aided Measurement-to-Track Association for Target Tracking With Compact HF Radar","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Target Tracking and Data Fusion in Sensor Networks","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":"Memorial University of Newfoundland","funders":"National Key Research and Development Program of China","keywords":"Computer science; Azimuth; Radar tracker; Clutter; Radar; Artificial intelligence; Track (disk drive); Tracking (education); Kinematics; Association (psychology); Feature (linguistics); Mathematics; Telecommunications","score_opus":0.02772768359535177,"score_gpt":0.25177575007739433,"score_spread":0.22404806648204256,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154232124","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.03230299,0.00011013117,0.96645856,0.00003054309,0.000026695194,0.000025938154,0.00003347548,0.00038568003,0.00062589097],"genre_scores_gemma":[0.592403,0.00015965373,0.4049432,0.00007097048,0.000052107094,0.00006681113,0.00041734046,0.00004720643,0.0018396267],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99952734,0.00007457261,0.000030537278,0.0001305204,0.00018690301,0.00005008846],"domain_scores_gemma":[0.99916244,0.00020623233,0.0001430887,0.00025152185,0.00020425055,0.000032500226],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006553927,0.00032468772,0.00039533712,0.00060973805,0.0004002801,0.0004001132,0.0006399677,0.00039164338,0.0007416186],"category_scores_gemma":[0.0023906992,0.00018110474,0.00029126118,0.0007480871,0.00027437488,0.0009002001,0.00089992903,0.000575752,0.0004226966],"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":[0.00036740745,0.00010423199,0.006485922,0.00005988085,0.000040435345,0.00010678074,0.00021787237,0.071339324,0.07176956,0.004200393,0.001520873,0.84378743],"study_design_scores_gemma":[0.000026093972,0.00020807728,0.0060163015,0.000008060326,0.000026561802,0.0003525809,0.000048044214,0.9513673,0.036648475,0.002065816,0.0032045809,0.000028111686],"about_ca_topic_score_codex":0.0019091944,"about_ca_topic_score_gemma":0.0030936261,"teacher_disagreement_score":0.0019091944,"about_ca_system_score_codex":0.00024892855,"about_ca_system_score_gemma":0.000613595,"threshold_uncertainty_score":0.0037961602},"labels":[],"label_agreement":null},{"id":"W3154253854","doi":"10.1109/ieeeconf38699.2020.9389229","title":"Sea Ice Image Semantic Segmentation Using Deep Neural Networks","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","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":"Memorial University of Newfoundland","funders":"Canadian Space Agency; Memorial University of Newfoundland","keywords":"Computer science; Segmentation; Artificial intelligence; Image segmentation; Pixel; Deep learning; Artificial neural network; Remote sensing; Process (computing); Computer vision; Pattern recognition (psychology); Geology","score_opus":0.012573624041757369,"score_gpt":0.22526574319890624,"score_spread":0.21269211915714886,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3154253854","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":[0.71050876,0.0016837766,0.2569274,0.00060675555,0.00025450834,0.0003186261,0.006175717,0.011452013,0.012072457],"genre_scores_gemma":[0.88384,0.00044671848,0.0971149,0.00027857907,0.00006044769,0.0001319082,0.01349148,0.00019197674,0.004443959],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998062,0.000022932662,0.000011950389,0.00006560565,0.000044369506,0.000049019265],"domain_scores_gemma":[0.9998274,0.000036792884,0.000028833163,0.000022268092,0.00006970991,0.000014944588],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00036723018,0.0013013416,0.0004425533,0.0013766505,0.0003256326,0.0007597955,0.00072513154,0.00061646494,0.0011924958],"category_scores_gemma":[0.0005863307,0.00027811553,0.00068136136,0.0008581059,0.00035152206,0.0012191945,0.00058095955,0.00061228377,0.00052547513],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0008192979,0.000598259,0.010414459,0.00027671736,0.0003452893,0.00021479787,0.0001390112,0.47332013,0.041825924,0.0022522542,0.013185625,0.45660824],"study_design_scores_gemma":[0.000012771298,0.00007156125,0.0020872913,0.000014441721,0.000022990025,0.000020589798,0.00004988187,0.98477477,0.010571278,0.0012924585,0.0010721507,0.000009717689],"about_ca_topic_score_codex":0.017799437,"about_ca_topic_score_gemma":0.026734166,"teacher_disagreement_score":0.017799437,"about_ca_system_score_codex":0.0009827567,"about_ca_system_score_gemma":0.0007445648,"threshold_uncertainty_score":0.03539169},"labels":[],"label_agreement":null},{"id":"W3155127060","doi":"10.1109/ieeeconf38699.2020.9389268","title":"Cabled Community Observatories for Coastal Monitoring - Developing Priorities and Comparing Results","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Marine Biology and Ecology Research","field":"Earth and Planetary Sciences","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":"Ocean Networks Canada Society","funders":"","keywords":"Citizen science; Environmental resource management; Shore; Stewardship (theology); Environmental science; Oceanography; Remote sensing; Marine spatial planning; Marine ecosystem; Government (linguistics); Geography; Ecosystem; Geology; Ecology","score_opus":0.08327340917207308,"score_gpt":0.2824338901766891,"score_spread":0.19916048100461597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155127060","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.21310212,0.009813871,0.32447332,0.021965574,0.0034872636,0.015505333,0.11074788,0.010892603,0.29001206],"genre_scores_gemma":[0.40381044,0.0046646185,0.5011565,0.0019557811,0.0006347158,0.009042815,0.05530549,0.002219819,0.021209778],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.98034966,0.005874963,0.0015289406,0.0022870007,0.008179043,0.0017804047],"domain_scores_gemma":[0.922409,0.009878869,0.0065497877,0.0076791462,0.046217334,0.0072659426],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.027088234,0.00087825744,0.00068432133,0.009242971,0.0030870084,0.0050676814,0.0029980494,0.0009925999,0.011142485],"category_scores_gemma":[0.060206223,0.00058066007,0.0007530624,0.012098408,0.000812151,0.0051368787,0.0092371525,0.0012384292,0.0030869832],"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":[0.0007795256,0.00025189648,0.25369066,0.0020607237,0.00040619253,0.0003769777,0.007986694,0.0033145212,0.0062824707,0.015248702,0.14376463,0.56583697],"study_design_scores_gemma":[0.0003574801,0.00060180284,0.34438154,0.005182211,0.00049135054,0.00045740328,0.03340396,0.013296134,0.008045516,0.01447388,0.5789235,0.0003851428],"about_ca_topic_score_codex":0.21592,"about_ca_topic_score_gemma":0.2856011,"teacher_disagreement_score":0.21592,"about_ca_system_score_codex":0.006995334,"about_ca_system_score_gemma":0.021837711,"threshold_uncertainty_score":0.42932642},"labels":[],"label_agreement":null},{"id":"W3155532278","doi":"10.1109/ieeeconf38699.2020.9388974","title":"Sea Ice Thickness Estimation From TechDemoSat-1 and Soil Moisture Ocean Salinity Data Using Machine Learning Methods","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Arctic and Antarctic ice dynamics","field":"Earth and Planetary Sciences","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":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Salinity; Sea ice; Water content; Support vector machine; Correlation coefficient; Consistency (knowledge bases); Convolutional neural network; Coefficient of determination; Seawater; Environmental science; Remote sensing; Sea ice concentration; Mean squared error; Sea ice thickness; Geology; Artificial intelligence; Computer science; Machine learning; Arctic ice pack; Mathematics; Climatology; Statistics; Oceanography","score_opus":0.034643828533166166,"score_gpt":0.2861542581348977,"score_spread":0.25151042960173153,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155532278","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":[0.8798036,0.0007005871,0.10527269,0.00018791275,0.00014462574,0.000096004725,0.0046435394,0.0021554087,0.0069956025],"genre_scores_gemma":[0.90530914,0.00023699683,0.085910045,0.00008446144,0.00005311414,0.00006743216,0.006714731,0.000087753,0.0015362962],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999785,0.000026428248,0.000019286128,0.00006119131,0.00008032294,0.000027787868],"domain_scores_gemma":[0.99973744,0.000032130083,0.00007269692,0.000035713896,0.00010304596,0.000018973118],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00040917937,0.0005704538,0.00031413953,0.0012751245,0.00017848307,0.0004946598,0.00048293555,0.0003858467,0.0007543496],"category_scores_gemma":[0.000803557,0.00020623382,0.0005979149,0.0012247174,0.00016903173,0.0006842754,0.00048881205,0.00036060723,0.00050767284],"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":[0.0003258939,0.00025942465,0.2603109,0.000330895,0.00045949864,0.0005241374,0.0001929304,0.22943252,0.085842066,0.0010853852,0.0049516764,0.41628465],"study_design_scores_gemma":[0.00004202155,0.00006382212,0.120876186,0.00004896726,0.00006270192,0.00016440198,0.0001432988,0.8484914,0.02518556,0.0005989342,0.0042643505,0.000058387286],"about_ca_topic_score_codex":0.0071803248,"about_ca_topic_score_gemma":0.015297272,"teacher_disagreement_score":0.0071803248,"about_ca_system_score_codex":0.00030989115,"about_ca_system_score_gemma":0.0005322826,"threshold_uncertainty_score":0.014277101},"labels":[],"label_agreement":null},{"id":"W3155789586","doi":"10.1109/ieeeconf38699.2020.9389447","title":"Sensitivity analysis of plunger-type wavemakers with water current","year":2020,"lang":"en","type":"article","venue":"Global Oceans 2020: Singapore – U.S. Gulf Coast","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Plunger; Sensitivity (control systems); Amplitude; Wedge (geometry); Current (fluid); Control theory (sociology); Channel (broadcasting); Mechanics; Physics; Mathematics; Engineering; Computer science; Electronic engineering; Geometry; Optics; Electrical engineering","score_opus":0.05330803913491001,"score_gpt":0.3034379045132777,"score_spread":0.2501298653783677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3155789586","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":[0.87195283,0.00026571314,0.12212148,0.00018445512,0.000047729605,0.00016288168,0.00045962218,0.0002802775,0.004525012],"genre_scores_gemma":[0.9966254,0.000047244554,0.0027915256,0.000021658907,0.0000027543879,0.000038954146,0.0001198517,0.000016442096,0.00033623687],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989637,0.00041185325,0.00004735359,0.00020001718,0.00023504285,0.000141977],"domain_scores_gemma":[0.99494606,0.0041581714,0.00021864244,0.00023082411,0.0003927285,0.000053706073],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0024627151,0.0009657016,0.00063306233,0.00077821204,0.00037821473,0.00091453607,0.0006067308,0.00090567773,0.0010266105],"category_scores_gemma":[0.007486258,0.00045309518,0.0013272067,0.00041378225,0.00052200805,0.00090620905,0.00094480894,0.0009278149,0.000091893766],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00008444037,0.000039973667,0.00366645,0.00006124396,0.00006646289,0.00010488519,0.00003252912,0.98822355,0.004449035,0.0006142646,0.00009613155,0.0025609436],"study_design_scores_gemma":[0.000010034443,0.0001577942,0.0028624537,0.000009574523,0.000045231045,0.000033421715,0.00004592336,0.990694,0.0051127956,0.0008252959,0.00018127514,0.000022280654],"about_ca_topic_score_codex":0.009672363,"about_ca_topic_score_gemma":0.0036874972,"teacher_disagreement_score":0.009672363,"about_ca_system_score_codex":0.0009896165,"about_ca_system_score_gemma":0.00057742815,"threshold_uncertainty_score":0.019232154},"labels":[],"label_agreement":null}]}