{"id":"W3211869911","doi":"10.1139/juvs-2021-0027","title":"A new scoring system for use in capture–recapture studies for bowhead whales photographed with drones","year":2021,"lang":"en","type":"article","venue":"Drone Systems and Applications","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thermo Fisher Scientific (Canada); Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; Nunavut Wildlife Management Board; Transport Canada","keywords":"Mark and recapture; Whaling; Fishery; Abundance (ecology); Whale; Drone; Population; Geography; Biology; Demography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000118746,0.0001652586,0.0003353171,0.00002556218,0.0002222621,0.00006993212,0.00008736425,0.00004717693,0.000007489849],"category_scores_gemma":[0.00001482474,0.0001333969,0.00004836078,0.0002916964,0.00006062891,0.0001297823,0.0001045034,0.00004996338,0.000004394505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001018726,"about_ca_system_score_gemma":0.00001651314,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005360528,"about_ca_topic_score_gemma":0.02468373,"domain_scores_codex":[0.9989302,0.00002083588,0.0002569468,0.0004349378,0.0001207346,0.0002363869],"domain_scores_gemma":[0.9994215,0.000125733,0.0001018252,0.000235228,0.00003894759,0.00007673024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005466011,0.0009680925,0.6292115,0.02064923,0.001695259,0.00004721777,0.01059258,0.003825651,0.01828952,0.1670889,0.03056431,0.1165211],"study_design_scores_gemma":[0.004762147,0.0003356108,0.09460326,0.001582208,0.0004647587,0.0001618721,0.04615627,0.002260697,0.0008209047,0.0007142317,0.8466642,0.001473819],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6374924,0.07952408,0.2484733,0.00159734,0.0005068452,0.02431523,0.0005337706,0.000483492,0.007073614],"genre_scores_gemma":[0.986072,0.0003065588,0.006917023,0.00004471104,0.0001138811,0.005111967,0.00002280218,0.00002678708,0.001384291],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8160999,"threshold_uncertainty_score":0.9931132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03477661646335339,"score_gpt":0.2637147575414778,"score_spread":0.2289381410781244,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}