{"id":"W3169635543","doi":"10.5066/p93ef3th","title":"Tracking Data for Black Scoter (Melanitta americana)","year":2020,"lang":"en","type":"article","venue":"USGS DOI Tool Production Environment","topic":"Marine animal studies overview","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Table (database); Transmitter; Metadata; Computer science; Raw data; Tracking (education); Lookup table; Database; Channel (broadcasting); Telecommunications; World Wide Web; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008450627,0.0003456016,0.0002153273,0.00204834,0.0006326956,0.0004923902,0.0004324072,0.0002030212,0.02786679],"category_scores_gemma":[0.001130493,0.0002045521,0.0002080243,0.002783493,0.0001439532,0.0003870268,0.0005302972,0.0003656864,0.01106989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007138563,"about_ca_system_score_gemma":0.001350033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1712606,"about_ca_topic_score_gemma":0.3291429,"domain_scores_codex":[0.9995301,0.00005107042,0.00004614923,0.00008430108,0.0002436591,0.00004474533],"domain_scores_gemma":[0.9980531,0.0001518158,0.000268811,0.0003022664,0.001069136,0.0001549111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005738674,0.0001235464,0.1552512,0.000636116,0.00007944184,0.0002591784,0.001368373,0.0006758674,0.01423222,0.001839208,0.6094261,0.2155348],"study_design_scores_gemma":[0.00001571456,0.00008348355,0.2890534,0.0001356537,0.00002659043,0.0001125643,0.0004492654,0.0001524236,0.001786003,0.0002023768,0.7079573,0.00002523661],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.06331869,0.001016382,0.005534774,0.0005070674,0.0002723815,0.0005153206,0.8279185,0.00146568,0.09945112],"genre_scores_gemma":[0.07893886,0.00168056,0.01760928,0.0002982066,0.00007485196,0.000647459,0.8070121,0.0005668986,0.0931718],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1712606,"threshold_uncertainty_score":0.3405274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07044706175497739,"score_gpt":0.2569682618295469,"score_spread":0.1865212000745695,"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."}}