{"id":"W6960791464","doi":"10.14286/jsxvro","title":"NS Southern Upland Salmon Tagging","year":2023,"lang":"en","type":"dataset","venue":"Ocean Tracking Network","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ocean Tracking Network","funders":"","keywords":"Indian ocean; Tracking (education); Extraction (chemistry); Satellite tracking; Aquatic animal","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001017516,0.001323447,0.0009851702,0.001860221,0.0007787703,0.001525591,0.001890668,0.0008773981,0.05594321],"category_scores_gemma":[0.003418499,0.0004742361,0.0007447937,0.004806992,0.0002762959,0.001037682,0.001691769,0.0009172793,0.0996896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001112028,"about_ca_system_score_gemma":0.002833153,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05347336,"about_ca_topic_score_gemma":0.10348,"domain_scores_codex":[0.9990911,0.0001237861,0.0001158157,0.0003179086,0.0002132278,0.0001381917],"domain_scores_gemma":[0.9981672,0.0001904284,0.0002217445,0.0004505199,0.0007916219,0.0001784178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007622495,0.00001450757,0.002470997,0.0002267347,0.00002734278,0.00002420578,0.00002723478,0.0001382776,0.000189764,0.0003503967,0.9936008,0.002853563],"study_design_scores_gemma":[0.0001154672,0.00001529615,0.01283705,0.0002105176,0.00002781912,0.00005285978,0.0001228369,0.0002407045,0.0004327996,0.0007398704,0.9851777,0.00002705781],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000269504,0.00002110532,0.00006103114,0.00002071529,0.00001432082,0.000008776394,0.9986135,0.0001347338,0.0008562259],"genre_scores_gemma":[0.000298737,0.00001421588,0.0001538962,0.00002039224,0.000002723237,0.00003244437,0.9985998,0.00003872045,0.0008389187],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9465266,"threshold_uncertainty_score":0.1871487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02106192764622673,"score_gpt":0.2050339096573268,"score_spread":0.1839719820111001,"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."}}