{"id":"W7133275614","doi":"","title":"Stock assessment of NAFO divs. 2J3KL witch flounder","year":2023,"lang":"en","type":"other","venue":"Federal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fisheries and Oceans Canada","keywords":"Fishing; Capelin; Stock (firearms); Witch; Flounder; Stock assessment; Herring; Apex predator","routes":{"ca_aff":false,"ca_fund":true,"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":[0.0005161316,0.0002608735,0.0001210488,0.002034981,0.0003639882,0.0004259842,0.0003890128,0.0001870165,0.002008114],"category_scores_gemma":[0.0007095798,0.0001539444,0.0002827189,0.0008321509,0.0001129262,0.0003655977,0.0003373946,0.0001730359,0.0005492977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001312831,"about_ca_system_score_gemma":0.0007963861,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.132848,"about_ca_topic_score_gemma":0.3852343,"domain_scores_codex":[0.9998406,0.000007181742,0.00002313325,0.00002911494,0.00006532235,0.00003463386],"domain_scores_gemma":[0.9990483,0.00002803138,0.0002573817,0.00002852097,0.0005207853,0.0001169657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004995932,0.00002366659,0.9883376,0.00001439498,0.00001702866,0.00005983101,0.0001667264,0.0002011645,0.0006355611,0.00005044319,0.001010363,0.009433242],"study_design_scores_gemma":[0.000003441539,0.00006097518,0.9968684,0.0000184628,0.00001144001,0.00004990965,0.0004022923,0.0006229595,0.0002672198,0.00001997459,0.001670274,0.000004673954],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884488,0.0000721644,0.0002691999,0.00005410841,0.000008333369,0.00007439559,0.006671653,0.0000179921,0.004383243],"genre_scores_gemma":[0.9680884,0.0001811957,0.001748137,0.00004901295,0.00000966477,0.0001577352,0.02162918,0.000009457414,0.008127168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.867152,"threshold_uncertainty_score":0.2641495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01344246028256602,"score_gpt":0.2714377987977195,"score_spread":0.2579953385151535,"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."}}