{"id":"W7133274121","doi":"","title":"2018 4X5Y Atlantic Cod Framework Data Inputs","year":2022,"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":"","keywords":"Fishing; Stock assessment; Stock (firearms); Ecosystem; Fish stock; Variety (cybernetics); Cod fisheries","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":[0.004650109,0.0007634258,0.0006783828,0.006415528,0.00155375,0.003545304,0.002433317,0.0008165976,0.05407228],"category_scores_gemma":[0.01471423,0.0006262924,0.0009341936,0.01036622,0.0003717444,0.001172695,0.001986346,0.001067267,0.02682101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01046242,"about_ca_system_score_gemma":0.03399341,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7966206,"about_ca_topic_score_gemma":0.8017139,"domain_scores_codex":[0.9967002,0.0002447206,0.0004516926,0.0003205819,0.001912329,0.0003704175],"domain_scores_gemma":[0.9866071,0.0008510386,0.0005546275,0.001293468,0.01014148,0.0005522519],"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":[0.0001663998,0.00004772874,0.00999527,0.0006828283,0.00005556688,0.0001055724,0.0001733893,0.001460209,0.0003630683,0.008160664,0.9365104,0.04227881],"study_design_scores_gemma":[0.00005078024,0.000009286337,0.01124513,0.0004071198,0.00001777655,0.00002437571,0.0001544407,0.0005789027,0.0004218466,0.001262992,0.9857884,0.00003893916],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009632274,0.000148232,0.001531739,0.0003406536,0.0001084066,0.0002692775,0.97009,0.0008093474,0.02573912],"genre_scores_gemma":[0.004268511,0.000433302,0.00756787,0.0002934617,0.00002561793,0.0006820798,0.9737061,0.0005084106,0.01251473],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2033794,"threshold_uncertainty_score":0.4091542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675512728753354,"score_gpt":0.2576640226236893,"score_spread":0.2409088953361557,"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."}}