{"id":"W2916003886","doi":"","title":"Cod monitoring : results 2015, quarter 2","year":2015,"lang":"en","type":"article","venue":"Socio-Environmental Systems Modeling","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Fishing; Catch per unit effort; Environmental science; Fishery; Unit price; Business; Geography; Economics","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":[0.004701046,0.0009318716,0.001047988,0.001867419,0.0005046495,0.003120028,0.0007091606,0.0007548796,0.00605642],"category_scores_gemma":[0.004148899,0.000342578,0.001640527,0.001463819,0.0002811524,0.0007701089,0.001133818,0.0005184383,0.00539729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002761643,"about_ca_system_score_gemma":0.002840358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06515864,"about_ca_topic_score_gemma":0.03628336,"domain_scores_codex":[0.9971772,0.0003620179,0.0002243255,0.0004285007,0.001488843,0.000319083],"domain_scores_gemma":[0.9959889,0.0003229195,0.0003021831,0.000534765,0.002512874,0.0003384308],"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":[0.009246984,0.002560293,0.267609,0.001089325,0.0009573084,0.00027703,0.0004964339,0.03252247,0.009776422,0.00392651,0.4599312,0.2116071],"study_design_scores_gemma":[0.0004604311,0.002584983,0.7059568,0.0002085715,0.0003709532,0.0001647876,0.0007541444,0.02032043,0.0223852,0.001238766,0.2454244,0.0001304814],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.4344043,0.002014185,0.009518031,0.001945579,0.0007950095,0.001570617,0.455652,0.004070483,0.09002972],"genre_scores_gemma":[0.4384702,0.0006871726,0.01170174,0.000679081,0.0001768079,0.0007869945,0.4664144,0.000717116,0.08036661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06515864,"threshold_uncertainty_score":0.1295587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04371540518058536,"score_gpt":0.2663243182454857,"score_spread":0.2226089130649003,"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."}}