{"id":"W1981033781","doi":"10.1139/cjfas-2014-0231","title":"When “data” are not data: the pitfalls of post hoc analyses that use stock assessment model output","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":135,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stock assessment; Computer science; Stock (firearms); Econometrics; Post hoc; Data mining; Mathematics; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2810194,0.001798788,0.002739415,0.004100239,0.003246068,0.007706437,0.004442842,0.002213689,0.002976359],"category_scores_gemma":[0.611633,0.001328865,0.002364057,0.006638411,0.007878782,0.0120923,0.0052883,0.008851336,0.001120345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002861251,"about_ca_system_score_gemma":0.006120765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007721792,"about_ca_topic_score_gemma":0.008932866,"domain_scores_codex":[0.7221002,0.2181181,0.01650025,0.01105847,0.03030373,0.001919188],"domain_scores_gemma":[0.2664627,0.5683855,0.03978965,0.08108021,0.04289216,0.00138975],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003929947,0.001056286,0.1096359,0.005637206,0.00729447,0.002068142,0.03267252,0.03273422,0.008785575,0.1257861,0.04581711,0.6245826],"study_design_scores_gemma":[0.0008260909,0.002807165,0.1129632,0.00676631,0.001987831,0.001095946,0.02353381,0.1120149,0.05802285,0.4827246,0.196033,0.001224246],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1174947,0.001639597,0.8387919,0.01835865,0.003209298,0.002194439,0.002224424,0.001517697,0.01456931],"genre_scores_gemma":[0.4856279,0.0006835966,0.4985944,0.006454475,0.001041613,0.002753311,0.001181671,0.001358588,0.002304366],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7189807,"threshold_uncertainty_score":0.8866311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6875398303356637,"score_gpt":0.4564772890122499,"score_spread":0.2310625413234138,"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."}}