{"id":"W6989765923","doi":"","title":"California Manufacturing Sector Bucks National Trend","year":2019,"lang":"en","type":"article","venue":"Chapman University Digital Commons (Chapman University)","topic":"Research, Science, and Academia","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Purchasing; Manufacturing sector; Quarter (Canadian coin); Manufacturing; National economy","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":[0.0004679684,0.0002714692,0.0002251852,0.002018598,0.001808027,0.002778378,0.0006481104,0.0007448955,0.1246025],"category_scores_gemma":[0.001625991,0.0002786198,0.0002772295,0.002406769,0.0002831684,0.001541274,0.0007017744,0.001200502,0.02256289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004386156,"about_ca_system_score_gemma":0.005564471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1632487,"about_ca_topic_score_gemma":0.3926597,"domain_scores_codex":[0.999319,0.00003199966,0.00002299031,0.0001398832,0.0003429681,0.0001431522],"domain_scores_gemma":[0.9981476,0.0001512152,0.000117683,0.00007340383,0.001136232,0.0003738392],"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":[0.0001547094,0.00006106146,0.01056779,0.000118677,0.000008455666,0.00007291795,0.0001329313,0.0003571064,0.0003030686,0.005460354,0.924533,0.05822992],"study_design_scores_gemma":[0.00002632471,0.0000748762,0.06662607,0.0001163387,0.00001386338,0.00007672183,0.001362441,0.000681688,0.0005211411,0.0006269122,0.9298584,0.00001524155],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.06077312,0.00273463,0.0005228372,0.01969934,0.002001828,0.00007341663,0.03011762,0.001263244,0.882814],"genre_scores_gemma":[0.1283056,0.002610757,0.0005203896,0.003030227,0.0003493663,0.00005053434,0.01597269,0.0001415287,0.8490187],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1632487,"threshold_uncertainty_score":0.4168368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07397013788062776,"score_gpt":0.2843758359617549,"score_spread":0.2104056980811271,"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."}}