{"id":"W2036411288","doi":"10.7202/305400ar","title":"Structure et effectifs des métiers du fer à Montréal avant 1765","year":2008,"lang":"fr","type":"article","venue":"Revue d histoire de l Amérique française","topic":"Historical Studies and Socio-cultural Analysis","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Geography; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0006344365,0.0003064484,0.0002181089,0.002658996,0.001923193,0.0009952685,0.000818736,0.0002311465,0.006769136],"category_scores_gemma":[0.002292349,0.0001805146,0.0002057842,0.003161392,0.001661381,0.0003730273,0.0009032553,0.0003931391,0.0003529302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01299909,"about_ca_system_score_gemma":0.005170759,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9594784,"about_ca_topic_score_gemma":0.9872903,"domain_scores_codex":[0.9992948,0.00008572161,0.00001976156,0.0001492399,0.0001713031,0.0002792277],"domain_scores_gemma":[0.998097,0.0003022238,0.0005815346,0.00007145631,0.0005466254,0.0004011676],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002487844,0.00004516516,0.9043468,0.000121509,0.0001175755,0.0004612744,0.02396144,0.0005233705,0.002281087,0.003209112,0.002360068,0.0623238],"study_design_scores_gemma":[0.000001285627,0.00001718538,0.9910021,0.00001408779,0.000007309479,0.00002299461,0.003071554,0.0000484756,0.0001283634,0.00002252876,0.005658235,0.000005903133],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894358,0.0009827527,0.000121864,0.0002854956,0.00001032567,0.00001518779,0.00138405,0.00001237895,0.007752096],"genre_scores_gemma":[0.9858088,0.0004311435,0.0002013928,0.00002514753,0.000006621938,0.0000106334,0.0004174146,0.000006088059,0.01309278],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04052162,"threshold_uncertainty_score":0.09431541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01041523724562339,"score_gpt":0.183238618469585,"score_spread":0.1728233812239617,"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."}}