{"id":"W7020340768","doi":"","title":"Le RÃ©giment De Maisonneuve: A Profile Based on Personnel Records","year":2012,"lang":"en","type":"article","venue":"Scholars Commons (Wilfrid Laurier University)","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Infantry; Battle; Fire brigade; Plan (archaeology); Officer; World War II","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008439719,0.0001975224,0.0001493292,0.005480594,0.002377499,0.001594583,0.0004569052,0.0002928799,0.006387934],"category_scores_gemma":[0.002985524,0.0001986572,0.0001113137,0.005041523,0.0003037839,0.0009241073,0.0009750071,0.0003524284,0.001897344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00443498,"about_ca_system_score_gemma":0.006348465,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.672161,"about_ca_topic_score_gemma":0.7595945,"domain_scores_codex":[0.9993532,0.0000517146,0.00006381189,0.00005930889,0.0002646698,0.0002072351],"domain_scores_gemma":[0.9982223,0.000114508,0.0002192135,0.00004889635,0.0007742066,0.0006208665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001003737,0.00008941252,0.8843332,0.0001233436,0.000009751892,0.0008956857,0.02631968,0.0001503385,0.001530724,0.0008051456,0.02442,0.06122238],"study_design_scores_gemma":[0.000004609785,0.00005653441,0.9238346,0.0001507138,0.000005087242,0.0005399278,0.02764554,0.0003763295,0.0003220505,0.00006831145,0.04697107,0.00002523853],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9568227,0.00074521,0.0004716365,0.001655054,0.00003191954,0.0004026716,0.01097294,0.00006979911,0.02882805],"genre_scores_gemma":[0.9686049,0.001679157,0.001231958,0.0002185136,0.00002376334,0.0002346691,0.01079915,0.00003427881,0.01717359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.327839,"threshold_uncertainty_score":0.6595395,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01430167096353187,"score_gpt":0.2157720811909889,"score_spread":0.201470410227457,"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."}}