{"id":"W4385365405","doi":"10.1515/9780773597907-023","title":"Appointments, Enlistments, Strength and Casualties—Canadian Expeditionary Force","year":2015,"lang":"en","type":"book-chapter","venue":"McGill-Queen's University Press eBooks","topic":"Military History and Strategy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Aeronautics; Forensic engineering; Engineering","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":[0.0007758663,0.0007550331,0.0003868072,0.002569714,0.01487318,0.005958538,0.001318916,0.001590348,0.02186242],"category_scores_gemma":[0.001794838,0.0005614271,0.0003312312,0.006579912,0.00537186,0.00142769,0.001741036,0.003148573,0.001372943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.137825,"about_ca_system_score_gemma":0.1974739,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9977499,"about_ca_topic_score_gemma":0.9994475,"domain_scores_codex":[0.9987992,0.00006185093,0.0000199321,0.00007295352,0.0005531672,0.0004928779],"domain_scores_gemma":[0.9994461,0.00006188195,0.00002201882,0.00001388376,0.0002440161,0.0002121066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000320113,0.00003507954,0.00238763,0.0001432839,0.00001007657,0.0001167251,0.01268202,0.0006481315,0.0001313499,0.3795134,0.4793721,0.1249282],"study_design_scores_gemma":[0.000004701677,0.000007152826,0.01119361,0.0002321999,0.000006896185,0.00003595104,0.007708318,0.0001571924,0.00003324934,0.006824077,0.9737734,0.00002322312],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01904095,0.05741709,0.0004105577,0.0310893,0.001735136,0.00006079674,0.0008772599,0.00005983203,0.8893091],"genre_scores_gemma":[0.1747214,0.04607201,0.0005780353,0.003491958,0.0003148159,0.0000424814,0.0004061841,0.00006871118,0.7743043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.137825,"threshold_uncertainty_score":0.9999952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03159119760169839,"score_gpt":0.23409592375753,"score_spread":0.2025047261558316,"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."}}