{"id":"W4385414635","doi":"10.1007/978-3-642-40458-0_43-2","title":"Cliometrics and the Study of Canadian Economic History","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Natural Resources and Economic Development","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Transformative learning; Context (archaeology); Interpretation (philosophy); Narrative; Immigration; Subsidy; Political science; Resource (disambiguation); Economics; Economy; History; Sociology; Computer science; Law","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":[0.001510875,0.0005945136,0.0005096331,0.01159277,0.005730975,0.007395967,0.001244385,0.0009077191,0.01853673],"category_scores_gemma":[0.008523335,0.0004100351,0.0003330609,0.02408652,0.0084177,0.003884182,0.0009665673,0.001915758,0.0008069882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08840331,"about_ca_system_score_gemma":0.05464142,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9809498,"about_ca_topic_score_gemma":0.9881818,"domain_scores_codex":[0.9988946,0.0002080059,0.00004904571,0.0001164889,0.0005141209,0.0002177082],"domain_scores_gemma":[0.9968361,0.001026138,0.0002100557,0.0001756876,0.001410073,0.0003418969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007980632,0.000003426566,0.001087044,0.00009876787,0.000005924824,0.00002712552,0.001196519,0.0006132301,0.00002780093,0.9030579,0.0500608,0.04381348],"study_design_scores_gemma":[0.000003163723,0.000003146836,0.008345108,0.0003383742,0.00001006216,0.00004922057,0.001979455,0.001244296,0.00005438647,0.1965624,0.7913791,0.00003128649],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01233954,0.1409924,0.01097147,0.04388967,0.001501795,0.00006731297,0.003048621,0.0002687255,0.7869205],"genre_scores_gemma":[0.5031246,0.1535985,0.01532684,0.002786678,0.001797012,0.0001204825,0.001974841,0.0004314385,0.3208396],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08840331,"threshold_uncertainty_score":0.6414139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07292718306544255,"score_gpt":0.1907116719207295,"score_spread":0.117784488855287,"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."}}