{"id":"W2899697459","doi":"10.4324/9781315291734","title":"Japanese Industrial History: Technology, Urbanization and Economic Growth","year":2016,"lang":"en","type":"book","venue":"","topic":"Japanese History and Culture","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Urbanization; Economic geography; Geography; Economics; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002359523,0.0001984468,0.0002703255,0.000177348,0.0002900778,0.00002264093,0.0002780157,0.001537292,0.003830487],"category_scores_gemma":[0.0001060823,0.0001632934,0.00005108754,0.00004134739,0.0009139696,0.0001947222,0.00005033482,0.0003039488,0.0005176429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002777313,"about_ca_system_score_gemma":0.001333566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004112674,"about_ca_topic_score_gemma":0.001853785,"domain_scores_codex":[0.9990366,0.00005965665,0.0001799125,0.0003644428,0.0001454263,0.0002139424],"domain_scores_gemma":[0.9994419,0.00003784597,0.0001712915,0.0001690631,0.00007248569,0.0001073695],"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":[0.000005111507,0.000003914296,0.00005440372,0.000005062529,0.00001494456,0.000001996533,0.003817204,1.088014e-8,0.000003365173,0.307988,0.6876621,0.0004438125],"study_design_scores_gemma":[0.0002178354,0.0000214111,0.00000179422,0.00003753413,0.00003156165,0.00000214544,0.0006730616,1.116965e-7,0.000001334879,0.008485447,0.990285,0.0002427218],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000253613,0.001334012,9.305083e-7,0.001665245,0.001648394,0.0002655183,0.00001537453,0.0002480563,0.9945689],"genre_scores_gemma":[0.002936541,0.0002304341,0.000007812742,0.0001209673,0.001791662,0.00001291178,0.00002350267,0.00002524644,0.9948509],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3026229,"threshold_uncertainty_score":0.9997589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02350609763642073,"score_gpt":0.2227380415523526,"score_spread":0.1992319439159319,"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."}}