{"id":"W6928781263","doi":"10.3886/e145421v1-131561","title":"Data and Code for: Product Innovation, Product Diversification, and Firm Growth: Evidence from Japan’s Early Industrialization","year":2023,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Booth University College","funders":"Japan Society for the Promotion of Science","keywords":"Leverage (statistics); Product (mathematics); Production (economics); New product development; Flexibility (engineering); Product innovation; Downstream (manufacturing); Appeal; Competence (human resources)","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":["metaresearch","metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.00483805,0.000855341,0.0008891278,0.0011158,0.0006293266,0.001340827,0.006086279,0.0005046196,0.00003042014],"category_scores_gemma":[0.04504569,0.0009347188,0.00002402491,0.003535436,0.0005494415,0.006909058,0.007725019,0.0008068455,0.0006980085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001868279,"about_ca_system_score_gemma":0.0005603306,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007487325,"about_ca_topic_score_gemma":0.002001101,"domain_scores_codex":[0.9915709,0.0002335281,0.001426699,0.00492434,0.001175141,0.0006693237],"domain_scores_gemma":[0.984601,0.0009288939,0.001875391,0.01093885,0.001471109,0.0001848241],"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":[0.0001932527,0.00007242792,0.005734899,0.0004501265,0.0002617706,0.000003974261,0.000164046,6.324188e-7,0.0009122087,0.00003352711,0.9914553,0.0007178548],"study_design_scores_gemma":[0.001086793,0.00007391925,0.01643176,0.001071503,0.001014219,0.0000104316,0.00007447947,0.0002186067,0.0002149408,0.000285241,0.9784811,0.001036991],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0124233,0.001929012,0.00009046242,0.001914183,0.001128524,0.003409391,0.9787389,0.0003656466,5.892152e-7],"genre_scores_gemma":[0.0006398894,0.003044009,0.0009730838,0.0001094377,0.002091461,0.0001812684,0.9926241,0.0002340804,0.0001026895],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04020763,"threshold_uncertainty_score":0.9996959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2798960489802537,"score_gpt":0.3607756138577338,"score_spread":0.08087956487748016,"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."}}