{"id":"W4398541674","doi":"10.7910/dvn/egwopg","title":"Replication Data for: \"Technology Adoption and Productivity Growth: Evidence from Industrialization in France\"","year":2023,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Economic Growth and Productivity","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Replication (statistics); Productivity; Industrialisation; Biology; Economics; Economic growth; Market economy","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002286355,0.0002799054,0.0006555975,0.0006726458,0.0001018623,0.0001103335,0.001072583,0.0006334783,0.0002018348],"category_scores_gemma":[0.009293837,0.0003760064,0.00003801044,0.0005532717,0.0001167762,0.00147129,0.0007923997,0.0004516019,0.009178961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001393147,"about_ca_system_score_gemma":0.00007468734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005974591,"about_ca_topic_score_gemma":0.00118219,"domain_scores_codex":[0.9965379,0.0000486035,0.0007998022,0.002258524,0.00004501488,0.0003101676],"domain_scores_gemma":[0.9941698,0.0002324985,0.0008184269,0.004661349,0.0000545223,0.00006341292],"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":[0.00004453947,0.00005496679,0.01313804,0.0001590461,0.00003993247,0.000001850064,0.00001546428,0.000007018545,0.000008246785,0.0006370802,0.9850532,0.0008405851],"study_design_scores_gemma":[0.0005242333,0.00003862193,0.00686134,0.0001300955,0.00002974537,0.000001572742,0.00001245322,0.0004776432,0.00002029866,0.0128892,0.9786576,0.0003571815],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004723958,0.0001017996,0.0008514124,0.0003653657,0.001286905,0.001011074,0.99158,0.00007176789,0.000007682893],"genre_scores_gemma":[0.0007925403,0.003454146,0.000514263,0.00005234981,0.0006395654,0.0001846688,0.9942455,0.00003332082,0.0000836165],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01225212,"threshold_uncertainty_score":0.9998692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1080197092961041,"score_gpt":0.2735990130656472,"score_spread":0.165579303769543,"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."}}