{"id":"W3145780687","doi":"10.1257/aeri.20190499","title":"Measuring Technological Innovation over the Long Run","year":2021,"lang":"en","type":"article","venue":"American Economic Review Insights","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":340,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Economics; Technological change; Quality (philosophy); Electricity; Work (physics); Index (typography); Government (linguistics); Industrial organization; Construct (python library); Aggregate (composite); Patent office; Macroeconomics; Computer science; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002927701,0.0001427956,0.0002878385,0.00008849401,0.0001836403,0.0001494536,0.0002619878,0.00002974954,0.0009052361],"category_scores_gemma":[0.0002465085,0.00008740212,0.00007957761,0.0007116488,0.0001790399,0.0004147428,0.000168394,0.0001712189,0.002096119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005196893,"about_ca_system_score_gemma":0.00003082888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001424532,"about_ca_topic_score_gemma":0.00004506994,"domain_scores_codex":[0.9990659,0.00002907169,0.0003776161,0.0002659174,0.00008472872,0.0001767512],"domain_scores_gemma":[0.9992281,0.00004447869,0.0002920784,0.0003286482,0.0001015091,0.000005163155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002665091,0.0001335997,0.01380968,0.00128378,0.0002141576,0.0000727151,0.00006124923,0.00006021333,0.0005973657,0.226434,0.03480598,0.7225006],"study_design_scores_gemma":[0.0001242081,0.000008193309,0.00975998,0.0005761293,0.00005262273,0.00001296013,0.00004903353,0.0006364348,0.0003508471,0.001724561,0.9864399,0.0002650836],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8857983,0.01538357,0.0002953781,0.004376894,0.0004196684,0.0004782497,8.367371e-7,0.0001627954,0.09308436],"genre_scores_gemma":[0.9735559,0.00514258,0.00002990068,0.02058817,0.0003539,0.00003075031,0.00001988224,0.00001600934,0.0002628641],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.951634,"threshold_uncertainty_score":0.9986809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1303301455025704,"score_gpt":0.240535351781061,"score_spread":0.1102052062784906,"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."}}