{"id":"W2988845952","doi":"10.3386/w26653","title":"Do Firm Effects Drift? Evidence from Washington Administrative Data","year":2020,"lang":"en","type":"preprint","venue":"National Bureau of Economic Research","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Business","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008605079,0.0003617597,0.0006643311,0.003227061,0.0007556973,0.002526534,0.001397252,0.001626024,0.004299588],"category_scores_gemma":[0.05028031,0.0005688898,0.0007266367,0.007938749,0.001014571,0.00171154,0.001297908,0.001574405,0.001273908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001231053,"about_ca_system_score_gemma":0.0008910864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07882705,"about_ca_topic_score_gemma":0.07382514,"domain_scores_codex":[0.9957758,0.001403912,0.000517436,0.001000356,0.0007560539,0.0005465568],"domain_scores_gemma":[0.8726654,0.06502376,0.0418463,0.01446947,0.004425414,0.001569672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001801888,0.00009315081,0.9738394,0.00009238749,0.0004220779,0.0002185378,0.0005149325,0.001372473,0.0001158651,0.002853718,0.00373271,0.01656448],"study_design_scores_gemma":[0.00003637883,0.00005203097,0.9855945,0.0001265342,0.000265461,0.00008693941,0.001001902,0.004304106,0.0004375957,0.001371897,0.006690919,0.00003194786],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9754305,0.004827844,0.002365594,0.002907801,0.00009037962,0.00003644298,0.007567721,0.0000865366,0.00668712],"genre_scores_gemma":[0.9904348,0.001516816,0.0005884113,0.0003490977,0.00008483957,0.00002239946,0.005324309,0.00002740921,0.001651875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07882705,"threshold_uncertainty_score":0.1567364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6664066129892718,"score_gpt":0.5204498562652372,"score_spread":0.1459567567240346,"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."}}