{"id":"W6891333262","doi":"10.3886/e195005v1","title":"Data and Code for: Local Productivity Spillovers","year":2024,"lang":"en","type":"dataset","venue":"ICPSR Data Holdings","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Toronto","funders":"","keywords":"Productivity; Revenue; Sorting; Quality (philosophy); Salient; Production (economics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0008096436,0.001520487,0.001058554,0.007732603,0.002071254,0.002842885,0.003076907,0.0009598232,0.05497744],"category_scores_gemma":[0.00787942,0.0006310964,0.0009761308,0.01980451,0.0005513222,0.0009038911,0.001599965,0.001585316,0.03460338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01326394,"about_ca_system_score_gemma":0.02124744,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.9684434,"about_ca_topic_score_gemma":0.9778992,"domain_scores_codex":[0.9984667,0.0001021457,0.0001108187,0.0002298284,0.0006548082,0.0004357206],"domain_scores_gemma":[0.9932586,0.0004333931,0.0005938301,0.0007461091,0.004374272,0.0005938603],"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":[0.00003105205,0.0000166765,0.00323647,0.0002683491,0.00001695591,0.00002531283,0.00008075494,0.0004220643,0.00004514007,0.000997209,0.99164,0.003220052],"study_design_scores_gemma":[0.00009572715,0.00001023325,0.03433964,0.0002842405,0.00002249326,0.00003902826,0.0003896787,0.0007877174,0.0002444837,0.0006972047,0.9630249,0.00006482655],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002989128,0.00005081292,0.00005361184,0.00005902208,0.000009373681,0.00001691974,0.9979342,0.0001278376,0.001449283],"genre_scores_gemma":[0.001723792,0.00008268311,0.0003572814,0.00003486509,0.000006224809,0.00007504198,0.9952244,0.00005268626,0.002443088],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9684434,"threshold_uncertainty_score":0.1839179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1061395928701074,"score_gpt":0.3590005546381066,"score_spread":0.2528609617679992,"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."}}