{"id":"W2022567354","doi":"10.1007/s11187-006-9042-x","title":"Does Gibrat’s Law Hold? Evidence from Canadian Retail and Manufacturing Firms","year":2007,"lang":"en","type":"article","venue":"Small Business Economics","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"Social Sciences and Humanities Research Council of Canada; Lakehead University","keywords":"Entrepreneurship; Manufacturing; Manufacturing sector; Economics; Retail trade; Industrial organization; Econometrics; Selection (genetic algorithm); Business; Labour economics; Marketing; Commerce; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003508366,0.0003678241,0.0008375444,0.004346821,0.004703327,0.004968406,0.002297244,0.002206279,0.01204852],"category_scores_gemma":[0.03686363,0.0002920462,0.0006900971,0.009616575,0.005269836,0.002413172,0.001396666,0.001984519,0.0009092924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0251155,"about_ca_system_score_gemma":0.02575251,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9703663,"about_ca_topic_score_gemma":0.9753878,"domain_scores_codex":[0.996917,0.0001916328,0.0001223999,0.0003558062,0.001386861,0.001026292],"domain_scores_gemma":[0.946499,0.02287529,0.007634757,0.002994742,0.01696075,0.003035444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00135971,0.0003298096,0.6998097,0.0006985803,0.0003213538,0.002760176,0.0117752,0.001804281,0.0006746727,0.1001188,0.07811487,0.1022328],"study_design_scores_gemma":[0.0001684154,0.0001085134,0.884172,0.0005240701,0.0004043336,0.0002934014,0.01872352,0.001816418,0.0009849403,0.01752085,0.07515632,0.000127194],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7715639,0.01607108,0.0007368132,0.03905885,0.0001484949,0.0001041921,0.003177877,0.00006769704,0.1690711],"genre_scores_gemma":[0.988816,0.003351379,0.0001578537,0.001444062,0.00006814535,0.000007617718,0.0007353643,0.00001368082,0.005405823],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0296337,"threshold_uncertainty_score":0.1822265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0444857507855471,"score_gpt":0.1960146488501217,"score_spread":0.1515288980645746,"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."}}