{"id":"W7100619469","doi":"","title":"TECHNOLOGY SECTOR IN NEW BRUNSWICK 1","year":2005,"lang":"en","type":"article","venue":"","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Operationalization; Cluster (spacecraft); Latent variable; Diamond model; Business cluster; Survey data collection; Manufacturing sector","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000385832,0.0003354267,0.0003341384,0.003084823,0.00107488,0.002068192,0.00090471,0.0003521038,0.006694756],"category_scores_gemma":[0.001862324,0.0003398748,0.0003665139,0.01149096,0.0004675992,0.001013516,0.001078886,0.0007484857,0.001107776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02132242,"about_ca_system_score_gemma":0.01868865,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9451298,"about_ca_topic_score_gemma":0.9640188,"domain_scores_codex":[0.999433,0.00008395225,0.00004057653,0.00009553604,0.0001196089,0.0002272388],"domain_scores_gemma":[0.998874,0.000286209,0.0002803693,0.00008255596,0.0003526204,0.0001242352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002334839,0.0001472178,0.6328797,0.0006733224,0.0001592899,0.004507378,0.006428132,0.03194594,0.003736134,0.106372,0.03170836,0.1812091],"study_design_scores_gemma":[0.0000561469,0.00005862099,0.6934369,0.0004871287,0.00008308814,0.0008177264,0.009744199,0.01591664,0.001818104,0.009143712,0.2683012,0.0001365464],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.803513,0.00877321,0.01054123,0.006342873,0.0002376971,0.0004178299,0.03635856,0.000259482,0.133556],"genre_scores_gemma":[0.9240495,0.006474158,0.004173056,0.0006474569,0.00002531154,0.000210747,0.01675583,0.00005732958,0.04760673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05487025,"threshold_uncertainty_score":0.1547056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753744818842804,"score_gpt":0.2127690167594866,"score_spread":0.1852315685710585,"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."}}