{"id":"W4417468638","doi":"10.4337/9781035317882.00021","title":"Leveraging technological change to renew creative regions: the case of Montreal","year":2025,"lang":"","type":"book-chapter","venue":"Edward Elgar Publishing eBooks","topic":"Cultural Industries and Urban Development","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Technological change; Government (linguistics); Work (physics); Context (archaeology); Production (economics); Information technology","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":[0.0009904768,0.0006007783,0.0002411394,0.001006869,0.01643157,0.01039581,0.002262089,0.002608913,0.01515342],"category_scores_gemma":[0.001656407,0.000313447,0.0004053264,0.002066001,0.01325392,0.003084644,0.003987174,0.002233209,0.0006695613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05604803,"about_ca_system_score_gemma":0.0387411,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9416411,"about_ca_topic_score_gemma":0.9828475,"domain_scores_codex":[0.9990671,0.0002465589,0.000008613378,0.00007972673,0.0001070776,0.0004909501],"domain_scores_gemma":[0.9994387,0.0001343019,0.00003589356,0.00003478402,0.00007771833,0.0002786884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00007410945,0.00007212436,0.002896794,0.0001006616,0.00002336909,0.003210471,0.04738621,0.003139265,0.000952073,0.8601425,0.04159221,0.04041037],"study_design_scores_gemma":[0.00006232823,0.00005925254,0.008226316,0.0001949011,0.00004091641,0.0003799821,0.0516983,0.001789117,0.0005717663,0.04641026,0.8904708,0.00009602854],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1040607,0.005680945,0.002416275,0.0223967,0.0002261545,0.0001459638,0.0001229532,0.0001003664,0.86485],"genre_scores_gemma":[0.7561463,0.002402005,0.002048691,0.001601168,0.00007055011,0.00007074833,0.00004409813,0.00008142384,0.2375349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05835891,"threshold_uncertainty_score":0.4066588,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09561163722397215,"score_gpt":0.289486047070099,"score_spread":0.1938744098461269,"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."}}