{"id":"W4399189282","doi":"10.1002/cjas.1755","title":"Généralisation de l'usage du Big Data en finance de marché, entre mythes et réalités: Une approche par le travail institutionnel","year":2024,"lang":"fr","type":"article","venue":"Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration","topic":"FinTech, Crowdfunding, Digital Finance","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Political science; Humanities; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01317601,0.0006508029,0.000756506,0.007160788,0.001710886,0.01259656,0.001499597,0.001824503,0.004125018],"category_scores_gemma":[0.04698032,0.0005984395,0.001325542,0.01220743,0.003614574,0.01115742,0.00357656,0.002602014,0.001017037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004397337,"about_ca_system_score_gemma":0.003782433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02604464,"about_ca_topic_score_gemma":0.02814461,"domain_scores_codex":[0.9903778,0.004871236,0.0008150634,0.001261423,0.002391778,0.0002825885],"domain_scores_gemma":[0.9643107,0.02084155,0.001829962,0.006409447,0.005985656,0.0006226728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005140349,0.0001405324,0.06419502,0.001785802,0.0004626185,0.001022582,0.01910478,0.03229441,0.005824054,0.3049937,0.03191598,0.5377465],"study_design_scores_gemma":[0.00005739314,0.0001135132,0.03393258,0.002248105,0.000228252,0.001056365,0.01637158,0.1373349,0.00872884,0.3027956,0.4969052,0.0002276861],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1359638,0.01005983,0.7385749,0.04716457,0.001344601,0.0005374184,0.007086576,0.003231229,0.05603706],"genre_scores_gemma":[0.5955284,0.005716725,0.3793581,0.002479737,0.0005518354,0.0004140603,0.004899374,0.0006012822,0.01045053],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02604464,"threshold_uncertainty_score":0.06968224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1237417892889591,"score_gpt":0.2977546340589898,"score_spread":0.1740128447700307,"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."}}