{"id":"W4320724334","doi":"10.32920/22094348.v1","title":"Algorithms, Platforms, and Policy: The Changing Face of Canadian News Distribution","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Hungarian Social, Economic and Educational Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gatekeeping; Journalism; Distribution (mathematics); Social media; Face (sociological concept); Government (linguistics); Political science; Proxy (statistics); News media; Business; Advertising; Computer science; Sociology; Law","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":[0.02308102,0.0005376614,0.0007710279,0.007411769,0.02615231,0.03299631,0.003372751,0.004123203,0.009084329],"category_scores_gemma":[0.06663746,0.0007378595,0.0006205069,0.01263892,0.01851534,0.009622577,0.004572123,0.005664612,0.001003418],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.2950566,"about_ca_system_score_gemma":0.3038925,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9924313,"about_ca_topic_score_gemma":0.989744,"domain_scores_codex":[0.9769841,0.003594337,0.0006030083,0.001942906,0.0127377,0.004137917],"domain_scores_gemma":[0.9280341,0.02046664,0.001917608,0.003091062,0.03870368,0.007786961],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001203894,0.00004202692,0.006534385,0.0002395141,0.0000367372,0.0001923755,0.01243962,0.00258016,0.0005929055,0.7539718,0.1101594,0.1130908],"study_design_scores_gemma":[0.00007066708,0.00003070626,0.01876559,0.0005358524,0.00005318322,0.0001075936,0.01820053,0.005160122,0.001489236,0.06116729,0.8941869,0.0002322562],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0841032,0.01588992,0.009719316,0.5648569,0.001373377,0.0001750394,0.002251209,0.0004889221,0.3211421],"genre_scores_gemma":[0.8507885,0.01773985,0.01950907,0.02727922,0.0009286121,0.0001357411,0.001469834,0.0007727771,0.08137634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2950566,"threshold_uncertainty_score":0.8176345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08404831891580153,"score_gpt":0.334840924087082,"score_spread":0.2507926051712804,"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."}}