{"id":"W7100160400","doi":"","title":"Toronto) Tutorial on Equalization Map","year":2005,"lang":"en","type":"article","venue":"","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Equalization (audio); Club; Credit card; Front (military)","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003119263,0.00108271,0.0006388358,0.001763176,0.002525808,0.004048812,0.0009684089,0.001050437,0.7917715],"category_scores_gemma":[0.001011031,0.000497446,0.0004355944,0.0032733,0.0004659118,0.00174715,0.001623491,0.001073063,0.5149636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004097136,"about_ca_system_score_gemma":0.007592262,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.206363,"about_ca_topic_score_gemma":0.4954854,"domain_scores_codex":[0.9997515,0.00002047427,0.000009086182,0.00003186764,0.000130564,0.0000565172],"domain_scores_gemma":[0.9993495,0.00003367756,0.00001259333,0.00004993791,0.000299696,0.0002544996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004703371,0.000005678469,0.00005445991,0.00003186771,4.357262e-7,0.00002331096,0.00003333744,0.0000431159,0.00003348366,0.001409014,0.9714671,0.02689341],"study_design_scores_gemma":[0.000001127749,0.000001740832,0.0001998679,0.00002380135,4.024371e-7,0.00001301427,0.00005372,0.00001636887,0.00001244265,0.000214214,0.9994614,0.000001929928],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003298318,0.002399044,0.0008301478,0.002465862,0.002168028,0.00009694033,0.007330484,0.001457143,0.9829224],"genre_scores_gemma":[0.001658975,0.001948006,0.0007480921,0.0003167153,0.0002050519,0.00003022022,0.002995889,0.000354804,0.9917424],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.793637,"threshold_uncertainty_score":0.4103237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02080182508738797,"score_gpt":0.3260479029791745,"score_spread":0.3052460778917865,"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."}}