{"id":"W7015855678","doi":"","title":"U.S. Speaker Session 5: Canada and U.S Approaches to the Movement of People - U.S Speaker","year":2005,"lang":"en","type":"article","venue":"Canada-United States law journal","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Movement (music); Session (web analytics); Speaker recognition; Perception","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":[0.003420049,0.0009039436,0.0005505148,0.001300116,0.02506054,0.007824994,0.001790969,0.01569664,0.06900376],"category_scores_gemma":[0.003584973,0.0005237462,0.000978882,0.001293627,0.002573811,0.002130816,0.00380399,0.01357335,0.007901051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03860571,"about_ca_system_score_gemma":0.07752785,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.88616,"about_ca_topic_score_gemma":0.9638106,"domain_scores_codex":[0.9973006,0.0001768991,0.00004913917,0.0003525975,0.0008876008,0.001233257],"domain_scores_gemma":[0.9978245,0.0002378095,0.00005855711,0.00004891277,0.0008039991,0.001026248],"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":[0.0000414421,0.00002601937,0.0006580547,0.00003740688,0.000007848365,0.0001922861,0.0009953069,0.00008896473,0.0003050451,0.02993663,0.9615641,0.006146967],"study_design_scores_gemma":[0.00002606792,0.0000168545,0.004260212,0.0001492073,0.00002297189,0.00007199094,0.002353054,0.0002021076,0.0003508483,0.002800095,0.989703,0.00004361145],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.01130823,0.01272768,0.002332399,0.4197176,0.04759585,0.000439331,0.004031135,0.0003321606,0.5015156],"genre_scores_gemma":[0.08839613,0.004718058,0.001348525,0.05823594,0.005027474,0.0002616363,0.0009460215,0.0001879092,0.8408784],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.11384,"threshold_uncertainty_score":0.2801053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02294731036194704,"score_gpt":0.2080017902641358,"score_spread":0.1850544799021887,"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."}}