{"id":"W3108699229","doi":"10.1121/1.5147765","title":"Developing a cross-platform federated code repository for speech research","year":2020,"lang":"en","type":"article","venue":"The Journal of the Acoustical Society of America","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Documentation; Scripting language; Python (programming language); Code (set theory); World Wide Web; Point (geometry); Open research; Open science; Source code; Data science; Process (computing); Open source; Set (abstract data type); Programming language; Software","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1154075,0.001921306,0.00255715,0.01787832,0.004282684,0.01457558,0.01055142,0.003378169,0.01952424],"category_scores_gemma":[0.2552799,0.002560508,0.003460579,0.009478162,0.003389638,0.02132701,0.02011354,0.008034286,0.03059598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003921259,"about_ca_system_score_gemma":0.02662215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002902271,"about_ca_topic_score_gemma":0.003495346,"domain_scores_codex":[0.9370739,0.02119792,0.009777172,0.007500552,0.02224903,0.002201425],"domain_scores_gemma":[0.5584721,0.06509582,0.02031206,0.1752082,0.1606291,0.02028278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009124146,0.001154689,0.008339965,0.001693191,0.0003292753,0.001461547,0.005512444,0.006187749,0.01572607,0.04491965,0.2470478,0.6667152],"study_design_scores_gemma":[0.0005140744,0.000975411,0.005320777,0.002865084,0.000256304,0.001831777,0.002035115,0.06808873,0.0516965,0.05375765,0.811841,0.0008175464],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008224231,0.0005374274,0.8200924,0.005164615,0.002000478,0.002859526,0.004575689,0.1464173,0.01012829],"genre_scores_gemma":[0.02970749,0.0005856264,0.8727236,0.001349187,0.0006846056,0.002821096,0.02364741,0.04930021,0.01918065],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1154075,"threshold_uncertainty_score":0.6103404,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1147673965792893,"score_gpt":0.3587112357129718,"score_spread":0.2439438391336825,"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."}}