{"id":"W1940972223","doi":"10.1109/icassp.1978.1170469","title":"A phoneme recognition system based on human audition","year":2005,"lang":"en","type":"article","venue":"","topic":"Speech Recognition and Synthesis","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Speech recognition; Artificial intelligence","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":[0.000365466,0.0004432125,0.0008570731,0.0005380613,0.0004318021,0.0006280004,0.0005415396,0.0006819883,0.007533674],"category_scores_gemma":[0.0007614666,0.0003287328,0.0003018824,0.0003063117,0.0001962208,0.0005742909,0.0005180108,0.000428295,0.002993313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001611275,"about_ca_system_score_gemma":0.0005989111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001724659,"about_ca_topic_score_gemma":0.002905519,"domain_scores_codex":[0.9997575,0.00002744714,0.00001828813,0.00007475122,0.00008496206,0.00003718283],"domain_scores_gemma":[0.9994748,0.0001553785,0.0000182456,0.00006979441,0.0002176495,0.00006417021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001043126,0.0000994541,0.002075039,0.000205967,0.00006997449,0.0002443951,0.00006665892,0.000730932,0.6999413,0.0007019838,0.003401273,0.2914198],"study_design_scores_gemma":[0.0003964415,0.001668964,0.04600761,0.0001382012,0.0008016795,0.003033943,0.0001416924,0.1583429,0.7542123,0.002011522,0.03298637,0.000258407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2951995,0.001916843,0.6651239,0.0003214435,0.001185141,0.0005579909,0.001661227,0.02240119,0.01163263],"genre_scores_gemma":[0.6961086,0.0009148446,0.2805385,0.0003842017,0.0002453697,0.0003772408,0.001519265,0.0003899283,0.0195221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007533674,"threshold_uncertainty_score":0.02520263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05221428637379322,"score_gpt":0.2634940145083017,"score_spread":0.2112797281345085,"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."}}