{"id":"W4393981161","doi":"10.25144/16085","title":"THE CONTRIBUTION OF AUTOMATIC SPEECH RECOGNITION FOR KEYWORDS TO ASSIST IN THE INTEGRATED ORGANISATION OF DIGITAL MESSAGES","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kwantlen Polytechnic University","funders":"","keywords":"Computer science; Speech recognition; Natural language processing","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":[0.001115165,0.0008467808,0.00049828,0.001530671,0.0003173505,0.001687021,0.0006448947,0.0009919646,0.004129036],"category_scores_gemma":[0.003789745,0.0002457429,0.0004172384,0.000644172,0.0003789808,0.001384441,0.000408479,0.0007278378,0.004671961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002634161,"about_ca_system_score_gemma":0.0006149064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002554975,"about_ca_topic_score_gemma":0.002369234,"domain_scores_codex":[0.9991308,0.0002847138,0.00006591631,0.0002076485,0.0002374331,0.00007361726],"domain_scores_gemma":[0.9965403,0.0018938,0.0001221463,0.0002900848,0.00105798,0.00009571895],"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":[0.0005241826,0.0001583116,0.002398665,0.0003036033,0.00006447338,0.0001514468,0.0001680317,0.002717444,0.2266001,0.001758653,0.005003907,0.7601511],"study_design_scores_gemma":[0.0000898943,0.0009569175,0.01544498,0.0001779698,0.000361753,0.00142198,0.0005875371,0.5088978,0.4135404,0.007791382,0.05055277,0.000176601],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.215043,0.01128573,0.7389619,0.002646123,0.002361875,0.0003082624,0.002041445,0.008286199,0.0190655],"genre_scores_gemma":[0.5546114,0.00344879,0.4190189,0.0007404689,0.0008947686,0.0001051893,0.00230699,0.000585111,0.01828842],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004129036,"threshold_uncertainty_score":0.01381296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02200570484138726,"score_gpt":0.3041059391850769,"score_spread":0.2821002343436896,"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."}}