{"id":"W6950458897","doi":"10.5683/sp2/5t2rd9","title":"RGB-D Tongue State Classification Dataset","year":2019,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Tongue; Annotation; Pattern recognition (psychology); State (computer science); Tip of the tongue","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006419615,0.0006491571,0.0006525617,0.0004428783,0.00009950751,0.0002937751,0.001579406,0.0004770969,0.0006194701],"category_scores_gemma":[0.0002688169,0.0006341577,0.0001251924,0.0003577014,0.0001486436,0.0004443461,0.0003279799,0.0006843,0.02424844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003616716,"about_ca_system_score_gemma":0.0003524525,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.08208791,"about_ca_topic_score_gemma":0.04544261,"domain_scores_codex":[0.9963995,0.0002750024,0.000676939,0.00105468,0.0009370908,0.0006568151],"domain_scores_gemma":[0.9938312,0.000132274,0.000790015,0.004830227,0.0001697067,0.000246635],"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":[0.00006897518,0.0001262056,0.000004157598,0.0001551509,0.0001160349,0.00004342925,0.00001330003,0.000008720721,0.00006598555,0.00001641166,0.9990473,0.000334345],"study_design_scores_gemma":[0.0004193359,0.00004830654,0.001074182,0.00007303865,0.0002321508,0.0000152514,0.00002403096,0.00003966032,0.00003098077,0.00003433332,0.9972917,0.0007169562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000001518378,0.0001076942,0.000006270099,0.00009806776,0.0003346648,0.000812593,0.9980217,0.0001315267,0.0004859361],"genre_scores_gemma":[0.00000114247,0.0003694332,0.00005827742,0.000389692,0.0003471392,0.0001169078,0.998389,0.0001781424,0.0001502435],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0366453,"threshold_uncertainty_score":0.999611,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06303706101234073,"score_gpt":0.3295795156528261,"score_spread":0.2665424546404854,"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."}}