{"id":"W6931496671","doi":"10.5281/zenodo.7003405","title":"Liopterus haemorrhoidalis","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Instar; Margin (machine learning); Table (database); Seta; Head and neck","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":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005383707,0.00009099588,0.00009547365,0.0002646278,0.003361439,0.0005186159,0.002551493,0.00002606593,0.004854028],"category_scores_gemma":[0.0001545096,0.0001028707,0.00004074727,0.0007999539,0.00008766151,0.0001977968,0.003868031,0.0003331112,0.002661841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000126406,"about_ca_system_score_gemma":0.000002918822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001091679,"about_ca_topic_score_gemma":6.327241e-8,"domain_scores_codex":[0.9985604,0.0002705829,0.0001453347,0.0003985173,0.0003209422,0.0003042454],"domain_scores_gemma":[0.9990631,0.0000157503,0.0000701141,0.0006006222,0.0001676483,0.00008278075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001538018,0.000210591,0.00000986212,0.00001423913,0.00002671803,0.00008954699,0.001024254,0.0001944533,0.003404675,0.1494025,0.2209922,0.6246157],"study_design_scores_gemma":[0.0002196331,0.0002188366,0.0004802768,0.000002744398,0.000002621949,0.0003087323,0.000113309,0.001865588,0.0004753102,0.001121913,0.9950648,0.0001262218],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06879964,0.0002945244,0.4752354,0.01708102,0.0009638958,0.0008306358,0.0003113152,0.01367937,0.4228042],"genre_scores_gemma":[0.9960107,0.000007578027,0.002246382,0.0002981937,0.00004316573,6.562816e-8,0.0001703456,0.0003929934,0.0008305719],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.927211,"threshold_uncertainty_score":0.9981147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03224118539328549,"score_gpt":0.233640262156411,"score_spread":0.2013990767631255,"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."}}