{"id":"W3164603418","doi":"10.31234/osf.io/rzd6v","title":"MAD saccade: statistically robust saccade threshold estimation","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Saccade; Standard deviation; Estimator; Computer science; Outlier; Artificial intelligence; Gaze; False positive paradox; Pattern recognition (psychology); Mathematics; Computer vision; Algorithm; Eye movement; Statistics","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":[0.001849692,0.0008994926,0.001076905,0.002961454,0.0005004237,0.00143707,0.001736085,0.00103068,0.003939928],"category_scores_gemma":[0.01401424,0.0005069567,0.0009066482,0.001383862,0.000416722,0.001054215,0.001286637,0.001091354,0.001906424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006573601,"about_ca_system_score_gemma":0.001035314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003444529,"about_ca_topic_score_gemma":0.003892986,"domain_scores_codex":[0.9986473,0.0002355798,0.0001416944,0.0004214751,0.000439498,0.000114549],"domain_scores_gemma":[0.9964893,0.001383607,0.0005504875,0.0006817224,0.0007800083,0.0001149731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001363355,0.0002162378,0.01961704,0.0004674224,0.0005655391,0.0003208313,0.0002815413,0.04508338,0.06605483,0.009336105,0.02223041,0.8344632],"study_design_scores_gemma":[0.000124191,0.000545561,0.02498622,0.00008554127,0.0001302746,0.0009019816,0.0001478816,0.8639921,0.0775023,0.01299101,0.01839259,0.0002003332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03157761,0.001245762,0.9467644,0.0001802928,0.0002053015,0.0001698702,0.001611446,0.01695495,0.001290407],"genre_scores_gemma":[0.3391401,0.0003599563,0.6511749,0.0002400669,0.0001584563,0.000411501,0.003754753,0.001409336,0.003350968],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003939928,"threshold_uncertainty_score":0.01318038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03211086929901479,"score_gpt":0.2752813321536318,"score_spread":0.243170462854617,"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."}}