{"id":"W6906628046","doi":"10.17632/bk45c9yxb9","title":"CRICVA Database","year":2019,"lang":"en","type":"dataset","venue":"Mendeley Data","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pixel; Eye tracking; Image processing; Fixation (population genetics); Tracking (education); Notice","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science","insufficient_payload"],"consensus_categories":["open_science","insufficient_payload"],"category_scores_codex":[0.001636518,0.0009109962,0.0009498135,0.0005096257,0.0001276682,0.0002598313,0.01210756,0.000472129,0.01111112],"category_scores_gemma":[0.0009159832,0.0008798051,0.0000829237,0.0005876932,0.0001227997,0.001336045,0.01231695,0.001425485,0.3683471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002195038,"about_ca_system_score_gemma":0.0005865614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001638253,"about_ca_topic_score_gemma":0.0009300594,"domain_scores_codex":[0.9938666,0.0003133599,0.0007347021,0.002577768,0.001469337,0.00103826],"domain_scores_gemma":[0.9704664,0.0002096466,0.0005507555,0.02834883,0.0001056062,0.0003187677],"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":[0.00005339192,0.0002415276,0.000002272513,0.0003733717,0.0002139759,0.0001935019,0.000002658183,0.000001610508,0.00006419217,0.000006227947,0.9986365,0.0002107121],"study_design_scores_gemma":[0.0006616648,0.00004017324,0.000003304234,0.0002201431,0.0005593403,0.00005459342,0.00001645449,0.0001806442,0.0000136463,0.000009912117,0.9972278,0.001012253],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[9.283842e-7,0.001066893,0.00002677134,0.00006780824,0.001835022,0.0007862456,0.9955003,0.0001858004,0.0005302565],"genre_scores_gemma":[7.057633e-7,0.0007432356,0.0006592128,0.0005101535,0.0009110652,0.00003305282,0.9957147,0.0002450324,0.001182799],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.357236,"threshold_uncertainty_score":0.9993653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2202930564974461,"score_gpt":0.3882515971809712,"score_spread":0.1679585406835251,"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."}}