{"id":"W4393459169","doi":"10.5281/zenodo.7504829","title":"Pupillary dynamics reflect the impact of temporal expectation on detection strategy - data","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Opinion Dynamics and Social Influence","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Laboratory for Brain, Music and Sound Research","funders":"","keywords":"Dynamics (music); Computer science; Econometrics; Artificial intelligence; Mathematics; Physics; Acoustics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000530648,0.0002054956,0.0002125193,0.0001853748,0.001290419,0.0004807445,0.001650593,0.00009927887,0.001326189],"category_scores_gemma":[0.0001258534,0.0001701386,0.0001088413,0.0005891914,0.0001379946,0.0001825107,0.001027343,0.0005038336,0.002313568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001810016,"about_ca_system_score_gemma":0.00001969071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00252152,"about_ca_topic_score_gemma":0.00001598746,"domain_scores_codex":[0.9982877,0.0003345674,0.0003313315,0.0004255778,0.0003574876,0.0002632949],"domain_scores_gemma":[0.9981173,0.00005235111,0.0003448751,0.001078864,0.0003282543,0.00007838698],"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":[0.00004148218,0.00009878063,0.000003465432,0.00002971984,0.000138716,0.000001769788,0.00007555341,0.000639263,0.00004285204,0.0005347003,0.9793963,0.01899737],"study_design_scores_gemma":[0.0004263033,0.0008229428,0.001108371,0.00009195749,0.00005604677,0.000005967368,0.0008882695,0.01213782,0.00001790117,0.0008626112,0.983169,0.0004128018],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002261939,0.00001003281,0.0005208894,0.00005778424,0.0001569751,0.0004029329,0.9932614,0.000129832,0.003198232],"genre_scores_gemma":[0.09407227,0.00004866984,0.000004716803,0.000007198373,0.0002702234,8.180714e-8,0.9050301,0.0004757682,0.00009098335],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09181033,"threshold_uncertainty_score":0.9995868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06648286238104817,"score_gpt":0.342809376285905,"score_spread":0.2763265139048569,"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."}}