{"id":"W4281681607","doi":"10.24908/iee.2022.15.2.e","title":"Screen adaptation theory for humans","year":2022,"lang":"en","type":"article","venue":"Ideas in Ecology and Evolution","topic":"Media Influence and Health","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adaptation (eye); Leverage (statistics); Computer science; Psychology; Cognitive science; Cognitive psychology; Artificial intelligence; Neuroscience","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005888682,0.00004299756,0.0000783518,0.00009477812,0.0006391274,0.000008442408,0.00004325897,0.00002511973,0.0006656351],"category_scores_gemma":[0.00004953632,0.00004426257,0.00001642404,0.00001729162,0.0001017694,0.00009223276,0.00002124105,0.0001002663,0.000009088852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008223199,"about_ca_system_score_gemma":0.00005128932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000317365,"about_ca_topic_score_gemma":0.01034997,"domain_scores_codex":[0.9994758,0.00009523703,0.0001298764,0.0001086022,0.00004556456,0.0001449277],"domain_scores_gemma":[0.999725,0.0001392752,0.00004456128,0.00004848613,0.00002354583,0.00001905904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008125907,0.0000289957,0.01821065,0.00001217828,0.000004139369,6.65732e-7,0.01097286,0.0001838888,0.000002880955,0.9681741,0.001180734,0.001147653],"study_design_scores_gemma":[0.0007061243,0.0004479056,0.2234123,0.000005257569,0.00001436351,0.000002471466,0.01699413,0.001586725,5.950869e-7,0.6855715,0.07115417,0.0001044192],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9912877,0.0003874819,0.0004232855,0.0007687983,0.0007021592,0.0003420712,0.00003812775,0.00002560481,0.006024783],"genre_scores_gemma":[0.9975882,0.00001509458,0.00005883704,0.0007002645,0.0001828543,0.000235519,0.00003221842,0.000004246062,0.001182834],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2826026,"threshold_uncertainty_score":0.7288238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0395201690865812,"score_gpt":0.2695129795004634,"score_spread":0.2299928104138822,"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."}}