{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001675193,0.0005651876,0.0003024216,0.001072671,0.002052213,0.003489655,0.001239428,0.002097252,0.01014493],"category_scores_gemma":[0.003714753,0.0001857787,0.0005608575,0.0007045356,0.01569891,0.003774985,0.002349248,0.001959943,0.001243862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00250669,"about_ca_system_score_gemma":0.001086723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003746567,"about_ca_topic_score_gemma":0.00165203,"domain_scores_codex":[0.9984642,0.0007924754,0.00004660458,0.0003353829,0.0002363737,0.0001248779],"domain_scores_gemma":[0.9983737,0.0009043019,0.0001193603,0.0002353601,0.0002337186,0.0001334581],"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":[0.000006863701,0.00001670927,0.0006467525,0.00004145295,0.000006582489,0.00005729756,0.002803138,0.000568767,0.0001361424,0.9839535,0.001965826,0.009796991],"study_design_scores_gemma":[0.00001138355,0.00003085128,0.001584148,0.00007280902,0.00001154151,0.0001772609,0.001501824,0.001909019,0.0001912824,0.9353404,0.05915231,0.00001708271],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04728372,0.004017637,0.16388,0.02887107,0.0004980569,0.0001696513,0.0002551156,0.0002403171,0.7547844],"genre_scores_gemma":[0.919886,0.002021261,0.03303578,0.003821845,0.0003023458,0.0004318362,0.0001495342,0.00009744864,0.04025399],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01014493,"threshold_uncertainty_score":0.03393811,"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."}}