{"id":"W2955124896","doi":"10.3390/ijerph16132275","title":"Methodology to Derive Objective Screen-State from Smartphones: A SMART Platform Study","year":2019,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Impact of Technology on Adolescents","field":"Social Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; University of Regina","funders":"Saskatchewan Health Research Foundation","keywords":"Screen time; Mobile device; Context (archaeology); Computer science; Entertainment; Population; Sample (material); State (computer science); Human–computer interaction; Internet privacy; World Wide Web; Medicine; Physical activity; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006117077,0.0000996747,0.0002542672,0.0005525652,0.000284384,0.0001559041,0.0007324993,0.00007641735,0.0005826449],"category_scores_gemma":[0.0009914292,0.00008984762,0.00004743677,0.0001835627,0.0003591246,0.0004798988,0.0003155899,0.0006314266,0.0001281428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001136663,"about_ca_system_score_gemma":0.0006402252,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008450202,"about_ca_topic_score_gemma":0.00291392,"domain_scores_codex":[0.9961919,0.0009497408,0.0004082133,0.0002278638,0.001629361,0.0005929146],"domain_scores_gemma":[0.9981818,0.0006456057,0.0002247144,0.000131521,0.0001509397,0.0006653821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007420587,0.002232263,0.77893,0.000003321852,0.0004150577,0.0001037324,0.03679858,0.000001933113,0.0008145581,0.0005488914,0.001280897,0.1781287],"study_design_scores_gemma":[0.001858252,0.002948412,0.8767244,0.00004539947,0.000002389566,0.00002814307,0.09613864,0.000005084761,0.00009898034,0.005111932,0.01691239,0.0001260384],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818437,0.0001446032,0.0003439649,0.01582584,0.0004838488,0.0005158487,0.00006891492,0.000009711827,0.0007636277],"genre_scores_gemma":[0.9968433,0.0004711694,0.001173475,0.0009324852,0.0001543546,0.000004684704,0.000004929434,0.00001057339,0.0004050356],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1780027,"threshold_uncertainty_score":0.9981526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1509204761275483,"score_gpt":0.4578016728801314,"score_spread":0.3068811967525831,"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."}}