{"id":"W2913799641","doi":"10.1561/1100000041","title":"Exertion Games","year":2016,"lang":"en","type":"article","venue":"Foundations and Trends® in Human–Computer Interaction","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Perspective (graphical); Exertion; Human–computer interaction; Computer science; Context (archaeology); Work (physics); Engineering; Artificial intelligence; Physical therapy; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.0001882223,0.0001921838,0.00017012,0.001386745,0.0002480365,0.00025838,0.0003083786,0.0001062777,0.000253059],"category_scores_gemma":[0.00001659842,0.000154769,0.00005564294,0.0006165248,0.00009263671,0.002670655,0.0001872857,0.0002196538,0.0001012006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002361596,"about_ca_system_score_gemma":0.0000106629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005703058,"about_ca_topic_score_gemma":0.0001618548,"domain_scores_codex":[0.9985371,0.00008105567,0.0004331367,0.0005470956,0.0001509215,0.0002506494],"domain_scores_gemma":[0.9990924,0.0001083925,0.0002037407,0.0004134818,0.0001456467,0.00003636094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001038704,0.0001452107,0.001471126,0.000005073807,0.00002792885,0.000008661824,0.0004576606,0.00001808393,0.007228443,0.2225929,0.001646023,0.7663885],"study_design_scores_gemma":[0.00645321,0.001771867,0.5939608,0.001124041,0.00005649864,0.0008716426,0.0002590239,0.06433728,0.03091583,0.1232177,0.1746342,0.0023979],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.329699,0.00001322379,0.6623926,0.00295795,0.001614065,0.0001091307,0.000002228612,0.0003379837,0.002873881],"genre_scores_gemma":[0.9908876,0.000009550872,0.007564205,0.0001341008,0.0001964727,0.00005712597,0.00002103764,0.00001217672,0.001117731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7639906,"threshold_uncertainty_score":0.6311297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03347544928296987,"score_gpt":0.3268492114647387,"score_spread":0.2933737621817689,"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."}}