{"id":"W2064468319","doi":"10.1177/154193120204602103","title":"Human-Computer Interaction as Cognitive Science","year":2002,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cognition; Cognitive science; Computer science; Human–computer interaction; Data science; Psychology; Neuroscience","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":[0.0003763969,0.0001477099,0.0001587091,0.00005883953,0.0009438497,0.0004212672,0.0007473594,0.00005082242,0.000009240628],"category_scores_gemma":[0.00006703711,0.0001141071,0.00011767,0.0003408464,0.0003460612,0.001431972,0.0007511269,0.0001649613,0.000003401403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005564866,"about_ca_system_score_gemma":0.00001326219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003292757,"about_ca_topic_score_gemma":0.000001057693,"domain_scores_codex":[0.9989084,0.000005180344,0.0002712791,0.000359174,0.0002208577,0.0002351257],"domain_scores_gemma":[0.9991528,0.00003603909,0.0003183368,0.00009452443,0.0003178833,0.00008039679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001459738,0.0008294923,0.1091273,0.0004943807,0.0003457398,5.954067e-7,0.2204386,0.0001602862,0.07889228,0.5551231,0.02391423,0.0106594],"study_design_scores_gemma":[0.003460072,0.001257596,0.1271322,0.002273055,0.0002920585,0.0000588833,0.08983815,0.532402,0.2199195,0.01217512,0.007891289,0.003300076],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965528,0.00001833571,0.00050239,0.00008925042,0.0001613532,0.00008906753,0.00000708593,0.00005395643,0.002525765],"genre_scores_gemma":[0.9982862,0.00002099783,0.001174379,0.0002244762,0.0000862974,0.000001529475,0.000001136054,0.000007347541,0.0001976502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5429479,"threshold_uncertainty_score":0.7259424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02824075944019179,"score_gpt":0.2824295005622129,"score_spread":0.2541887411220211,"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."}}