{"id":"W2095168481","doi":"10.1109/hicss.2010.431","title":"Using Personality Factors to Predict Interface Learning Performance","year":2010,"lang":"en","type":"article","venue":"","topic":"Innovative Teaching and Learning Methods","field":"Psychology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Locus of control; Visualization; Personality; Interface (matter); Computer science; Trait; Psychology; Big Five personality traits; Human–computer interaction; User interface; Cognitive psychology; Applied psychology; Artificial intelligence; Developmental psychology; Social psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001948898,0.0001545291,0.0001644946,0.000120743,0.0002760545,0.00003445671,0.0001901867,0.0001198734,0.00517439],"category_scores_gemma":[0.0004240148,0.0001278839,0.00004633357,0.0002625052,0.00006285733,0.0000776773,0.00006170609,0.00152721,0.0002305486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002982186,"about_ca_system_score_gemma":0.00002081476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000485994,"about_ca_topic_score_gemma":0.000009469888,"domain_scores_codex":[0.9985092,0.0005030161,0.0001891581,0.000319576,0.0001425315,0.0003365737],"domain_scores_gemma":[0.9993518,0.0001678521,0.00007189443,0.0002428558,0.00007600356,0.00008957309],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004920079,0.00005072124,0.9047243,0.00001023437,0.00004077583,0.000001181539,0.02115129,0.0003849885,0.05742726,0.00144734,0.0004647803,0.01424793],"study_design_scores_gemma":[0.0002470302,0.0002316009,0.9253747,0.00002015197,0.00001203785,0.00001798584,0.002810327,0.002817996,0.004171628,0.00001295175,0.06398509,0.000298448],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8615877,0.000004367248,0.06922804,0.00007546752,0.001256488,0.00008401419,9.319132e-7,0.0002206154,0.06754235],"genre_scores_gemma":[0.960828,8.521098e-8,0.0236587,0.0001241847,0.000191699,0.0000036545,0.000002262963,0.0000251874,0.01516625],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09924025,"threshold_uncertainty_score":0.995735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1097026960305915,"score_gpt":0.4376667084872584,"score_spread":0.327964012456667,"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."}}