{"id":"W2563817626","doi":"","title":"Investigating Memory for Spatial and Temporal Relations with Eye Movement Monitoring","year":2012,"lang":"en","type":"dissertation","venue":"Library and Archives Canada (Government of Canada)","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Movement (music); Eye movement; Cartography; Cognitive psychology; Computer science; Geography; Psychology; Artificial intelligence; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00001398293,0.0002006323,0.0002276466,0.00003677399,0.0002462075,0.0000352284,0.0002419132,0.00005086086,0.000001757962],"category_scores_gemma":[0.000004544509,0.0001862284,0.00001650101,0.00006080105,0.00005077373,0.0003267346,0.00007752119,0.0001770443,7.111027e-10],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008332623,"about_ca_system_score_gemma":0.0009871916,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003776836,"about_ca_topic_score_gemma":0.03248496,"domain_scores_codex":[0.9984865,0.00002401978,0.0002308755,0.0002865607,0.0007196897,0.0002524224],"domain_scores_gemma":[0.999239,0.0001493953,0.0002681931,0.0001841801,0.000001397909,0.0001578076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001649378,0.00005332958,0.7238109,0.0008845853,0.0002549048,0.00002586816,0.0008714434,0.00006465167,0.0185854,0.1457388,0.0003260144,0.1092193],"study_design_scores_gemma":[0.0005098946,0.0001624196,0.8815411,0.000544227,0.00005428642,0.000002297849,0.002844253,0.003075177,0.105481,0.00367325,0.00162385,0.0004881368],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9311,0.001057197,0.009722526,0.0040402,0.001096963,0.0007747976,0.0001668329,0.00009439356,0.0519471],"genre_scores_gemma":[0.9730749,0.00001362159,0.020918,0.00009692299,0.00007069466,0.00003410858,0.00002772547,0.00001855819,0.0057455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1577303,"threshold_uncertainty_score":0.9851696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005851364214656708,"score_gpt":0.1739026024142401,"score_spread":0.1680512381995834,"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."}}