{"id":"W2078642016","doi":"10.3138/carto.44.3.159","title":"fMRI and Human Subjects Research in Cartography","year":2009,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Functional magnetic resonance imaging; Cartography; Perception; Window (computing); Data science; Computer science; Psychology; Geography; Neuroscience; World Wide Web","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":[0.001268417,0.0001339376,0.0001162746,0.001752944,0.0004503589,0.0004843939,0.0001842987,0.0001058859,0.00000861558],"category_scores_gemma":[0.00005801383,0.0001129521,0.00008043929,0.0008632849,0.0001232105,0.0009072044,0.00001956215,0.0003264694,0.000001344536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002555745,"about_ca_system_score_gemma":0.00001547415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003890981,"about_ca_topic_score_gemma":0.0000844235,"domain_scores_codex":[0.9986447,0.000068398,0.0004704435,0.0001009968,0.0004797426,0.0002357013],"domain_scores_gemma":[0.9989659,0.0001004324,0.0000923917,0.00008652897,0.0006629073,0.00009187424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0005391284,0.0002338127,0.1176883,0.000247204,0.0004448003,0.00001539476,0.01098534,0.003701552,0.005132599,0.457923,0.008610893,0.3944781],"study_design_scores_gemma":[0.008852968,0.001214254,0.5289382,0.0006905014,0.000107977,0.0005252481,0.005432392,0.05581149,0.001912748,0.2326525,0.1625965,0.001265208],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883403,0.0006550751,0.005873722,0.002183563,0.0007788428,0.0006140314,0.00002223541,0.0001217539,0.001410433],"genre_scores_gemma":[0.9972045,0.001822717,0.00006609219,0.0005532639,0.0001463829,0.00003330273,0.0001614639,0.000008383856,0.000003922249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4112499,"threshold_uncertainty_score":0.4671022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02384016842379008,"score_gpt":0.3334056111107177,"score_spread":0.3095654426869276,"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."}}