{"id":"W2107908575","doi":"10.1037/0278-7393.32.3.333","title":"Global-scale location and distance estimates: Common representations and strategies in absolute and relative judgments.","year":2006,"lang":"en","type":"article","venue":"Journal of Experimental Psychology Learning Memory and Cognition","topic":"Spatial Cognition and Navigation","field":"Engineering","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Latitude; Pairwise comparison; Scale (ratio); Multidimensional scaling; Equator; Scaling; Geography; Geographic coordinate system; Frequency; Geographical distance; Representation (politics); Distance decay; Artifact (error); Mathematics; Statistics; Geodesy; Economic geography; Cartography; Computer science; Sociology; Demography; Geometry; Population; Law; Artificial intelligence; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004435109,0.000408817,0.0002813819,0.00137348,0.0003245692,0.003092562,0.0006592718,0.001044375,0.002051058],"category_scores_gemma":[0.06410569,0.0003346044,0.0004270615,0.001111914,0.002019544,0.005072085,0.001447687,0.0008575693,0.0002615773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005305345,"about_ca_system_score_gemma":0.0003913577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00104504,"about_ca_topic_score_gemma":0.00101252,"domain_scores_codex":[0.9977815,0.0009092716,0.0001658683,0.0004868579,0.0005538619,0.0001027577],"domain_scores_gemma":[0.9766178,0.01550784,0.003285789,0.002292357,0.001849429,0.0004467605],"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":[0.001473377,0.000342337,0.1505243,0.0008451613,0.0005725113,0.0007567968,0.08154416,0.006408054,0.02930712,0.2517921,0.003184283,0.4732499],"study_design_scores_gemma":[0.0003902462,0.001345357,0.2978972,0.0006197656,0.0008274736,0.003315893,0.04095446,0.09185335,0.0259723,0.499722,0.03659348,0.0005083949],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8131654,0.001213917,0.1538564,0.001276114,0.0001198278,0.00009836392,0.0001858234,0.0002038012,0.02988037],"genre_scores_gemma":[0.9841958,0.0001144942,0.01477441,0.0000879217,0.00001333726,0.00003114125,0.00004956838,0.0000197169,0.0007135568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004435109,"threshold_uncertainty_score":0.02345538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01275559115684595,"score_gpt":0.3129479435468294,"score_spread":0.3001923523899835,"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."}}