{"id":"W2076648340","doi":"10.3138/carto.44.1.33","title":"The Effect of Global-Scale Map-Projection Knowledge on Perceived Land Area","year":2009,"lang":"en","type":"article","venue":"Cartographica The International Journal for Geographic Information and Geovisualization","topic":"Historical Geography and Cartography","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mercator projection; Projection (relational algebra); Cognitive map; Scale (ratio); Perception; Map projection; Cartography; Distortion (music); Conceptualization; Cognition; Computer science; Orthographic projection; Geography; Artificial intelligence; Psychology; Algorithm","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.002032486,0.0001711567,0.0001710818,0.0003861603,0.002161396,0.0004435972,0.0004651959,0.0001405202,0.00001051416],"category_scores_gemma":[0.0002737368,0.000103804,0.0004061816,0.001022452,0.0004231817,0.0005524531,0.0000198991,0.0002006184,0.000002456864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005743512,"about_ca_system_score_gemma":0.00006351083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001565663,"about_ca_topic_score_gemma":0.0004864112,"domain_scores_codex":[0.9980671,0.0002853652,0.0005245403,0.0001262916,0.0007208952,0.0002757689],"domain_scores_gemma":[0.9980158,0.0003928076,0.0004114945,0.0001421116,0.0009131267,0.0001247092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002906144,0.0002399712,0.2988528,0.00006988127,0.0006906377,0.000001545659,0.02039045,0.0002972001,0.00009145927,0.2622181,0.01861609,0.3956257],"study_design_scores_gemma":[0.002549136,0.002120856,0.1454161,0.000158434,0.0001958337,0.00002931439,0.003538523,0.001127406,0.00006717601,0.0184039,0.8260064,0.0003869455],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9476132,0.002219184,0.00889604,0.01262433,0.008056724,0.002259473,0.000129183,0.0002098812,0.01799197],"genre_scores_gemma":[0.9970102,0.00212206,0.00002035343,0.0004058545,0.0002948849,0.00003719535,0.00004948474,0.00000450574,0.00005540055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8073903,"threshold_uncertainty_score":0.9991376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007659579702086525,"score_gpt":0.3048066322192146,"score_spread":0.2971470525171281,"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."}}