{"id":"W2007214990","doi":"10.1167/10.7.975","title":"The Visual Perception of Correlation in Scatterplots","year":2010,"lang":"en","type":"article","venue":"Journal of Vision","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Correlation; Mathematics; Standard deviation; Statistics; Range (aeronautics); Set (abstract data type); Pattern recognition (psychology); Artificial intelligence; Computer science; Geometry; Materials science","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":[],"consensus_categories":[],"category_scores_codex":[0.0008995111,0.00003181514,0.00009366684,0.00001251484,0.00005818943,0.00001786725,0.00007624692,0.00003983327,0.0001374456],"category_scores_gemma":[0.000302745,0.000008396058,0.00006315126,0.0001344677,0.00003544482,0.00006904193,0.000009028863,0.0001591845,0.000002931622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006957005,"about_ca_system_score_gemma":0.000003145306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001811684,"about_ca_topic_score_gemma":0.0001010433,"domain_scores_codex":[0.9993368,0.0001210514,0.0002831492,0.00004149004,0.0001620359,0.00005544853],"domain_scores_gemma":[0.9990954,0.0005750092,0.0001932864,0.00001606856,0.00009248657,0.00002773946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000369845,0.00003001564,0.008695589,4.874188e-7,0.000001683105,7.512693e-7,0.00002250287,0.00001299468,0.6478828,0.0001170167,0.00004658578,0.3431526],"study_design_scores_gemma":[0.00006083136,0.0003030954,0.993899,0.00001383547,0.000006487628,0.000007025306,0.0001907057,0.003204285,0.0004633819,0.001147733,0.0006806491,0.00002294138],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989243,0.00001544033,0.000235282,0.0005532663,0.0001694904,0.00001972533,6.439603e-7,9.965381e-7,0.00008083926],"genre_scores_gemma":[0.9988456,0.00002855677,0.0009628127,0.00002222109,0.000117402,1.161597e-7,7.231295e-7,1.940024e-7,0.00002238997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9852034,"threshold_uncertainty_score":0.1504933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01816543249818752,"score_gpt":0.3368255429952132,"score_spread":0.3186601104970257,"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."}}