{"id":"W2335570229","doi":"10.1177/154193120204601708","title":"Judgments of 3D Bars in Depth","year":2002,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Data Visualization and Analytics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Scaling; Bar (unit); Statistics; Mathematics; Approximation error; Geometry; Apparent Size; Physics; Psychology; Cognitive psychology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00198925,0.0006850606,0.0004019038,0.0007730022,0.0003269556,0.0008665435,0.0003825159,0.001092883,0.003570774],"category_scores_gemma":[0.03440337,0.0004445471,0.0004272947,0.0002727193,0.0004949268,0.001211514,0.001223046,0.0004087827,0.0005849244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002994718,"about_ca_system_score_gemma":0.0002338723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002164683,"about_ca_topic_score_gemma":0.00292008,"domain_scores_codex":[0.9984011,0.0004993757,0.0001131882,0.0003526499,0.0005217834,0.0001119137],"domain_scores_gemma":[0.9840751,0.008347169,0.002875452,0.001224035,0.002887342,0.0005909897],"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":[0.005202037,0.0003421812,0.2554498,0.0009626193,0.0003419502,0.001387375,0.02950995,0.00983651,0.5004717,0.001987821,0.00182045,0.1926877],"study_design_scores_gemma":[0.0004931455,0.004438014,0.8265865,0.0002039807,0.0002929838,0.002187307,0.01692985,0.05471716,0.07354902,0.007006145,0.01309283,0.0005029756],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894716,0.0001507901,0.008805448,0.00004346093,0.00001589052,0.00004491482,0.000126379,0.000114629,0.001226862],"genre_scores_gemma":[0.990912,0.00005755981,0.0083188,0.0000398501,0.000006615739,0.00003863886,0.00008579095,0.00002408903,0.0005166916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003570774,"threshold_uncertainty_score":0.01194543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02820221458998811,"score_gpt":0.2512582793017291,"score_spread":0.223056064711741,"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."}}