{"id":"W2467984453","doi":"10.20533/ijcdse.2042.6364.2014.0223","title":"Using Effective Stereoscopic Molecular Model Visualizations in Undergraduate Classrooms","year":2014,"lang":"en","type":"article","venue":"International Journal for Cross-Disciplinary Subjects in Education","topic":"Visual and Cognitive Learning Processes","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Algoma University","funders":"","keywords":"Stereoscopy; Computer science; Computer graphics (images); Mathematics education; Human–computer interaction; Psychology; Artificial intelligence","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":[0.0005683189,0.0001903215,0.0001829088,0.0007179386,0.0001903808,0.0003146768,0.0003315243,0.0001295288,0.00006291779],"category_scores_gemma":[0.0002943337,0.0001958628,0.00009982906,0.0003477852,0.00008535559,0.0005701829,0.00005749694,0.000366388,0.0000150036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004370503,"about_ca_system_score_gemma":0.0003855216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003361399,"about_ca_topic_score_gemma":0.00007284274,"domain_scores_codex":[0.9983334,0.0002184141,0.0004772331,0.0003793291,0.0002833061,0.00030834],"domain_scores_gemma":[0.9987952,0.0003073994,0.0002089417,0.000114633,0.0004980621,0.0000757305],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001567625,0.004322829,0.3693157,0.000338364,0.0004075765,0.00008952605,0.02113548,0.2285866,0.004788559,0.1384992,0.0003702234,0.2305782],"study_design_scores_gemma":[0.004385663,0.0007618726,0.2389022,0.002118618,0.00006046609,0.0004331658,0.002850112,0.3806642,0.0008605983,0.3663698,0.001744903,0.0008484533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7771767,0.0004973568,0.21543,0.0004769808,0.004071092,0.0003525963,0.000009838451,0.00002699292,0.00195841],"genre_scores_gemma":[0.9962172,0.00002069115,0.00151364,0.000224685,0.000459224,0.0001799924,0.00007117211,0.00004119159,0.001272223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2297297,"threshold_uncertainty_score":0.7987052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04376032747522749,"score_gpt":0.4851105628423797,"score_spread":0.4413502353671522,"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."}}