{"id":"W2065949300","doi":"10.1021/ed200259j","title":"Identifying Student Use of Ball-and-Stick Images versus Electrostatic Potential Map Images via Eye Tracking","year":2013,"lang":"en","type":"article","venue":"Journal of Chemical Education","topic":"Visual and Cognitive Learning Processes","field":"Psychology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Texas AgriLife Research; National Science Foundation","keywords":"Eye tracking; Ball (mathematics); Equal time; Tracking (education); Hydroxide; Eye movement; Chemistry; Computer vision; Artificial intelligence; Psychology; Computer science; Physics; Mathematics; Inorganic chemistry; Geometry","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":[0.0008244782,0.0003470074,0.0002972154,0.0006052597,0.000204489,0.000839517,0.0002735878,0.0004266422,0.002479551],"category_scores_gemma":[0.00862393,0.000138631,0.0001943949,0.0002741735,0.0001974972,0.0006189688,0.0003843648,0.0003487939,0.0004538751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001598826,"about_ca_system_score_gemma":0.0001901238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001746331,"about_ca_topic_score_gemma":0.003173494,"domain_scores_codex":[0.9992488,0.0001870704,0.00007487096,0.0001554772,0.0002463045,0.00008732191],"domain_scores_gemma":[0.9944576,0.002896488,0.001321215,0.0002939786,0.0008215971,0.0002091692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001239898,0.001092916,0.6770718,0.0003580461,0.0001295421,0.0003475563,0.01659308,0.0004232562,0.1654541,0.0002175043,0.0009200621,0.1361523],"study_design_scores_gemma":[0.00003961074,0.002058094,0.9472393,0.00005664774,0.00008292926,0.0004735527,0.007568106,0.003266612,0.0372841,0.0002527378,0.001610714,0.00006765102],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973676,0.00003167244,0.001532415,0.00001981315,0.000003592192,0.00002391637,0.00005778163,0.00003057918,0.000932703],"genre_scores_gemma":[0.9974067,0.00004872332,0.001706824,0.00002479253,0.00000297954,0.00002936424,0.00004929559,0.000008689562,0.0007226305],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002479551,"threshold_uncertainty_score":0.00829494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0304908009610517,"score_gpt":0.3960855067001863,"score_spread":0.3655947057391346,"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."}}