{"id":"W2163040745","doi":"","title":"Guiding Age 10-11 Students to Notice the Salient Features of Physical Change Models in Chemistry Digital Learning Objects.","year":2015,"lang":"en","type":"article","venue":"Journal of Computers in Mathematics and Science Teaching","topic":"Innovative Educational Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"The King's University; University of Alberta","funders":"","keywords":"Notice; Salient; Mathematics education; Computer science; Educational technology; Science education; Multimedia; Chemistry; Psychology; Artificial intelligence; Political 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":[0.003496326,0.0001007136,0.0002247078,0.0003011742,0.0000966392,0.0003736261,0.001658918,0.00002360579,8.608823e-8],"category_scores_gemma":[0.001025198,0.00006839646,0.00002972934,0.0007088846,0.0001598215,0.0009452912,0.0007785991,0.0002781719,2.037054e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001382142,"about_ca_system_score_gemma":0.000111292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005317234,"about_ca_topic_score_gemma":0.000001012263,"domain_scores_codex":[0.9983914,0.00003274017,0.0003654241,0.0001562857,0.0008422589,0.0002118277],"domain_scores_gemma":[0.998945,0.0003008718,0.0003251368,0.0001806368,0.0001853627,0.00006299862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001768983,0.001474463,0.006741281,0.0001863254,0.00003225018,0.00009706648,0.5799115,0.06035995,0.01463537,0.3057919,0.000401264,0.03035103],"study_design_scores_gemma":[0.0008741969,0.0004885792,0.008458261,0.001825135,0.000008726636,0.0001784468,0.03143408,0.7261811,0.004070199,0.225947,0.00007261909,0.0004616413],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9027161,0.00002527304,0.09571702,0.0006659288,0.0001243739,0.00008803812,1.571443e-7,0.00001049177,0.0006526164],"genre_scores_gemma":[0.8793848,0.000001055465,0.1205006,0.00005005116,0.00004632949,0.000001771404,5.132317e-8,0.000003219598,0.00001206019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6658212,"threshold_uncertainty_score":0.3602885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08163939311193909,"score_gpt":0.344371484726223,"score_spread":0.2627320916142839,"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."}}