{"id":"W4413161850","doi":"10.1016/j.procs.2025.07.111","title":"Examining Critical Factors in Selecting AI Tools for Educational Success","year":2025,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Intelligent Tutoring Systems and Adaptive Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Canada West","funders":"University Canada West","keywords":"Computer science; Data science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0536746,0.0006719505,0.0008125548,0.007870147,0.002559883,0.01374406,0.001338161,0.001117965,0.003346087],"category_scores_gemma":[0.2074205,0.000486261,0.0009337967,0.005847818,0.002267926,0.007685585,0.003009626,0.001664868,0.00070863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004778631,"about_ca_system_score_gemma":0.01187238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002614982,"about_ca_topic_score_gemma":0.004702743,"domain_scores_codex":[0.954818,0.02205169,0.00614443,0.001518101,0.01346689,0.002000942],"domain_scores_gemma":[0.7418441,0.1959159,0.01913159,0.002531313,0.03616451,0.004412535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005764448,0.0007469888,0.2838189,0.009472615,0.0005532071,0.0007447809,0.06853452,0.0007944897,0.001726204,0.01617576,0.006046385,0.6108097],"study_design_scores_gemma":[0.000188222,0.003545179,0.4740227,0.03236428,0.002507512,0.001330291,0.3529,0.004347442,0.01173688,0.01953479,0.09709813,0.0004244497],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8822975,0.02680541,0.01375451,0.0105608,0.0003260636,0.002226847,0.0003340009,0.0001319122,0.06356289],"genre_scores_gemma":[0.9828871,0.005966869,0.009134028,0.0003703141,0.00003325759,0.0004676828,0.0001060849,0.00003197138,0.00100271],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0536746,"threshold_uncertainty_score":0.2838619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04989190787035973,"score_gpt":0.3404306432146234,"score_spread":0.2905387353442636,"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."}}