{"id":"W4400891208","doi":"10.3102/ip.24.2101405","title":"Why This App? How Ratings and Rankings Impact Educators’ Selection of High-Quality Educational Apps (Poster 12)","year":2024,"lang":"en","type":"article","venue":"","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Selection (genetic algorithm); Computer science; Quality (philosophy); Smartphone app; Internet privacy; World Wide Web; 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":[0.0007125546,0.0001699063,0.0001835067,0.0002503068,0.0001096742,0.0005129724,0.0003097717,0.00008613898,0.0006177823],"category_scores_gemma":[0.0001714449,0.0001434748,0.00007693694,0.0005975999,0.00006761819,0.0009100632,0.00009848164,0.0002254879,0.00002776844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001441697,"about_ca_system_score_gemma":0.0004852603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001074413,"about_ca_topic_score_gemma":0.00002647882,"domain_scores_codex":[0.9984803,0.0001641142,0.0002678933,0.0005139606,0.0003537085,0.0002200695],"domain_scores_gemma":[0.9988492,0.0004332622,0.0001329446,0.000324218,0.0001634381,0.00009697775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0000347067,0.0006537979,0.1005156,0.0008473481,0.0002363327,0.000001006401,0.02758754,0.0002226459,0.01992479,0.1985108,0.4801637,0.1713017],"study_design_scores_gemma":[0.001154238,0.0009679526,0.7455744,0.0006953916,0.0001315507,0.0004078571,0.0008159757,0.1045634,0.02881096,0.04610837,0.06874038,0.00202956],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8268753,0.000259458,0.1196406,0.04421961,0.002506038,0.0004874234,0.000003751213,0.0004096945,0.005598189],"genre_scores_gemma":[0.9719754,0.000008994932,0.02312434,0.0006350946,0.0003266533,0.00004949441,0.00001188769,0.00001519513,0.003852899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6450588,"threshold_uncertainty_score":0.6764283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01192098158824773,"score_gpt":0.2953929039581972,"score_spread":0.2834719223699495,"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."}}