{"id":"W4245864811","doi":"10.32920/ryerson.14639757","title":"Integrating iPads into Learning and Libraries","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Multimedia; Mathematics education; Data science; World Wide Web; Psychology","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":[0.0005689646,0.0005149677,0.0004163365,0.0009159432,0.0006977866,0.004796141,0.0008486689,0.001327955,0.01702657],"category_scores_gemma":[0.002817521,0.000590546,0.0007955055,0.001585665,0.0007871648,0.006038319,0.004828445,0.00124954,0.005728494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006048688,"about_ca_system_score_gemma":0.0006532914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002210801,"about_ca_topic_score_gemma":0.00210009,"domain_scores_codex":[0.9987814,0.000284659,0.00006229468,0.0001342733,0.0006143283,0.0001230136],"domain_scores_gemma":[0.9991456,0.0002060504,0.00002538559,0.000357439,0.0001930151,0.00007240771],"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":[0.0002020225,0.0003119443,0.002516794,0.0004015918,0.00007294483,0.0004736384,0.001624945,0.00712154,0.05518235,0.1782354,0.01229913,0.7415577],"study_design_scores_gemma":[0.00008278416,0.0002950447,0.005551102,0.0005389091,0.0001684991,0.0009890884,0.001823191,0.06641992,0.09665512,0.1492823,0.6780907,0.0001032864],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06298999,0.002865487,0.7129745,0.002591366,0.0004804,0.0002727087,0.0002876709,0.005458511,0.2120793],"genre_scores_gemma":[0.3600037,0.00511932,0.5031074,0.0009996584,0.0002904239,0.0002609716,0.0007268845,0.001659844,0.1278318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01702657,"threshold_uncertainty_score":0.05695957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223049216021489,"score_gpt":0.26866397882683,"score_spread":0.2564334866666151,"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."}}