{"id":"W2138982943","doi":"10.5430/ijhe.v1n2p43","title":"Examining Mobile Technology in Higher Education: Handheld Devices In and Out of the Classroom","year":2012,"lang":"en","type":"article","venue":"International Journal of Higher Education","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Mobile device; Mobile technology; Multimedia; Computer science; Graduate students; Psychology; Medical education; Mathematics education; Pedagogy; Medicine; World Wide Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0004262216,0.00009534417,0.0001392514,0.0006168304,0.00002388679,0.00005623462,0.0008307613,0.00008998528,0.00009373415],"category_scores_gemma":[0.00006030019,0.00007763098,0.00003072017,0.0004039489,0.0000577703,0.0008169801,0.0001221016,0.0002848242,0.000005659464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002480987,"about_ca_system_score_gemma":0.0005145597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003055105,"about_ca_topic_score_gemma":0.000009414321,"domain_scores_codex":[0.9987789,0.0001060928,0.0005028009,0.000136057,0.0003349074,0.0001411776],"domain_scores_gemma":[0.9986643,0.0001226265,0.0005968005,0.0002191053,0.0003507114,0.00004643404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007547455,0.0006666413,0.919822,0.00001329431,0.00001829703,4.067142e-7,0.002411557,0.00009380479,0.001035174,0.02104798,0.0009492713,0.05393396],"study_design_scores_gemma":[0.0002179274,0.00004298416,0.9545072,0.0002495334,0.000005147564,0.00004171117,0.0005605524,0.00002136374,0.0006748086,0.004492602,0.03910369,0.00008248799],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9712371,0.003152857,0.0001469906,0.009763516,0.01370148,0.0001317767,3.564232e-7,0.000008783052,0.001857193],"genre_scores_gemma":[0.9937213,0.00003378059,0.00342804,0.0003736714,0.0006857262,0.00003957438,0.000001116815,0.000007393288,0.001709404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05385147,"threshold_uncertainty_score":0.31657,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02543666466280798,"score_gpt":0.3218774917177415,"score_spread":0.2964408270549335,"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."}}