{"id":"W1588616339","doi":"10.24908/pceea.v0i0.4805","title":"CAN MOBILE LEARNING MATURITY BE MEASURED? A PRELIMINARY WORK","year":2013,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Maturity (psychological); Capability Maturity Model; Popularity; Computer science; Knowledge management; Mobile technology; Mobile device; Process (computing); World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006122934,0.0001771542,0.0001664128,0.0003035014,0.0002862113,0.0003714318,0.0008797196,0.000183648,0.00005038837],"category_scores_gemma":[0.001664939,0.0001815979,0.00008910443,0.001044321,0.00001760875,0.0005676276,0.00007964849,0.0005047781,0.00003119939],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002486411,"about_ca_system_score_gemma":0.0009720689,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01052778,"about_ca_topic_score_gemma":0.0007139338,"domain_scores_codex":[0.9984453,0.0000236966,0.0003033621,0.0003107114,0.0004974916,0.0004194854],"domain_scores_gemma":[0.9979689,0.00009507628,0.0004617936,0.0002224519,0.0009777702,0.0002740479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000004939901,0.0004149943,0.5407088,0.0006314293,0.0002556662,2.049299e-7,0.04176353,0.02096404,0.003989013,0.03282711,0.3252254,0.03321491],"study_design_scores_gemma":[0.0002098142,0.0000862499,0.8841086,0.0003220216,0.00004578043,0.00001014483,0.001088423,0.0170447,0.002082801,0.001091453,0.09323891,0.0006710793],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9461266,0.0002516821,0.0002933333,0.03926358,0.004547982,0.001746252,0.000005051025,0.0005125654,0.007252928],"genre_scores_gemma":[0.9893693,0.000004900129,0.00478927,0.0003579313,0.0001774356,0.0004675457,0.000005654035,0.00002924264,0.004798749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3433999,"threshold_uncertainty_score":0.9960612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005301032632490749,"score_gpt":0.190307687725987,"score_spread":0.1850066550934963,"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."}}