{"id":"W2952974520","doi":"10.19173/irrodl.v20i2.3961","title":"Mobile Technology","year":2019,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Mobile Learning in Education","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Competence (human resources); Interdependence; Mobile technology; Global citizenship; Mobile device; Public relations; Pedagogy; Political science; Psychology; Sociology; Computer science; Social science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004004593,0.0000575286,0.0001505811,0.0001858662,0.00006970518,0.0001396739,0.002546384,0.00003384957,0.0001621417],"category_scores_gemma":[0.001109235,0.00004148049,0.00002085096,0.0009248886,0.00009958232,0.0002668568,0.001547561,0.0005900526,0.00009949648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007567205,"about_ca_system_score_gemma":0.0001456868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007507449,"about_ca_topic_score_gemma":0.000001513418,"domain_scores_codex":[0.9985426,0.0003289385,0.0002395331,0.0002412344,0.0004679059,0.0001798087],"domain_scores_gemma":[0.9987091,0.0004842854,0.0001104087,0.0003731294,0.0002929692,0.00003011962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002998838,0.0002454205,0.2473068,0.001691239,0.0000456927,0.00001047205,0.0004991553,0.001062818,0.000554534,0.3296215,0.00634501,0.4125874],"study_design_scores_gemma":[0.0008458318,0.000465351,0.01450954,0.01237657,0.000003764013,0.00006540122,0.002292913,0.02409239,0.0004648958,0.02159694,0.9230605,0.0002259265],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5708251,0.1098534,0.0214102,0.1079411,0.001586447,0.008186826,0.00002353398,0.0002214806,0.1799519],"genre_scores_gemma":[0.9844455,0.01312126,0.001078152,0.0001406047,0.00001875845,0.0001791436,0.00002248301,0.000004647793,0.0009894237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9167154,"threshold_uncertainty_score":0.4731857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04230560053123637,"score_gpt":0.4241010271625681,"score_spread":0.3817954266313318,"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."}}