{"id":"W7143328845","doi":"10.5281/zenodo.19331698","title":"Exploring the Intersection of Social Networks and Mobile Technologies in Educational Settings","year":2024,"lang":"","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Impact of Technology on Adolescents","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Intersection (aeronautics); Czech; Mobile telephony; Mobile device; Mobile technology; Social network (sociolinguistics); Information and Communications Technology; Mobile computing","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":[0.001269824,0.000250795,0.0002016309,0.001899435,0.001882749,0.004457937,0.0003369848,0.0004941563,0.003990584],"category_scores_gemma":[0.002181844,0.000171504,0.0003238379,0.001861667,0.002084473,0.004378797,0.003424606,0.0007002642,0.0001864306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001274285,"about_ca_system_score_gemma":0.001280736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00335894,"about_ca_topic_score_gemma":0.005543302,"domain_scores_codex":[0.9984267,0.00116587,0.00003399101,0.00009401253,0.000110978,0.0001685374],"domain_scores_gemma":[0.9974461,0.001729523,0.0003615544,0.00006546426,0.0001323506,0.0002650651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001449801,0.0004433405,0.4376178,0.00108932,0.000154287,0.002256172,0.2903767,0.0004858618,0.001999336,0.1280813,0.001805018,0.135546],"study_design_scores_gemma":[0.00001567294,0.0002857021,0.4005303,0.001081716,0.0001047194,0.001559305,0.532158,0.001142439,0.0007315557,0.0190231,0.04333454,0.00003297453],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9314442,0.003119095,0.002650323,0.00261048,0.00005386828,0.00007742472,0.0001078712,0.00001052465,0.05992626],"genre_scores_gemma":[0.9981148,0.000671687,0.000505097,0.00005493922,0.000009458854,0.00002422279,0.00001197586,0.000001642406,0.0006062849],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004457937,"threshold_uncertainty_score":0.01334983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04821939259418019,"score_gpt":0.2903604246660989,"score_spread":0.2421410320719187,"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."}}