{"id":"W2564037277","doi":"10.2196/mhealth.6705","title":"The Mobile Phone Affinity Scale: Enhancement and Refinement","year":2016,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Impact of Technology on Adolescents","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Drug Abuse; National Institutes of Health","keywords":"Mobile phone; Computer science; Scale (ratio); Telecommunications; Geography; Cartography","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001397013,0.0001107926,0.0001556296,0.00004071447,0.001850605,0.0000460596,0.0001706114,0.0001112516,0.00006175072],"category_scores_gemma":[0.00008601229,0.00006358451,0.00001727459,0.0001339419,0.0006297465,0.00008607782,0.00007891595,0.0001476546,0.00003295884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002002385,"about_ca_system_score_gemma":0.0003207857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007936089,"about_ca_topic_score_gemma":0.001752768,"domain_scores_codex":[0.9983311,0.0001790044,0.0002546152,0.0002487527,0.0002957703,0.0006907025],"domain_scores_gemma":[0.9990357,0.0001336607,0.0001525665,0.000224363,0.00004448466,0.0004092736],"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":[0.0001344256,0.0001877794,0.02193825,0.0001338784,0.000008455473,0.000001218131,0.003884644,8.838024e-9,0.0001616411,0.003629841,0.02095487,0.948965],"study_design_scores_gemma":[0.002993254,0.0009840924,0.2819679,0.0002344341,0.00003147983,0.000005699546,0.006379259,0.000004509257,0.0005470912,0.003720144,0.7027329,0.0003992131],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9530141,0.001625864,0.00005389133,0.04192661,0.0003103561,0.0006816532,0.000008179073,0.00009963223,0.002279769],"genre_scores_gemma":[0.9788703,0.01725307,0.000139128,0.001272606,0.0001208644,0.000102325,6.100857e-7,0.000007785956,0.002233312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9485658,"threshold_uncertainty_score":0.9994488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03408425625091747,"score_gpt":0.3875012817327481,"score_spread":0.3534170254818306,"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."}}