{"id":"W47333458","doi":"10.25959/23206415","title":"Mobile phone text messaging language : how and why undergraduates use textisms","year":2013,"lang":"en","type":"dissertation","venue":"Figshare","topic":"Digital Communication and Language","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Popularity; Text messaging; Mobile phone; Phone; Psychology; Literacy; Text message; Computer science; Internet privacy; Social psychology; Linguistics; Pedagogy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00003184116,0.0002665009,0.0002265145,0.0001433812,0.0001159543,0.001928217,0.001032755,0.0001534448,0.009701059],"category_scores_gemma":[0.0002431426,0.0002497832,0.00007304912,0.0002458601,0.000006654716,0.001362803,0.0003150478,0.0002775696,0.001074977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002598142,"about_ca_system_score_gemma":0.00005283647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000552178,"about_ca_topic_score_gemma":0.0001332909,"domain_scores_codex":[0.9988951,0.00005339339,0.0001553544,0.0004060488,0.0002471492,0.0002429577],"domain_scores_gemma":[0.9984732,0.000176826,0.0001897466,0.0009311957,0.0001101079,0.0001189479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002898771,0.00007499401,0.000005883719,0.0004961297,0.00005710115,0.00004476708,0.007085661,0.000003239741,0.0004621019,0.001624575,0.9064784,0.08366424],"study_design_scores_gemma":[0.0005142666,0.00009665237,0.002179162,0.004067535,0.00002112461,0.00003145177,0.004770593,0.002486689,0.004097472,0.000417099,0.9799564,0.001361482],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01787408,0.05825992,0.0001937676,0.001595997,0.0005884956,0.003896378,0.09592906,0.003425125,0.8182372],"genre_scores_gemma":[0.598642,0.0001102939,0.001558892,0.0009981517,0.00004066652,0.0007537717,0.2720291,0.00008360366,0.1257836],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6924536,"threshold_uncertainty_score":0.9999955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02502491036017116,"score_gpt":0.2593299642676871,"score_spread":0.234305053907516,"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."}}