{"id":"W4281664560","doi":"10.1002/tesq.3161","title":"Digital Literacies in <scp>TESOL</scp>: Mapping Out the Terrain","year":2022,"lang":"en","type":"article","venue":"TESOL Quarterly","topic":"Literacy, Media, and Education","field":"Arts and Humanities","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Library science; Citation; Inclusion (mineral); Columbia university; Media studies; Sociology; Computer science; Anthropology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003076708,0.0001768801,0.000170326,0.00018241,0.0006067395,0.0009180001,0.0003466364,0.00002288055,0.0007611504],"category_scores_gemma":[0.00007304548,0.000136402,0.00009121517,0.00008647073,0.0001407276,0.0007334565,0.00004047686,0.0003174192,0.0002495417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007715863,"about_ca_system_score_gemma":0.00006043628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001186541,"about_ca_topic_score_gemma":0.0002666458,"domain_scores_codex":[0.9986149,0.00009880804,0.000355546,0.0002517861,0.000286339,0.000392595],"domain_scores_gemma":[0.9989938,0.0004736522,0.0001121215,0.0003135713,0.00004814882,0.00005872241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.000002519842,0.0001164114,0.001169379,0.00001886192,0.00001208499,0.000006277028,0.9570849,0.000001520666,0.00001209887,0.002312118,0.0204029,0.01886092],"study_design_scores_gemma":[0.000174103,0.0001869848,0.0009337579,0.00001803951,0.00000505404,0.000006303582,0.5487147,0.0001610396,0.000002639741,0.00411241,0.4456126,0.00007232117],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9598439,0.0005095273,0.00001377682,0.001572617,0.002370408,0.0002979917,0.0001057621,0.0001240231,0.03516201],"genre_scores_gemma":[0.9651428,0.000001585423,0.00001196288,0.001010224,0.001301947,0.0001847001,0.0001318751,0.00002422033,0.03219061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4252097,"threshold_uncertainty_score":0.8852296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357149687598935,"score_gpt":0.2234667665565265,"score_spread":0.1998952696805372,"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."}}