{"id":"W3139872651","doi":"10.29173/iasl7747","title":"Using social networks and ICTs to enhance literature circles","year":2021,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Educational Methods and Media Use","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"ICTS; Information and Communications Technology; Reading (process); Knowledge management; Sociology; Computer science; World Wide Web; Political 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":[0.0002593356,0.0001453961,0.0001800045,0.0000683984,0.0001986612,0.0006709653,0.0003332934,0.0001053245,0.000007320616],"category_scores_gemma":[0.0002848902,0.0001466578,0.00003264305,0.0006122226,0.00004511641,0.0007594775,0.0002984831,0.0002201225,0.000003935461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002524226,"about_ca_system_score_gemma":0.0002262222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005841517,"about_ca_topic_score_gemma":0.00000222356,"domain_scores_codex":[0.9987901,0.00002185642,0.0001646092,0.0004930434,0.0002193046,0.0003110399],"domain_scores_gemma":[0.9983962,0.00006043285,0.0000683816,0.00009176527,0.001181425,0.0002018038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000239507,0.0001629514,0.003405403,0.0001997758,0.00004346302,0.00004275406,0.5135331,0.00001164059,0.01656122,0.1256696,0.004786587,0.3355596],"study_design_scores_gemma":[0.002275133,0.001150228,0.1821893,0.005410668,0.0002141345,0.001818666,0.162528,0.1198318,0.1481068,0.2286656,0.1402801,0.007529491],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8189869,0.0006108854,0.1732452,0.005996809,0.0005390614,0.0001201693,0.000006462945,0.00008010968,0.0004144202],"genre_scores_gemma":[0.7981383,0.00005366799,0.199615,0.001421299,0.0005068095,0.00001458833,0.000002056379,0.000007740855,0.000240536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.351005,"threshold_uncertainty_score":0.6470134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04238031954501861,"score_gpt":0.3507300690554228,"score_spread":0.3083497495104042,"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."}}