{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003804989,0.0005166573,0.000232937,0.002972964,0.003535824,0.005457385,0.001066128,0.001186596,0.009101317],"category_scores_gemma":[0.01224046,0.000241787,0.0003887721,0.001225283,0.002116292,0.006156157,0.008860184,0.0008404723,0.002428829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001059279,"about_ca_system_score_gemma":0.001737246,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004035763,"about_ca_topic_score_gemma":0.0009156072,"domain_scores_codex":[0.9955591,0.003148918,0.0001070725,0.0002792045,0.0006510751,0.000254651],"domain_scores_gemma":[0.9820011,0.01223161,0.00158673,0.001224921,0.0009941262,0.001961572],"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":[0.0002473482,0.001624189,0.01633412,0.001321912,0.00007591354,0.001629359,0.09453749,0.001721079,0.0154906,0.08692402,0.01053323,0.7695606],"study_design_scores_gemma":[0.0002755249,0.001723029,0.03105327,0.001369699,0.0001990693,0.002395268,0.08806141,0.007126617,0.01867846,0.1289914,0.7199301,0.000196109],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.515702,0.00290324,0.08421394,0.01235286,0.0005211559,0.0008434547,0.0001050358,0.001808684,0.3815497],"genre_scores_gemma":[0.9404991,0.001124274,0.03955797,0.000469301,0.0002230676,0.0003348967,0.0000531575,0.000103671,0.01763457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009101317,"threshold_uncertainty_score":0.03044701,"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."}}