{"id":"W2963179014","doi":"10.29173/iasl7204","title":"A Richer Read: Supporting Critical Analysis","year":2016,"lang":"en","type":"article","venue":"IASL Annual Conference Proceedings","topic":"Literacy and Educational Practices","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Reading (process); Set (abstract data type); Computer science; Contrast (vision); Mathematics education; Psychology; Artificial intelligence; Linguistics; Programming language","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":[0.06749237,0.001902242,0.001370334,0.009261522,0.005204177,0.01770084,0.003625893,0.00262561,0.05098008],"category_scores_gemma":[0.2003774,0.001279362,0.001506968,0.004725081,0.005491305,0.01993526,0.01812167,0.004506086,0.01156997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002827142,"about_ca_system_score_gemma":0.00983051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007606851,"about_ca_topic_score_gemma":0.003215326,"domain_scores_codex":[0.9615092,0.02645961,0.002510669,0.003890472,0.004787682,0.0008423125],"domain_scores_gemma":[0.6697214,0.2524206,0.009229814,0.04098668,0.02001572,0.007625755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000729416,0.0008984222,0.004685986,0.004185691,0.0001269207,0.001796816,0.1358074,0.001760936,0.007822338,0.1598492,0.143711,0.5386259],"study_design_scores_gemma":[0.0005061215,0.0002113343,0.003029535,0.006240315,0.0001147615,0.001329815,0.04187108,0.009959935,0.008303128,0.3362405,0.591895,0.0002984239],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02899914,0.00161529,0.8261034,0.02260832,0.003422438,0.00307012,0.004941212,0.02507666,0.08416341],"genre_scores_gemma":[0.08394259,0.0006336386,0.9005758,0.001193833,0.0006635335,0.002649756,0.001362494,0.002546449,0.006431835],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06749237,"threshold_uncertainty_score":0.356938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04654627095964278,"score_gpt":0.4063899509019165,"score_spread":0.3598436799422737,"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."}}