{"id":"W6939099005","doi":"10.60692/m7hdm-s4m11","title":"Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications","year":2018,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Text Readability and Simplification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Office of the Chief Medical Examiner","funders":"","keywords":"Comprehension; Coherence (philosophical gambling strategy); Set (abstract data type); Reading comprehension; Interpretation (philosophy); Semantic interpretation; Natural language; Identification (biology)","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":[0.0002581378,0.00008714965,0.00008931295,0.0001072306,0.0002316967,0.0001814776,0.0005187939,0.00005510096,0.000001237817],"category_scores_gemma":[0.0000320879,0.00005801984,0.00004970346,0.0003781149,0.00005829515,0.0007897657,0.00005528073,0.00005900785,0.00002546594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007595636,"about_ca_system_score_gemma":0.00006445996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001052709,"about_ca_topic_score_gemma":1.146711e-7,"domain_scores_codex":[0.999202,0.000007920788,0.0003298901,0.0001351605,0.0002086031,0.0001164209],"domain_scores_gemma":[0.998843,0.00001514236,0.0003222929,0.0002712994,0.0005228541,0.00002537878],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001008589,0.00004483852,0.02157549,0.002446198,0.00004233598,2.11484e-8,0.4537996,0.00001121706,0.0003782635,0.250729,0.00173444,0.2691377],"study_design_scores_gemma":[0.002674065,0.0005363924,0.418411,0.003715519,0.0001272104,0.0001489357,0.0854849,0.2117674,0.2387922,0.001350058,0.03472452,0.002267754],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1884542,0.00001079148,0.7971437,0.001860906,0.0003681986,0.002927155,0.00004892303,0.0005119853,0.008674117],"genre_scores_gemma":[0.9901992,1.715176e-8,0.008884657,0.0001465517,0.000132984,0.0004667788,0.000004817838,0.000003468703,0.000161505],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.801745,"threshold_uncertainty_score":0.236598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02536774890642076,"score_gpt":0.2651448984971112,"score_spread":0.2397771495906904,"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."}}