{"id":"W4399217282","doi":"10.14428/dvn/aauem2","title":"Core Metadata Schema for Learner Corpora (version 2)","year":2024,"lang":"en","type":"article","venue":"","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canarie","funders":"","keywords":"Metadata; Schema (genetic algorithms); Computer science; Information retrieval; Meta Data Services; Metadata repository; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008849333,0.0009639655,0.0009821946,0.005856306,0.002274447,0.00756565,0.002694184,0.002180183,0.06287622],"category_scores_gemma":[0.01800232,0.001443923,0.0007709699,0.007204889,0.001117394,0.009886887,0.0055644,0.003187248,0.09053168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002729074,"about_ca_system_score_gemma":0.008485969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01279532,"about_ca_topic_score_gemma":0.009880933,"domain_scores_codex":[0.994825,0.001164119,0.001303623,0.000573101,0.00182316,0.0003110893],"domain_scores_gemma":[0.9862133,0.002278112,0.000836003,0.003723294,0.00633912,0.0006100817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004244107,0.0001946361,0.003222834,0.001777793,0.00005316773,0.0003310412,0.00317981,0.001843823,0.008271477,0.1183627,0.7050194,0.1573188],"study_design_scores_gemma":[0.00002687245,0.00002395555,0.0008135049,0.000284678,0.000009956073,0.0001968899,0.0003704807,0.001036264,0.003051298,0.008731587,0.98541,0.00004446341],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.005511911,0.0008522656,0.3670796,0.002386709,0.000948933,0.004809593,0.4403828,0.04418518,0.133843],"genre_scores_gemma":[0.01894426,0.001158331,0.2598648,0.00162059,0.0002522197,0.005970436,0.6314587,0.01453325,0.06619737],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06287622,"threshold_uncertainty_score":0.2103419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06591753522626567,"score_gpt":0.3327246597542288,"score_spread":0.2668071245279631,"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."}}