{"id":"W4302599139","doi":"10.1007/978-1-4614-6170-8_100005","title":"Information Extraction","year":2014,"lang":"en","type":"book-chapter","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Extraction (chemistry); Information extraction; Computer science; Information retrieval; Chromatography; Chemistry","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":[0.0008563232,0.002166388,0.001462109,0.007557802,0.001151713,0.004256593,0.001663504,0.0009928998,0.07937279],"category_scores_gemma":[0.003162032,0.0008490296,0.001562299,0.0091086,0.0005170731,0.00664494,0.002262365,0.001558846,0.09633368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007671856,"about_ca_system_score_gemma":0.001437208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001411097,"about_ca_topic_score_gemma":0.001993717,"domain_scores_codex":[0.9992583,0.0001151873,0.00007286631,0.0002185997,0.0002880281,0.00004686561],"domain_scores_gemma":[0.998896,0.0004111833,0.00005041547,0.0002812885,0.0003182751,0.00004279684],"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":[0.0000292918,0.00004217065,0.0001535514,0.0005801344,0.00003572443,0.00006673235,0.0001123706,0.0006433836,0.003079202,0.01597405,0.1584504,0.820833],"study_design_scores_gemma":[0.00001240994,0.00002847249,0.0007599826,0.0004743561,0.0001009715,0.0006213839,0.0001501787,0.008568574,0.01158686,0.05201238,0.9256356,0.00004882019],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.002745251,0.0234929,0.6985403,0.002525827,0.001886871,0.0006829688,0.01111851,0.01742471,0.2415826],"genre_scores_gemma":[0.03441516,0.03779339,0.4736509,0.00148394,0.00254824,0.0006893466,0.05089544,0.005043594,0.39348],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.07937279,"threshold_uncertainty_score":0.2655284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02130740299116722,"score_gpt":0.2286075006550297,"score_spread":0.2073000976638625,"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."}}