{"id":"W2970205171","doi":"","title":"TAC SRIE 2018: Extracting Systematic Review Information with MedaCy.","year":2018,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Information retrieval","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01830683,0.001799924,0.003807996,0.03327492,0.001942575,0.005401216,0.002093149,0.001852697,0.03034352],"category_scores_gemma":[0.1623812,0.001270388,0.005623299,0.02183222,0.00126883,0.004732803,0.006932353,0.002003831,0.008231585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0016369,"about_ca_system_score_gemma":0.01242655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003245242,"about_ca_topic_score_gemma":0.01431939,"domain_scores_codex":[0.9859995,0.005257878,0.004766338,0.001904334,0.001837896,0.0002340276],"domain_scores_gemma":[0.9026234,0.07482126,0.007640764,0.007882181,0.005663353,0.001369084],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001678527,0.0001815027,0.0179231,0.1935359,0.010645,0.001169476,0.004054434,0.001935435,0.007172657,0.02522799,0.403129,0.333347],"study_design_scores_gemma":[0.001075913,0.0003656865,0.01691019,0.02360008,0.01079489,0.001266875,0.001229834,0.007311638,0.005157954,0.06142821,0.8705356,0.0003231416],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.009196787,0.02906422,0.1060177,0.004465314,0.001039217,0.006065979,0.8111305,0.0223273,0.01069291],"genre_scores_gemma":[0.04111003,0.009383436,0.5015028,0.001712712,0.0005181598,0.02172433,0.4182188,0.002099713,0.003730068],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9816931,"threshold_uncertainty_score":0.1015092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006880278853483287,"score_gpt":0.2608429318200521,"score_spread":0.2539626529665688,"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."}}