{"id":"W4392846105","doi":"10.1145/3625007.3629127","title":"KoExPubMed: A Tool for Effective and Customized Knowledge Extraction from PubMed","year":2023,"lang":"en","type":"article","venue":"","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Extraction (chemistry); Information retrieval","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":[0.003291321,0.002828636,0.001715792,0.01693993,0.001046255,0.003497986,0.00205221,0.001271319,0.03171483],"category_scores_gemma":[0.01584122,0.001222515,0.001841925,0.01090681,0.0004557256,0.004197232,0.005462144,0.001326806,0.01578295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007247097,"about_ca_system_score_gemma":0.003226555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001605678,"about_ca_topic_score_gemma":0.003557484,"domain_scores_codex":[0.9981726,0.0004139741,0.0005546648,0.0003242262,0.0004426933,0.00009193841],"domain_scores_gemma":[0.9900964,0.007186386,0.0008671735,0.0007967473,0.0007237032,0.0003295342],"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":[0.0009232379,0.0003010804,0.004959493,0.02063858,0.0009447376,0.003866524,0.002214505,0.002705839,0.02168592,0.01416642,0.3394572,0.5881364],"study_design_scores_gemma":[0.0007358362,0.000285017,0.0112085,0.002998307,0.0004547215,0.004816492,0.001223735,0.03009327,0.03134251,0.02783295,0.8884726,0.0005361126],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.008696044,0.002649372,0.4072475,0.001648642,0.0003441294,0.002259477,0.1966202,0.3681668,0.0123678],"genre_scores_gemma":[0.0249007,0.002663949,0.8099185,0.0009485369,0.000194051,0.003202891,0.1391912,0.01301036,0.005969771],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03171483,"threshold_uncertainty_score":0.1060967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01754573588304488,"score_gpt":0.2996503121778821,"score_spread":0.2821045762948372,"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."}}