{"id":"W6969088978","doi":"10.5281/zenodo.4609335","title":"CINECA_Query expansion service_D1.2","year":2020,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"European Commission","keywords":"Discoverability; Ontology; Representation (politics); SPARQL; Ranking (information retrieval); External Data Representation; Data access; Data integration; RDF","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":[0.008846716,0.002734361,0.001821503,0.003277991,0.001616206,0.007405954,0.004547221,0.003041585,0.07916607],"category_scores_gemma":[0.02432115,0.001711697,0.003126553,0.002979609,0.001562602,0.00930788,0.009814223,0.004266407,0.05217854],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003508973,"about_ca_system_score_gemma":0.004540804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03354904,"about_ca_topic_score_gemma":0.01730789,"domain_scores_codex":[0.9934052,0.001346378,0.0006982788,0.001403766,0.002573255,0.0005732625],"domain_scores_gemma":[0.9856476,0.004785909,0.0003764635,0.005327173,0.00312585,0.0007370695],"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":[0.001041694,0.000167629,0.003051286,0.0006230799,0.0001362627,0.0004293661,0.000833954,0.001529278,0.00592775,0.02505904,0.9012398,0.05996094],"study_design_scores_gemma":[0.0003653976,0.000089382,0.002691624,0.0001762299,0.00004498277,0.0004806741,0.0003939597,0.03887171,0.01325394,0.0211968,0.922245,0.000190287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.003373029,0.0004967747,0.1710621,0.003612976,0.0005946871,0.001219513,0.08486801,0.6825712,0.05220176],"genre_scores_gemma":[0.1051805,0.001429029,0.2597975,0.01433828,0.0008163243,0.003485486,0.3918955,0.1537206,0.06933663],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.07916607,"threshold_uncertainty_score":0.2648369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04041229772472648,"score_gpt":0.2513374146380585,"score_spread":0.210925116913332,"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."}}