{"id":"W4394131026","doi":"10.6084/m9.figshare.19401737","title":"Additional file 3 of The Xenopus phenotype ontology: bridging model organism phenotype data to human health and development","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Phenotype; Bridging (networking); Xenopus; Organism; Model organism; Computational biology; Ontology; Computer science; Biology; Genetics; Gene; Computer security","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001464174,0.001892189,0.001345577,0.003556329,0.0008609507,0.001973403,0.002232609,0.001765372,0.3765457],"category_scores_gemma":[0.008845724,0.0006866522,0.001358902,0.005001305,0.0004997775,0.00169345,0.001753855,0.001591449,0.08730619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001789004,"about_ca_system_score_gemma":0.002247013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01430469,"about_ca_topic_score_gemma":0.02663724,"domain_scores_codex":[0.9990922,0.0001147947,0.0001501392,0.0003014782,0.0002072377,0.0001341457],"domain_scores_gemma":[0.9944708,0.003369152,0.0004869908,0.0005902727,0.0007750372,0.0003076436],"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":[0.0001677058,0.00005791013,0.002238997,0.002209855,0.00005944002,0.00006958155,0.00005421405,0.0004209736,0.0003263495,0.0008307043,0.9903106,0.003253778],"study_design_scores_gemma":[0.0008736068,0.00005355766,0.01028013,0.0008707331,0.0001159304,0.0002613551,0.0001947471,0.000783622,0.001101892,0.003535429,0.9818649,0.00006410918],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005599423,0.00001093083,0.0000561143,0.00002623016,0.000005652628,0.00001033388,0.9994779,0.000121077,0.0002357571],"genre_scores_gemma":[0.000684485,0.00003297917,0.0005212127,0.00006205736,0.000005725244,0.0001549614,0.997768,0.00009562707,0.0006748438],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3765457,"threshold_uncertainty_score":0.8892819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08255026807067962,"score_gpt":0.3075142445151045,"score_spread":0.2249639764444249,"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."}}