{"id":"W4393503215","doi":"10.5281/zenodo.7796011","title":"Dataset for the TIA1 antibody screening study","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Antibody; Computational biology; Computer science; Biology; Genetics","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":[0.001354278,0.001456367,0.001553312,0.002932843,0.0006466857,0.001815967,0.002172782,0.002608596,0.05798109],"category_scores_gemma":[0.009026786,0.0004197253,0.001331647,0.004290464,0.0003321895,0.0008076171,0.001502985,0.001487764,0.04248484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001115598,"about_ca_system_score_gemma":0.001954518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007146676,"about_ca_topic_score_gemma":0.01766376,"domain_scores_codex":[0.9987453,0.0002809359,0.0002129728,0.0004384072,0.0002122789,0.0001100852],"domain_scores_gemma":[0.9970117,0.001400601,0.0003414167,0.0004877573,0.000522582,0.0002358442],"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":[0.0003942685,0.00008635889,0.004148458,0.004312589,0.000231467,0.0001268329,0.00004080616,0.001137368,0.0006179575,0.001031609,0.9799849,0.007887359],"study_design_scores_gemma":[0.0007359893,0.00007757163,0.01053772,0.001090319,0.0002583298,0.0003396235,0.00008170101,0.001126239,0.0007702983,0.003038414,0.9818907,0.00005301774],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003567327,0.0003037363,0.0001537285,0.00009452656,0.00002641734,0.00002391253,0.9983444,0.0001811084,0.0005154281],"genre_scores_gemma":[0.0008094319,0.0001314776,0.0004678953,0.0001073206,0.000008215335,0.0001359822,0.997925,0.00003746904,0.0003771682],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05798109,"threshold_uncertainty_score":0.1939661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05197658169050061,"score_gpt":0.3437961368751362,"score_spread":0.2918195551846355,"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."}}