{"id":"W4310267466","doi":"10.1101/2022.11.25.518001","title":"SLIDE: Significant Latent Factor Interaction Discovery and Exploration across biological domains","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Systemic Sclerosis and Related Diseases","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Inference; Computational biology; Computer science; Discriminative model; Mechanism (biology); Biology; Machine learning; Artificial intelligence; Bioinformatics","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":[0.003788276,0.001825056,0.001571939,0.002744514,0.000803121,0.001940421,0.00148025,0.001093912,0.004263461],"category_scores_gemma":[0.007667467,0.0005863673,0.003688382,0.002006225,0.0009817119,0.001500686,0.00299899,0.002647079,0.001347761],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005332515,"about_ca_system_score_gemma":0.001648483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00262672,"about_ca_topic_score_gemma":0.004944137,"domain_scores_codex":[0.9982767,0.0007235447,0.00007576062,0.0004931232,0.0002793878,0.0001514076],"domain_scores_gemma":[0.9947607,0.003927785,0.000374081,0.0005036816,0.0002148849,0.0002188028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002381466,0.0009012115,0.08373664,0.002353044,0.003371243,0.002517625,0.001142056,0.2882904,0.05152655,0.03883197,0.05788606,0.4670618],"study_design_scores_gemma":[0.0001531201,0.0002252963,0.00539668,0.00006482219,0.0001411663,0.0002676175,0.0001665335,0.9430038,0.003734088,0.04105843,0.005725719,0.00006275985],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06849973,0.002314265,0.9042526,0.001097674,0.0001162603,0.0002066287,0.007805826,0.01417948,0.001527504],"genre_scores_gemma":[0.4962488,0.0009780733,0.4730255,0.0009031123,0.0003269549,0.000707739,0.02413585,0.0009711026,0.002702879],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004263461,"threshold_uncertainty_score":0.02003455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05167816385312227,"score_gpt":0.2795780560540562,"score_spread":0.227899892200934,"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."}}