{"id":"W4393408774","doi":"10.1101/2024.03.27.587041","title":"Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas Construction and Usage","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Health, Environment, Cognitive Aging","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; Common Fund; National Institutes of Health; NIH Office of the Director; Canadian Institute for Advanced Research","keywords":"Atlas (anatomy); Computer science; Cartography; Geography; Biology; Anatomy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001044976,0.0008544169,0.00062636,0.0002508427,0.0006116619,0.0004665876,0.0005962286,0.0007412717,0.0005257883],"category_scores_gemma":[0.00008389558,0.000944544,0.0001291728,0.0005607528,0.001124793,0.0002338727,0.002429902,0.001774795,0.0008450891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009012115,"about_ca_system_score_gemma":0.0001257629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006173626,"about_ca_topic_score_gemma":0.00003863575,"domain_scores_codex":[0.9945667,0.0003381417,0.0007738513,0.00256514,0.0007633063,0.0009929006],"domain_scores_gemma":[0.9974394,0.00003853191,0.0004483216,0.001450614,0.00004657339,0.0005765348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000007059761,0.0002140595,0.02061813,0.0005537205,0.0001197339,0.0002358953,0.00003488829,0.00002835201,0.9768761,0.000750674,0.0002418666,0.0003194739],"study_design_scores_gemma":[0.001720131,0.0007043829,0.5959752,0.002372831,0.0008398355,9.312918e-7,0.00003712193,0.0009901952,0.2909293,0.0002716067,0.1010816,0.005076871],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949745,0.0004456909,0.0004015635,0.0001732825,0.0004415249,0.001998005,0.0001382331,0.0007121238,0.0007150933],"genre_scores_gemma":[0.9881666,0.0001780533,0.01050665,0.0001785391,0.0002203281,0.0005306839,0.00000223826,0.000187484,0.00002947764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6859469,"threshold_uncertainty_score":0.9999329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714348019966578,"score_gpt":0.2573146904181123,"score_spread":0.2401712102184465,"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."}}