{"id":"W3209141514","doi":"10.1038/s41592-021-01291-4","title":"MISpheroID: a knowledgebase and transparency tool for minimum information in spheroid identity","year":2021,"lang":"en","type":"article","venue":"Nature Methods","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Cancer Institute; National Institute on Aging; Kom op tegen Kanker; Canadian Institutes of Health Research; Stand Up To Cancer; Syöpäjärjestöt; Vlaamse regering; Universiteit Gent; Bundesministerium für Bildung und Forschung; ZonMw; Brain Tumour Charity; National Institutes of Health; Cancer Research UK","keywords":"Spheroid; Transparency (behavior); Crowdsourcing; Computer science; Interrogation; Computational biology; Biological system; Biochemical engineering; Biology; Engineering; Cell culture; Geography; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.001524711,0.0001088026,0.0001772347,0.00008155378,0.00003106122,0.00006720426,0.0001344442,0.0003399547,0.0001117865],"category_scores_gemma":[0.002689275,0.0001102273,0.00004910259,0.0004573175,0.00003277877,0.0003728146,0.0000385589,0.0006286466,0.000007278515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006061173,"about_ca_system_score_gemma":0.0000563242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003779083,"about_ca_topic_score_gemma":0.00004981307,"domain_scores_codex":[0.9989943,0.0001368553,0.0002761443,0.0001407767,0.0001956311,0.0002563038],"domain_scores_gemma":[0.9990052,0.0006032814,0.000017462,0.000181051,0.0001133947,0.00007962923],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004601441,0.00005466891,0.001175425,0.001845076,0.00005124553,0.00001374045,0.00109683,0.0002564021,0.04534417,0.001520237,0.003201687,0.9453945],"study_design_scores_gemma":[0.005039528,0.0001230764,0.04139195,0.0004981142,0.00006877869,0.00004118314,0.0005000408,0.1858415,0.2797904,0.01886676,0.466749,0.00108962],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2407142,0.006928641,0.7479294,0.0002839584,0.0008484052,0.000381895,0.0000231882,0.0001400646,0.0027503],"genre_scores_gemma":[0.1739398,0.0002893224,0.8251925,0.0001236897,0.0001158375,0.00008268082,0.00003759552,0.00002423955,0.0001944232],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9443049,"threshold_uncertainty_score":0.4494937,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01627184094607337,"score_gpt":0.378525836789286,"score_spread":0.3622539958432126,"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."}}