{"id":"W6939460859","doi":"10.6084/m9.figshare.19092517","title":"Additional file 1 of MORPHIOUS: an unsupervised machine learning workflow to detect the activation of microglia and astrocytes","year":2022,"lang":"en","type":"article","venue":"Open MIND","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Workflow; Microglia; Artificial neural network; Unsupervised learning; Deep learning","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":[0.001379674,0.001939378,0.001514242,0.002143538,0.001090256,0.001960435,0.002162304,0.001438187,0.7370312],"category_scores_gemma":[0.01354981,0.0008871391,0.001360952,0.002400598,0.0004158891,0.001489037,0.001400834,0.001493975,0.2022354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008961282,"about_ca_system_score_gemma":0.001621533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004857908,"about_ca_topic_score_gemma":0.009622926,"domain_scores_codex":[0.9993737,0.00009106779,0.00008326762,0.0002120411,0.0001552049,0.00008469553],"domain_scores_gemma":[0.993647,0.00439453,0.0003220318,0.0005322417,0.0008569428,0.0002470607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005806753,0.0001122583,0.002168484,0.002521348,0.00007169251,0.0001505713,0.0000794149,0.001160827,0.001500483,0.0008315799,0.9773401,0.01348255],"study_design_scores_gemma":[0.002830405,0.000295931,0.01658661,0.001630753,0.0002954009,0.0009133703,0.0003434782,0.009466509,0.01069835,0.02094197,0.9357125,0.0002847852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.0004100265,0.00005974491,0.003450638,0.000107626,0.00006315998,0.0001137197,0.987532,0.00683128,0.001431799],"genre_scores_gemma":[0.009816324,0.0002098565,0.02363221,0.0005859027,0.0001340982,0.001838052,0.9424572,0.01253949,0.00878697],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7370312,"threshold_uncertainty_score":0.375093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04018940554878828,"score_gpt":0.2594455411652259,"score_spread":0.2192561356164376,"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."}}