{"id":"W4210274687","doi":"10.1186/s12974-021-02376-9","title":"MORPHIOUS: an unsupervised machine learning workflow to detect the activation of microglia and astrocytes","year":2022,"lang":"en","type":"article","venue":"Journal of Neuroinflammation","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"Canadian Institutes of Health Research; Canada Research Chairs; National Institute of Biomedical Imaging and Bioengineering; Canada Excellence Research Chairs, Government of Canada; Weston Brain Institute","keywords":"Microglia; Astrocyte; Neuroscience; Hippocampal formation; Glial fibrillary acidic protein; Nestin; Neuroinflammation; Biology; Chemistry; Pathology; Medicine; Cell biology; Central nervous system; Neural stem cell; Immunohistochemistry; Immunology; Stem cell; Inflammation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001936915,0.002017845,0.00110111,0.001991861,0.000865383,0.001537396,0.002360979,0.001456559,0.007596952],"category_scores_gemma":[0.003598469,0.0009894619,0.002125175,0.0007576297,0.0006977195,0.0008713208,0.001586927,0.001901176,0.003594758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008974629,"about_ca_system_score_gemma":0.002192543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004464063,"about_ca_topic_score_gemma":0.008323973,"domain_scores_codex":[0.999108,0.0001569913,0.0001003457,0.0003056048,0.0002360374,0.00009290125],"domain_scores_gemma":[0.9987503,0.0005288615,0.0001761491,0.0001507767,0.000311298,0.00008260795],"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":[0.001251607,0.0004311453,0.01007201,0.001605466,0.001047757,0.0009531365,0.0008954423,0.1240739,0.1476512,0.01118049,0.06762771,0.6332101],"study_design_scores_gemma":[0.0001208983,0.0001696773,0.003408621,0.00005545217,0.00006870415,0.0002926275,0.0001088778,0.9070281,0.05323742,0.01318603,0.02219845,0.0001250658],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007587259,0.000148715,0.9229715,0.0001322488,0.00005803491,0.0002467299,0.00234293,0.06570333,0.0008093068],"genre_scores_gemma":[0.04679646,0.0001502519,0.9405773,0.000200724,0.00003577539,0.001227596,0.004420323,0.004816205,0.001775466],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007596952,"threshold_uncertainty_score":0.02541429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02706335776572621,"score_gpt":0.245049166383932,"score_spread":0.2179858086182058,"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."}}