{"id":"W2616861674","doi":"10.71781/32146","title":"ALCAM : cell adhesion molecule or tight junction? The characterization of its role in the context of neuroinflammation","year":2016,"lang":"en","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Neuroinflammation and Neurodegeneration Mechanisms","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Schweizerische Multiple Sklerose Gesellschaft; Canadian Institutes of Health Research; Eidgenössische Technische Hochschule Zürich; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Fonds de Recherche du Québec - Santé; Multiple Sclerosis Society of Canada; European Commission; Multiple Sclerosis Society; University of Bern; National Science Foundation","keywords":"Neuroinflammation; ALCAM; Context (archaeology); Cell adhesion molecule; Neuroscience; Characterization (materials science); Psychology; Materials science; Medicine; Inflammation; Nanotechnology; Immunology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001032986,0.0004032743,0.0006006669,0.0007698631,0.0004889367,0.001755467,0.000537584,0.001284892,0.001903486],"category_scores_gemma":[0.001117202,0.0002021913,0.0003709882,0.001002597,0.0009264413,0.001854675,0.0006782745,0.00131996,0.0008328807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004800469,"about_ca_system_score_gemma":0.0006621372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007921725,"about_ca_topic_score_gemma":0.001046203,"domain_scores_codex":[0.9992149,0.000190529,0.00007088819,0.000145916,0.0002422699,0.0001355084],"domain_scores_gemma":[0.9994485,0.0001428249,0.0001299877,0.00007109272,0.0001424152,0.00006522565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002713197,0.00005572418,0.003116176,0.001009097,0.00005313588,0.0003855823,0.000234999,0.0001190775,0.9660044,0.003116709,0.0003898869,0.0252439],"study_design_scores_gemma":[0.00005413823,0.0009297692,0.02954731,0.0004804237,0.0002644373,0.004089492,0.001325011,0.002153476,0.8881834,0.005612273,0.06727795,0.00008232155],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7473512,0.1817502,0.04688269,0.008113325,0.001386935,0.000356719,0.0009993383,0.000203341,0.01295628],"genre_scores_gemma":[0.902676,0.05832848,0.02220079,0.002665172,0.0005653682,0.0003728881,0.0008508398,0.00005405469,0.01228638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001903486,"threshold_uncertainty_score":0.006367743,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008544342630336703,"score_gpt":0.1826841222866292,"score_spread":0.1741397796562925,"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."}}