{"id":"W6993035625","doi":"","title":"Neointimal cell origin in allograft arteriosclerosis","year":2000,"lang":"en","type":"other","venue":"Library and Archives Canada (Government of Canada)","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Arteriosclerosis; Cell; Transplantation; Disease; Cell culture","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0000115992,0.0002624274,0.0003586859,0.00007685822,0.00004960339,0.00005731289,0.000639886,0.00005735442,0.0001737618],"category_scores_gemma":[6.480875e-7,0.0002604791,0.00003625268,0.0001372257,0.00005319897,0.000233648,0.0001752283,0.0001944188,1.042622e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004197263,"about_ca_system_score_gemma":0.001154197,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007769519,"about_ca_topic_score_gemma":0.02599526,"domain_scores_codex":[0.9978089,0.0001231807,0.0002634809,0.0003920024,0.001061263,0.0003511753],"domain_scores_gemma":[0.999193,0.0001197805,0.0001468174,0.0003607433,1.200639e-7,0.0001795888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005571535,0.0003299772,0.009924142,0.001451887,0.0002809093,0.002132828,0.0006467384,0.0001783082,0.06122915,0.05449012,0.6344844,0.2342944],"study_design_scores_gemma":[0.0008183555,0.00008411874,0.007531798,0.0004376307,0.00001494979,0.000007178148,0.00007073818,0.002554494,0.01753716,0.0008285352,0.969457,0.0006580953],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003645371,0.0004260142,0.003438383,0.0008263165,0.0002587172,0.0001350495,0.00007281797,0.00002854407,0.9944496],"genre_scores_gemma":[0.03802773,0.0007911108,0.08176243,0.003191022,0.0001626163,0.00001276409,0.00001037505,0.0001922272,0.8758497],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3349725,"threshold_uncertainty_score":0.9999847,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004361096048982754,"score_gpt":0.1565607311608731,"score_spread":0.1521996351118903,"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."}}