{"id":"W4413781125","doi":"10.1371/journal.pone.0331188","title":"VNC-Dist: A machine learning-based semi-automated pipeline for quantification of neuronal position in the C. elegans ventral nerve cord","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; Canadian Institutes of Health Research; University of Ottawa","keywords":"Ventral nerve cord; Connectomics; Biology; Segmentation; Computer science; Spinal cord; Software; Artificial intelligence; Anatomy; Neuroscience; Connectome; Nervous system; Functional connectivity","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":[0.001250355,0.001822362,0.001111803,0.002044325,0.0006659949,0.001146197,0.002213606,0.001137557,0.006848644],"category_scores_gemma":[0.002910786,0.001062209,0.001431674,0.00100628,0.0005540882,0.0009554633,0.002082838,0.001781234,0.004010299],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001011635,"about_ca_system_score_gemma":0.002081682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005968844,"about_ca_topic_score_gemma":0.01481354,"domain_scores_codex":[0.9992923,0.00007473517,0.0000539129,0.000264385,0.0002449993,0.00006960559],"domain_scores_gemma":[0.999046,0.000385431,0.0001445191,0.0001473279,0.0001902329,0.00008656664],"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":[0.0009074459,0.0002581518,0.009192751,0.001609081,0.0007680967,0.000468809,0.0004337539,0.07774687,0.1950551,0.007478634,0.09324487,0.6128364],"study_design_scores_gemma":[0.0001108768,0.0001579707,0.008955446,0.00008223937,0.00006495348,0.0003115835,0.00007385133,0.8899485,0.07311974,0.007637933,0.0193587,0.0001781536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01631234,0.000243814,0.8117387,0.0001171178,0.00006789008,0.0001444762,0.008234874,0.1621695,0.0009711937],"genre_scores_gemma":[0.06955571,0.0002124392,0.9051446,0.0001943918,0.00002222641,0.0008672138,0.0139567,0.007969876,0.002076704],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006848644,"threshold_uncertainty_score":0.02291095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02243441169072565,"score_gpt":0.2541771390989844,"score_spread":0.2317427274082587,"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."}}