{"id":"W2989581600","doi":"10.1101/857854","title":"PhenoMIP: High Throughput Phenotyping of Diverse <i>C. elegans</i> Populations via Molecular Inversion Probes","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetics, Aging, and Longevity in Model Organisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; National Institutes of Health","keywords":"Biology; Caenorhabditis elegans; Genetics; Computational biology; Mutant; Gene; Genome; Population; Genetic Fitness","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":[0.0008861916,0.0007228116,0.0005827836,0.001384413,0.0005911387,0.0008551161,0.0008935026,0.000604614,0.001931851],"category_scores_gemma":[0.0008778969,0.0003735869,0.0005527671,0.0005964098,0.000538657,0.0004626756,0.001757528,0.001331066,0.0006505954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004692927,"about_ca_system_score_gemma":0.0002746693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008843947,"about_ca_topic_score_gemma":0.002722559,"domain_scores_codex":[0.9993163,0.00007540587,0.0000494338,0.00024833,0.0002286561,0.00008191165],"domain_scores_gemma":[0.9992472,0.0002216643,0.0002203571,0.0001270015,0.00008182463,0.0001019414],"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":[0.0000700891,0.00004289261,0.003976878,0.00006691094,0.00003789211,0.0000597141,0.00005914355,0.0006487585,0.9810411,0.0004486693,0.0003712469,0.01317678],"study_design_scores_gemma":[0.00003117767,0.0005314861,0.04298672,0.00002834799,0.00008246184,0.0006655161,0.0001793193,0.02298804,0.9221895,0.001266982,0.00895848,0.00009190392],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5143628,0.0007222005,0.4682136,0.0003251567,0.00006733366,0.0008471593,0.005690277,0.005766061,0.004005424],"genre_scores_gemma":[0.6051109,0.0005605863,0.3813428,0.0004977803,0.00003811105,0.002202797,0.004392401,0.001030174,0.004824443],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001931851,"threshold_uncertainty_score":0.006462693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01263526827322588,"score_gpt":0.21212055452756,"score_spread":0.1994852862543341,"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."}}