{"id":"W4251374370","doi":"10.1063/1.4971157.1","title":"10.1063/1.4971157.1","year":2016,"lang":"en","type":"dataset","venue":"Default Digital Object Group","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":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; University of Toronto; York University","funders":"","keywords":"Biology; Orientation (vector space); Electrophysiology; Microinjection; Microfluidics; Caenorhabditis elegans; Neuroscience; Anatomy; Computer science; Cell biology; Nanotechnology; Materials science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001586839,0.0007504137,0.0005442768,0.0001386777,0.0001353859,0.000331262,0.001007208,0.0009184715,0.001129157],"category_scores_gemma":[0.0002535436,0.0006474322,0.0004139684,0.0001090601,0.000240799,0.00001743397,0.000632278,0.0003019217,0.004237922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005152501,"about_ca_system_score_gemma":0.000149214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004557854,"about_ca_topic_score_gemma":0.0001165258,"domain_scores_codex":[0.9970474,0.00005823759,0.0005293306,0.00112586,0.000471491,0.0007677007],"domain_scores_gemma":[0.9976235,0.00003516528,0.0002830871,0.001628312,0.0001484176,0.0002814943],"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":[0.0000755658,0.0001518136,0.00001623541,0.00008424807,0.0001688237,0.00003338111,0.00001101378,0.000002895631,0.002126367,0.000003273127,0.9941344,0.003192017],"study_design_scores_gemma":[0.0006115119,0.0006713263,0.00004903278,0.00005819418,0.00007921881,0.00007078322,0.00001163749,0.000001703285,0.002539121,0.0001103743,0.9948721,0.0009250183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001518506,0.0009679068,0.0004457175,0.00005856673,0.0006974944,0.0003667592,0.9921399,0.00005481011,0.003750276],"genre_scores_gemma":[0.008559487,0.000458463,0.00005311506,0.000408616,0.001707873,0.00004962338,0.9720768,0.0001164877,0.01656954],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02006317,"threshold_uncertainty_score":0.9997839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006915107904809705,"score_gpt":0.226024410437391,"score_spread":0.2191093025325813,"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."}}