{"id":"W3087756686","doi":"10.1242/dev.191213","title":"FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research","year":2020,"lang":"en","type":"review","venue":"Development","topic":"Cleft Lip and Palate Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Children's Hospital; University of Calgary","funders":"Lawrence Berkeley National Laboratory; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Dental and Craniofacial Research; Wellcome Trust; University of Pittsburgh; National Human Genome Research Institute; U.S. Department of Energy","keywords":"Interoperability; Craniofacial; Multidisciplinary approach; Biology; Visualization; Data sharing; Data science; Data management; Resource (disambiguation); Reusability; Computer science; World Wide Web; Database; Data mining","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":[],"consensus_categories":[],"category_scores_codex":[0.0006847431,0.0002464688,0.0005498924,0.0001058769,0.0002152353,0.0001470776,0.0001966829,0.0003081818,0.00001438592],"category_scores_gemma":[0.0002582385,0.000206043,0.0001073745,0.0001335975,0.0001598547,0.000002624967,0.0005138197,0.0002745978,0.00001756559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003396093,"about_ca_system_score_gemma":0.0004212529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002984751,"about_ca_topic_score_gemma":0.0000136821,"domain_scores_codex":[0.9982103,0.0001535089,0.0003209717,0.0006210456,0.0002930023,0.0004011809],"domain_scores_gemma":[0.9993194,0.0001283091,0.00004483325,0.0001629216,0.00007897243,0.0002655416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003444705,0.00002536774,0.000141941,0.00276392,0.0001507991,0.0000173073,0.00008783391,1.932704e-8,0.00003426061,0.00003417382,0.001498836,0.9952111],"study_design_scores_gemma":[0.0002396702,0.0001407354,0.0001995385,0.0004404669,0.0000381731,0.00003632656,0.00006085008,0.000004681877,0.00003411392,0.000005718801,0.9985605,0.000239236],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.005603563,0.9920944,0.00008502618,0.00009970845,0.00006507853,0.001330267,0.0001884389,0.00001014329,0.0005233868],"genre_scores_gemma":[0.0003427144,0.9971531,0.0006348719,0.00002923968,0.0002727519,0.0002015225,0.0004432211,0.00003804662,0.0008845177],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9970617,"threshold_uncertainty_score":0.8402189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1609189419495038,"score_gpt":0.4294368628367071,"score_spread":0.2685179208872033,"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."}}