{"id":"W3048607454","doi":"10.1002/ajhb.23468","title":"Using point clouds to investigate the relationship between trabecular bone phenotype and behavior: An example utilizing the human calcaneus","year":2020,"lang":"en","type":"article","venue":"American Journal of Human Biology","topic":"Bone health and osteoporosis research","field":"Medicine","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"H2020 European Research Council; Division of Behavioral and Cognitive Sciences; Biotechnology and Biological Sciences Research Council; Research Councils UK; Pennsylvania State University; University of Pennsylvania; National Science Foundation","keywords":"Calcaneus; Anisotropy; Trabecular bone; Volume fraction; Degree (music); Univariate; Volume (thermodynamics); Cancellous bone; Point (geometry); Anatomy; Mathematics; Statistics; Geology; Biology; Materials science; Geometry; Physics; Medicine; Multivariate statistics; Osteoporosis; Pathology; Optics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001023314,0.0004414727,0.000425285,0.002805328,0.0005316609,0.0009078718,0.0005086016,0.000714126,0.001018106],"category_scores_gemma":[0.003485875,0.0004168466,0.0005545595,0.003074361,0.0006579402,0.0004599976,0.0008056417,0.0003815863,0.0003493906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003004782,"about_ca_system_score_gemma":0.0007764727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01170238,"about_ca_topic_score_gemma":0.01776477,"domain_scores_codex":[0.9992751,0.0002216394,0.00003933271,0.0001199157,0.0003005186,0.00004345658],"domain_scores_gemma":[0.9982565,0.0009213227,0.0002210964,0.000250153,0.000308472,0.00004248124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001166593,0.0003269519,0.2394035,0.0007609854,0.0005486354,0.001489374,0.003356061,0.1063107,0.2226303,0.006826024,0.00150932,0.4156716],"study_design_scores_gemma":[0.0001095691,0.0004774017,0.3506589,0.0001393252,0.0002315432,0.003727159,0.00214614,0.5495718,0.07367732,0.01349286,0.00555983,0.0002082173],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5078617,0.0004953125,0.4866545,0.0002435952,0.0000347142,0.0002601648,0.0007291251,0.0007734086,0.002947388],"genre_scores_gemma":[0.7482307,0.0003757832,0.2503586,0.00002938884,0.00001767822,0.0001044521,0.0003029811,0.00008922642,0.0004912093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01170238,"threshold_uncertainty_score":0.02326852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2894464364290088,"score_gpt":0.4303742437547177,"score_spread":0.1409278073257089,"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."}}