{"id":"W2953831863","doi":"10.1080/23746149.2019.1622451","title":"Advanced bioengineering technologies for preclinical research","year":2019,"lang":"en","type":"article","venue":"Advances in Physics X","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's Hospital of Eastern Ontario; University of Ottawa","funders":"H2020 European Research Council; Natural Sciences and Engineering Research Council of Canada; Generalitat de Catalunya; European Commission; University of Ottawa","keywords":"Human health; Computer science; Drug discovery; Risk analysis (engineering); Nanotechnology; Human disease; Data science; Biochemical engineering; Engineering ethics; Biology; Engineering; Disease; Medicine; Bioinformatics; Pathology; Materials science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006620262,0.0001213348,0.0002048059,0.0001484869,0.00003004361,0.00002088403,0.0004793029,0.0001128294,0.000009018524],"category_scores_gemma":[0.0006410175,0.0001202767,0.00004825621,0.0007116279,0.0001470055,0.000312303,0.0001503887,0.0006276921,0.0001039266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001028619,"about_ca_system_score_gemma":0.00002024247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.421967e-7,"about_ca_topic_score_gemma":0.000002007317,"domain_scores_codex":[0.9984977,0.00001882608,0.0002348025,0.0002862738,0.0003525295,0.0006098184],"domain_scores_gemma":[0.9981827,0.001278655,0.0000143246,0.0004053732,0.0000775825,0.00004141039],"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":[0.00002884796,0.00004910979,0.001903307,0.0006663282,0.00001414342,0.000002118407,0.00005743076,0.08432452,0.01894212,0.0142781,0.0001378492,0.8795961],"study_design_scores_gemma":[0.001824885,0.0003960722,0.0005738822,0.0007132925,0.000003688527,0.000001462538,0.0004400638,0.2952482,0.1466305,0.1568155,0.3966587,0.0006938038],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7138888,0.03744329,0.1603398,0.001045377,0.006475539,0.00635806,0.00006711781,0.006354004,0.06802807],"genre_scores_gemma":[0.9749371,0.002191304,0.02229266,0.00000472888,0.000131163,0.0002636461,0.000005754366,0.00004959937,0.0001239952],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8789023,"threshold_uncertainty_score":0.490474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04618518798862048,"score_gpt":0.4078539097927861,"score_spread":0.3616687218041656,"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."}}