{"id":"W4284709094","doi":"10.1126/science.add0829","title":"Hearts by design","year":2022,"lang":"en","type":"letter","venue":"Science","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ted Rogers Centre for Heart Research; Toronto Rehabilitation Institute; University of Toronto","funders":"","keywords":"Computational biology; Computer science; Biology","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":[0.0004532814,0.0003006072,0.0002206537,0.0001881632,0.0003183878,0.001028022,0.0004918625,0.001474039,0.004093173],"category_scores_gemma":[0.0006552485,0.000280802,0.000275568,0.00009889645,0.0006420635,0.0008048928,0.0008180053,0.001708911,0.003320347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005586577,"about_ca_system_score_gemma":0.0002322528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001387676,"about_ca_topic_score_gemma":0.0004300507,"domain_scores_codex":[0.9996799,0.00003098929,0.00001597324,0.000050702,0.000185952,0.00003649553],"domain_scores_gemma":[0.9997606,0.00006950399,0.00003344201,0.00005370616,0.00005097469,0.00003170511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001454234,0.00006960003,0.0003980374,0.0004970339,0.00002986494,0.0008085461,0.0002154194,0.002444326,0.5802615,0.07097665,0.1246536,0.2195001],"study_design_scores_gemma":[0.00005537396,0.00028542,0.0004425658,0.00007425347,0.00001687294,0.001429611,0.00005679794,0.01604604,0.2008283,0.0127617,0.7679605,0.00004272228],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"commentary","genre_scores_codex":[0.06276692,0.03143255,0.5866496,0.05360437,0.0227946,0.000419472,0.0006830902,0.004840567,0.2368089],"genre_scores_gemma":[0.5483872,0.01327536,0.2543198,0.02441643,0.002892527,0.0007968399,0.0004557545,0.0007126572,0.1547435],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.004093173,"threshold_uncertainty_score":0.01369303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03329833901574445,"score_gpt":0.2825018434282281,"score_spread":0.2492035044124837,"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."}}