{"id":"W4380738215","doi":"10.1002/adem.202201743","title":"Glass, Ceramic, Polymeric, and Composite Scaffolds with Multiscale Porosity for Bone Tissue Engineering","year":2023,"lang":"en","type":"article","venue":"Advanced Engineering Materials","topic":"Bone Tissue Engineering Materials","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Centre québécois sur les matériaux fonctionnels; Natural Sciences and Engineering Research Council of Canada; Faculty of Engineering, McGill University; McGill University","keywords":"Materials science; Porosity; Macropore; Scaffold; Tissue engineering; Composite number; Ceramic; Composite material; Bone tissue; Nanopore; Fabrication; Nanotechnology; Biomedical engineering; Mesoporous material; Chemistry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002585634,0.0006675922,0.0008525845,0.000333288,0.00009534747,0.0001782059,0.000218776,0.0001974111,0.00003123268],"category_scores_gemma":[0.00004195298,0.000713412,0.00005153362,0.0004340925,0.00003808192,0.0004187637,0.00009747274,0.0001008558,0.00005636662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001047118,"about_ca_system_score_gemma":0.00001005333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001847821,"about_ca_topic_score_gemma":0.0000019535,"domain_scores_codex":[0.9977013,0.00001279044,0.0005681046,0.0005148724,0.0002307803,0.0009721104],"domain_scores_gemma":[0.9990114,0.0001662219,0.00006932065,0.0004638187,0.00004807987,0.0002411345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002967118,0.000007461431,0.00001034568,0.0006683774,0.00006142754,0.00002564451,0.00008369083,0.3007163,0.6972042,0.0001325894,0.00009784841,0.0009624656],"study_design_scores_gemma":[0.001293242,0.0001240408,0.003812312,0.0002782863,0.00005708105,0.00009122702,0.00001351781,0.03374276,0.9535486,0.0000181382,0.006004684,0.001016174],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9659959,0.0006598502,0.02563689,0.0000501338,0.00176238,0.0008558136,0.0003085739,0.004711364,0.0000191115],"genre_scores_gemma":[0.9652436,0.0002072671,0.0329898,0.00001094422,0.0003088381,0.0004436444,0.0002024925,0.0004039931,0.0001894309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2669735,"threshold_uncertainty_score":0.9995317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004775978548190586,"score_gpt":0.2008574085367292,"score_spread":0.1960814299885386,"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."}}