{"id":"W4389883177","doi":"10.1186/s42825-023-00142-6","title":"Collagen-based biomaterials in organoid technology for reproductive medicine: composition, characteristics, and applications","year":2023,"lang":"en","type":"article","venue":"Collagen and Leather","topic":"Tissue Engineering and Regenerative Medicine","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"Sichuan Province Science and Technology Support Program; Natural Science Foundation of Sichuan Province; National Natural Science Foundation of China","keywords":"Decellularization; Organoid; Context (archaeology); Biomedicine; Matrigel; Regenerative medicine; Biological materials; Biofabrication; Engineering ethics; Nanotechnology; Tissue engineering; Biomedical engineering; Computer science; Medicine; Biotechnology; Engineering; Biology; Stem cell; Bioinformatics; Cell biology; In vivo; Materials science","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":[0.0002352602,0.000118485,0.0003149934,0.0003270722,0.00008365767,0.000006831544,0.00003146309,0.00009235276,0.0000396594],"category_scores_gemma":[0.0001102167,0.00009128646,0.00001179774,0.0005496638,0.0002603052,0.00001182977,0.00001462453,0.00002173831,0.000008752024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002030864,"about_ca_system_score_gemma":0.00003215795,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005791086,"about_ca_topic_score_gemma":0.000001985848,"domain_scores_codex":[0.9992832,0.00001830259,0.0001942458,0.0002899413,0.00006479438,0.0001495438],"domain_scores_gemma":[0.9995686,0.00005427288,0.00003934003,0.0001815623,0.00009241013,0.00006376355],"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":[0.0001207667,0.00005768022,0.008300275,0.0003179003,0.0000478979,0.00002798134,0.0007034308,0.000006935016,0.9807311,0.00182309,0.003118434,0.004744519],"study_design_scores_gemma":[0.01573071,0.002121293,0.1919549,0.001096182,0.0004522385,0.0002610605,0.003190893,0.002214891,0.3089468,0.001039458,0.4721121,0.0008794298],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757978,0.003597846,0.003598177,0.01477664,0.0002244061,0.001626874,0.00004898457,0.0002280973,0.0001012221],"genre_scores_gemma":[0.9940706,0.0001388736,0.0006387165,0.0001032832,0.0005474341,0.0003769243,0.0001175536,0.00002969692,0.00397691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6717843,"threshold_uncertainty_score":0.3722554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01612232427673524,"score_gpt":0.2887516227122613,"score_spread":0.2726292984355261,"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."}}