{"id":"W4318999647","doi":"10.1016/j.bprint.2023.e00260","title":"In situ 3D bioprinting: A promising technique in advanced biofabrication strategies","year":2023,"lang":"en","type":"article","venue":"Bioprinting","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria; University of Saskatchewan; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada","keywords":"Biofabrication; 3D bioprinting; Regenerative medicine; In situ; Transplantation; Regeneration (biology); Tissue engineering; Computer science; Nanotechnology; Biomedical engineering; Engineering; Materials science; Medicine; Stem cell; Biology; Chemistry; Surgery","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":[0.001536581,0.0002026757,0.0002369568,0.001031361,0.00005311904,0.000117474,0.000366359,0.0001915409,0.00002596433],"category_scores_gemma":[0.0005744178,0.0002245532,0.00004424566,0.0026844,0.00007544096,0.000328259,0.0002484449,0.0005715243,0.0001910188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002183415,"about_ca_system_score_gemma":0.00006186445,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009579056,"about_ca_topic_score_gemma":0.0000516823,"domain_scores_codex":[0.9979295,0.00005212469,0.0005349467,0.0003988627,0.0003342738,0.0007503279],"domain_scores_gemma":[0.9993158,0.0001661607,0.00005626872,0.0003346668,0.0000435428,0.00008353926],"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":[0.000004709078,0.00002323725,0.008639285,0.0002681888,0.000005481803,0.00004249588,0.0003222499,0.002299367,0.95,0.0005252642,0.0000191197,0.03785059],"study_design_scores_gemma":[0.0009211543,0.00003908665,0.2332964,0.001245494,0.000004029983,0.00001792402,0.001399113,0.07819252,0.6770416,0.002898152,0.004096369,0.0008481679],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848073,0.0000556019,0.004116006,0.0002306259,0.0001705592,0.0005936885,8.089696e-7,0.001019588,0.009005882],"genre_scores_gemma":[0.9871907,0.00006481461,0.01232304,0.000009446895,0.00006841717,0.0002083408,0.000005942542,0.00005411244,0.0000751494],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2729584,"threshold_uncertainty_score":0.9157015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01918417706213177,"score_gpt":0.3038508304951074,"score_spread":0.2846666534329756,"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."}}