{"id":"W2965112455","doi":"10.3390/mi10080501","title":"3D Printing Breast Tissue Models: A Review of Past Work and Directions for Future Work","year":2019,"lang":"en","type":"review","venue":"Micromachines","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Innovate BC","keywords":"Tissue engineering; Breast cancer; 3D bioprinting; Work (physics); Computer science; Biomedical engineering; Biochemical engineering; Engineering; Medicine; Cancer; Mechanical engineering","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":[0.0006311691,0.0004477152,0.001648693,0.0002151988,0.00006942842,0.00004478105,0.0004178071,0.0003248734,0.00004521991],"category_scores_gemma":[0.0001172946,0.0003505558,0.0003099271,0.0008517877,0.00007339958,0.00006029851,0.0002208133,0.0005973442,0.00002298815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006447605,"about_ca_system_score_gemma":0.00005589494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005704096,"about_ca_topic_score_gemma":0.000001362646,"domain_scores_codex":[0.9981312,0.00009158009,0.0007284675,0.0004063596,0.0002290326,0.0004133465],"domain_scores_gemma":[0.9986579,0.0004504216,0.000171752,0.0004981459,0.0001006665,0.0001210957],"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":[0.000001123418,0.00001109329,0.00001252731,0.2483111,0.0001183492,7.619995e-7,0.00001636667,0.000003910012,0.000002113575,0.00001583851,0.002143875,0.7493629],"study_design_scores_gemma":[0.00006490435,0.000008828072,0.00002377104,0.138198,0.0002750319,0.0000353002,0.000001395934,0.00005498728,0.000001144333,0.00001304864,0.8610502,0.0002733642],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00001321782,0.9960916,0.0009649123,0.0001018941,0.0005907856,0.0014545,0.0001358664,0.0001674796,0.0004797533],"genre_scores_gemma":[0.000006115957,0.9927981,0.005603254,0.00001333913,0.0007033605,0.0002260838,0.000109141,0.0001370886,0.0004034876],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8589064,"threshold_uncertainty_score":0.9998946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03780718646518786,"score_gpt":0.3326897294163928,"score_spread":0.2948825429512049,"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."}}