{"id":"W2791956807","doi":"10.1002/adhm.201701174","title":"The Current Landscape of 3D In Vitro Tumor Models: What Cancer Hallmarks Are Accessible for Drug Discovery?","year":2018,"lang":"en","type":"review","venue":"Advanced Healthcare Materials","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Drug discovery; Context (archaeology); Cancer; Disease; Clinical trial; Drug development; Cancer drugs; Identification (biology); Computational biology; Tumor microenvironment; Biology; Medicine; Bioinformatics; Drug; Data science; Computer science; Pharmacology; Pathology; Internal medicine","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":[0.001293422,0.0004757455,0.001850659,0.0002164935,0.00012949,0.0002987124,0.0009381567,0.0001856502,0.0000207573],"category_scores_gemma":[0.0002558356,0.0003217451,0.0001798405,0.0003695722,0.0001229999,0.0006046506,0.0002702028,0.0004651437,0.000007629012],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003873747,"about_ca_system_score_gemma":0.0004702074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001352604,"about_ca_topic_score_gemma":0.0003825278,"domain_scores_codex":[0.9964263,0.0002808782,0.001403487,0.0005207407,0.000458498,0.0009100856],"domain_scores_gemma":[0.9975635,0.0008770094,0.0005153505,0.0006908021,0.0001973102,0.0001559702],"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":[0.00006353336,0.00001474066,8.381637e-7,0.09060724,0.0000391377,0.000001801645,0.00005285854,0.00009002633,0.00005979658,0.00004643663,0.0003301308,0.9086934],"study_design_scores_gemma":[0.0004682959,0.00003618225,0.000006479852,0.08516443,0.00006938015,0.000002373688,0.00008443803,0.000577268,0.001983606,0.001362068,0.9096602,0.0005853207],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0005419665,0.9914044,0.0001875523,0.0001793446,0.004268628,0.002252742,0.00106741,0.00008099061,0.00001701863],"genre_scores_gemma":[0.001184672,0.9945336,0.0005358288,0.00001832593,0.0005409804,0.002784835,0.0002072545,0.0001467153,0.00004776758],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.90933,"threshold_uncertainty_score":0.9999235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07189689545766036,"score_gpt":0.4114860451520324,"score_spread":0.339589149694372,"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."}}