{"id":"W3115106661","doi":"10.1371/journal.pone.0244549","title":"Carboplatin sensitivity in epithelial ovarian cancer cell lines: The impact of model systems","year":2020,"lang":"en","type":"article","venue":"PLoS ONE","topic":"3D Printing in Biomedical Research","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal; Centre Hospitalier de l’Université de Montréal","funders":"Institute of Cancer Research; Fonds de Recherche du Québec - Santé; Canada First Research Excellence Fund; Cancer Research Society; Mitacs; Canadian Cancer Society Research Institute; Ovarian Cancer Canada","keywords":"Carboplatin; Spheroid; Cell culture; Flow cytometry; 3D cell culture; Cancer research; Ovarian cancer; Drug; Medicine; Oncology; Cancer; Biology; Internal medicine; Immunology; Pharmacology; Chemotherapy; Cisplatin; Genetics","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":[0.0003231151,0.00009389086,0.0002220876,0.000027008,0.00001438303,0.00001430722,0.0001302407,0.00007149058,0.0000288596],"category_scores_gemma":[0.0001856796,0.00006726886,0.00004300142,0.0002177719,0.0000372963,0.00003739125,0.00005912167,0.0002912291,0.00001133055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001174058,"about_ca_system_score_gemma":0.0000791263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00479356,"about_ca_topic_score_gemma":0.0001162426,"domain_scores_codex":[0.9990513,0.00005814011,0.0002005255,0.0001156206,0.0003472955,0.0002271048],"domain_scores_gemma":[0.9994819,0.0001721701,0.00002540032,0.000167824,0.00004986628,0.0001028237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001730017,0.0000987608,0.003181786,0.0003949495,0.00008617226,0.000006234368,0.0007589906,0.4261618,0.5690594,0.000010519,0.00006536156,0.0001586705],"study_design_scores_gemma":[0.0002005204,0.00002189078,0.003303872,0.0001151281,0.00001068495,1.634482e-7,0.00002786864,0.9427335,0.05350929,0.000009340892,0.000001125456,0.00006663587],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971328,0.0002381124,0.000918332,0.000233062,0.00002343715,0.0002358992,0.00007124904,0.00006447682,0.001082648],"genre_scores_gemma":[0.9993374,0.00009665379,0.0003239572,0.00000998286,0.0001647599,0.00001979329,0.000002164164,0.00002356633,0.00002172174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5165717,"threshold_uncertainty_score":0.7246461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07475281238679342,"score_gpt":0.2828448602030896,"score_spread":0.2080920478162962,"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."}}