{"id":"W4362541656","doi":"10.1158/1538-7445.am2023-168","title":"Abstract 168: Esophageal adenocarcinoma-on-a-chip; modeling patient specific disease progression and a step towards functional precision oncology","year":2023,"lang":"en","type":"article","venue":"Cancer Research","topic":"Cancer Cells and Metastasis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal General Hospital; McGill University","funders":"","keywords":"Docetaxel; Stromal cell; Cancer research; Medicine; Esophageal cancer; Organoid; Adenocarcinoma; Cancer; Chemotherapy; Pathology; Oncology; Internal medicine; Biology; Cell biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002246801,0.0003629634,0.0003237755,0.00009910687,0.00008158193,0.0003791125,0.0004796396,0.0004323579,0.0009838927],"category_scores_gemma":[0.0002724851,0.0001704775,0.0003926344,0.0001214046,0.0001451249,0.0001956654,0.0002497382,0.0004065208,0.0002905983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002743233,"about_ca_system_score_gemma":0.000310004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001852942,"about_ca_topic_score_gemma":0.001863894,"domain_scores_codex":[0.9999062,0.00001794447,0.000004144732,0.00002924587,0.00003033029,0.00001220254],"domain_scores_gemma":[0.9999138,0.00003147298,0.00001375197,0.00001283505,0.00001993372,0.000008199404],"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":[0.0002096699,0.0001786669,0.004140022,0.0005999846,0.0001184891,0.0002524891,0.00008371017,0.3416335,0.6067275,0.00448546,0.003107431,0.03846312],"study_design_scores_gemma":[0.00002114912,0.0003999665,0.002874441,0.00001904584,0.00006372095,0.0001951846,0.00003173352,0.8303792,0.1521627,0.00103969,0.01278222,0.00003090564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4577027,0.003135891,0.5257425,0.0006578343,0.0003535872,0.0001975757,0.002726304,0.001645401,0.007838206],"genre_scores_gemma":[0.8786647,0.00172373,0.1132156,0.000200433,0.00004105019,0.0002413402,0.001472616,0.00009378218,0.004346794],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001852942,"threshold_uncertainty_score":0.003684282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1721593685825923,"score_gpt":0.4357737182193671,"score_spread":0.2636143496367748,"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."}}