{"id":"W2981762363","doi":"10.1016/j.biomaterials.2019.119572","title":"Gels for Live Analysis of Compartmentalized Environments (GLAnCE): A tissue model to probe tumour phenotypes at tumour-stroma interfaces","year":2019,"lang":"en","type":"article","venue":"Biomaterials","topic":"Cancer Cells and Metastasis","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Stroma; Stromal cell; Paracrine signalling; Biology; Cell biology; Tumor microenvironment; Cancer cell; Cell; Phenotype; Tumour heterogeneity; Cancer research; Cancer; Immunology; Tumor cells; Genetics; Gene; Immunohistochemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009580087,0.001427817,0.0003633202,0.002026424,0.001037181,0.001261355,0.0008539464,0.001128246,0.009642664],"category_scores_gemma":[0.0004365206,0.0008459642,0.0005103542,0.0008026023,0.0007165489,0.001155194,0.0008699441,0.001803766,0.002675419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004165195,"about_ca_system_score_gemma":0.000519051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001621405,"about_ca_topic_score_gemma":0.005225271,"domain_scores_codex":[0.9994973,0.0001102107,0.00004614315,0.0001427826,0.0001246728,0.00007901427],"domain_scores_gemma":[0.9993943,0.0002178163,0.0001313645,0.000124709,0.00008083536,0.00005086571],"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":[0.00009518275,0.00003670035,0.0001700167,0.0002047348,0.00001494545,0.0001411903,0.0001949006,0.0002209809,0.9903722,0.00195442,0.0006097488,0.005984853],"study_design_scores_gemma":[0.00004333257,0.0001194271,0.002644799,0.00008535795,0.00008359457,0.0009992787,0.0001462839,0.007215707,0.9592525,0.001160938,0.02818727,0.0000615154],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3209274,0.006150268,0.6281413,0.001436722,0.0004080236,0.000564334,0.00587762,0.0123436,0.02415073],"genre_scores_gemma":[0.2944076,0.005067915,0.658155,0.0004757284,0.0001174753,0.001317882,0.003846133,0.004892639,0.03171973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009642664,"threshold_uncertainty_score":0.03225791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03122378778061608,"score_gpt":0.3103776267385666,"score_spread":0.2791538389579505,"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."}}