{"id":"W2131525177","doi":"10.1186/1471-2164-13-274","title":"Defining new criteria for selection of cell-based intestinal models using publicly available databases","year":2012,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Cancer Cells and Metastasis","field":"Medicine","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université de Lausanne; Université de Genève; RIKEN; Oncosuisse; Institute for Oil Sands Innovation, University of Alberta; University of Bern; Helsingin Yliopisto; Universidad Nacional de La Plata; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Cell culture; Biology; Phenotype; Intestinal epithelium; Database; Epithelial–mesenchymal transition; Epithelium; Computational biology; Bioinformatics; Cancer research; Gene; Genetics; Downregulation and upregulation; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002911391,0.0001069027,0.000218234,0.00009602212,0.00005032287,0.00001570342,0.00004548228,0.00003127971,0.0002509119],"category_scores_gemma":[0.00007423975,0.0001081441,0.00008273986,0.0001232181,0.00001773132,0.0001747231,0.00002632638,0.00005763135,0.000007232629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001284196,"about_ca_system_score_gemma":0.000799392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001020636,"about_ca_topic_score_gemma":0.0001106155,"domain_scores_codex":[0.9992231,0.00001549952,0.0002362274,0.0001645252,0.0000873399,0.0002732896],"domain_scores_gemma":[0.9993523,0.0000710165,0.0001271814,0.0001853644,0.0001092685,0.0001548997],"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":[0.00124905,0.0004696572,0.0495728,0.001444295,0.00005602454,4.667214e-7,0.0003462395,0.008387939,0.9174784,0.000855391,0.01694648,0.003193205],"study_design_scores_gemma":[0.002680716,0.0002293087,0.0002136228,0.0001199882,0.0004882586,0.00004106342,0.0001876218,0.1813791,0.7838699,0.00005835024,0.03048983,0.0002422423],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4547173,0.001129965,0.5427759,0.0000181561,0.0002257668,0.00028621,0.00006889291,0.0000241013,0.000753633],"genre_scores_gemma":[0.4725071,0.00001379038,0.5266868,0.0000999933,0.0002458418,0.000007284998,0.00008330891,0.00002612604,0.0003296751],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1729912,"threshold_uncertainty_score":0.4409989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1686903902787067,"score_gpt":0.3361731869211504,"score_spread":0.1674827966424437,"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."}}