{"id":"W2050104639","doi":"10.1111/eva.12031","title":"From forest and agro‐ecosystems to the microecosystems of the human body: what can landscape ecology tell us about tumor growth, metastasis, and treatment options?","year":2012,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Mathematical Biology Tumor Growth","field":"Mathematics","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Fondation Fyssen; Agence Nationale de la Recherche","keywords":"Biology; Ecology; Metastasis; Competition (biology); Multicellular organism; Evolutionary ecology; Tumor microenvironment; Cancer; Neuroscience; Cell","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":[0.0006912285,0.0003841822,0.0006391951,0.0007745912,0.0007095805,0.003271601,0.0006452359,0.001244137,0.002221661],"category_scores_gemma":[0.002924526,0.0002024608,0.0003452187,0.0009686804,0.005830542,0.006437907,0.001058982,0.001587949,0.0003378279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001114376,"about_ca_system_score_gemma":0.000740142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007196281,"about_ca_topic_score_gemma":0.007284127,"domain_scores_codex":[0.9997912,0.0001084008,0.000005823867,0.00003398725,0.00003382231,0.00002677543],"domain_scores_gemma":[0.9991885,0.0004712574,0.0001249301,0.00006362163,0.00007162087,0.00008005415],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001251271,0.00007148053,0.02083549,0.0009995874,0.0001960578,0.0005364482,0.002526703,0.01991279,0.001801103,0.7126858,0.01595553,0.2243539],"study_design_scores_gemma":[0.000007800159,0.00003734266,0.01459756,0.0003492223,0.00003299709,0.0003624327,0.002484197,0.005811213,0.0002534898,0.9229215,0.05310532,0.00003699635],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2224024,0.3754786,0.05716359,0.289576,0.002433575,0.00002010054,0.0005032545,0.0001438125,0.05227859],"genre_scores_gemma":[0.8600469,0.1183238,0.006753523,0.007966869,0.001771586,0.00002495762,0.0001166078,0.0000537832,0.004942037],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007196281,"threshold_uncertainty_score":0.01430881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982763697785465,"score_gpt":0.2704110143719288,"score_spread":0.2505833773940741,"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."}}