{"id":"W2885201665","doi":"10.1111/mec.14832","title":"<scp>DNA</scp> metabarcoding reveals changes in the contents of carnivorous plants along an elevation gradient","year":2018,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Plant and Biological Electrophysiology Studies","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Biology; Invertebrate; Abiotic component; Ecology; Trophic level; Species richness; Range (aeronautics); Predation; Carnivorous plant; DNA barcoding; Environmental gradient; Habitat","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":[0.0005787323,0.0007464738,0.0007786879,0.004647357,0.0006551076,0.0008654229,0.0009336567,0.0008968936,0.01973208],"category_scores_gemma":[0.002838246,0.0003235275,0.0006010383,0.005251705,0.0005155167,0.0003939675,0.0006155469,0.0009879622,0.004946296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004035344,"about_ca_system_score_gemma":0.0005474563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003216094,"about_ca_topic_score_gemma":0.01008717,"domain_scores_codex":[0.9994485,0.00007654358,0.00008078355,0.0001793019,0.0001675355,0.00004735353],"domain_scores_gemma":[0.997368,0.0009220336,0.0009946981,0.0002190869,0.0003003096,0.0001958526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001564918,0.0002571751,0.04685782,0.005571158,0.001065326,0.006614264,0.00125017,0.0021653,0.7211839,0.004437427,0.1147999,0.09423253],"study_design_scores_gemma":[0.0003436625,0.0004439068,0.6728743,0.0006802914,0.0006586923,0.004653546,0.0005615876,0.01032132,0.07374267,0.003884597,0.2315681,0.0002673309],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.236337,0.002491657,0.03361481,0.003987505,0.0009732582,0.0005769714,0.6803843,0.006736941,0.03489752],"genre_scores_gemma":[0.389713,0.00211604,0.1459168,0.00445727,0.0008965028,0.001283224,0.4384358,0.002740655,0.01444073],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01973208,"threshold_uncertainty_score":0.06601042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02925167401157386,"score_gpt":0.2305591506789142,"score_spread":0.2013074766673404,"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."}}