{"id":"W2096786076","doi":"10.1111/ecog.00983","title":"Predicting ecosystem functions from biodiversity and mutualistic networks: an extension of trait‐based concepts to plant–animal interactions","year":2014,"lang":"en","type":"article","venue":"Ecography","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":339,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ministerio de Economía y Competitividad; Deutsche Forschungsgemeinschaft","keywords":"Biodiversity; Ecosystem; Ecology; Ecological network; Biological dispersal; Species richness; Trait; Biology; Ecosystem services; Trophic level; Environmental resource management; Environmental science; Computer science; Population; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009233336,0.00008891684,0.0001495466,0.00002318742,0.0003018267,0.00002680259,0.00007261001,0.00003557771,0.00006598046],"category_scores_gemma":[0.00002519725,0.00004065809,0.00006160373,0.0001901579,0.00003508534,0.0000801729,0.00003608166,0.00005788112,0.000004674697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003720799,"about_ca_system_score_gemma":0.000001057659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007505951,"about_ca_topic_score_gemma":0.01342227,"domain_scores_codex":[0.9993924,0.00005825836,0.0001269347,0.0002176589,0.00007318429,0.0001315497],"domain_scores_gemma":[0.9994874,0.0002942845,0.00006473157,0.00002093717,0.00003808407,0.00009453727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002611716,0.0001495828,0.898828,0.000009210897,0.00005807157,0.000002660544,0.0003163237,0.00009078342,0.09016182,0.00004740958,0.002515309,0.007559671],"study_design_scores_gemma":[0.0001054186,0.0004873442,0.9913626,0.00004525909,0.00003225213,0.000001462305,0.0008369378,0.003476404,0.0001404367,0.00001324134,0.003395245,0.0001033668],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979567,0.0000431828,0.00005820995,0.0001530107,0.0001035237,0.00008597071,0.001431765,0.00005440213,0.0001132505],"genre_scores_gemma":[0.9994711,0.00000513382,0.00005780955,0.0001010586,0.0001799311,0.000003505604,0.0001785033,3.742317e-7,0.000002599777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09253465,"threshold_uncertainty_score":0.7489941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03719125108245164,"score_gpt":0.212455004703983,"score_spread":0.1752637536215314,"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."}}