{"id":"W2555008246","doi":"10.1111/fwb.12872","title":"It is about time: genetic variation in the timing of leaf‐litter inputs influences aquatic ecosystems","year":2016,"lang":"en","type":"article","venue":"Freshwater Biology","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Kyoto University; Genome Canada","keywords":"Phenology; Biology; Ecosystem; Ecology; Plant litter; Riparian zone; Populus trichocarpa; Aquatic ecosystem; Species richness; Litter; Forest ecology; Habitat","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":[0.0002953446,0.0001609631,0.000154115,0.0002795503,0.0001856021,0.0004269945,0.0002416686,0.0001767748,0.0008500074],"category_scores_gemma":[0.0005183354,0.00008864892,0.000140486,0.0002842016,0.0003618351,0.000219005,0.0003454313,0.0002389892,0.00006439239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002887809,"about_ca_system_score_gemma":0.0002440033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002968253,"about_ca_topic_score_gemma":0.005593931,"domain_scores_codex":[0.9997309,0.0001031961,0.00001155041,0.00009117978,0.00003436515,0.0000287937],"domain_scores_gemma":[0.9994968,0.0001675095,0.0001632171,0.00004766901,0.00003348243,0.00009125847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007267452,0.0002351144,0.4904329,0.0001036347,0.0005000152,0.0002801144,0.0008862329,0.001383988,0.4848532,0.001065604,0.000275018,0.01925736],"study_design_scores_gemma":[0.000003840019,0.00008724319,0.9957683,0.000005979128,0.00004381624,0.00003733155,0.0001673164,0.00108492,0.002197817,0.000322215,0.000273644,0.000007660678],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992173,0.00006409881,0.0003512216,0.00002445443,0.000002867107,0.000002222489,0.00004853526,0.000005738953,0.0002835864],"genre_scores_gemma":[0.9995492,0.00003894302,0.0002204031,0.0000276491,0.000001573105,0.000002909698,0.00003522883,0.000004025145,0.0001200782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002968253,"threshold_uncertainty_score":0.005901933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03749186368910309,"score_gpt":0.2273764670371722,"score_spread":0.1898846033480691,"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."}}