{"id":"W4249869384","doi":"10.22541/au.158750262.24733914","title":"Effects of precipitation extremes on nestedness and modularity of tropical seed dispersal networks","year":2020,"lang":"en","type":"dataset","venue":"Authorea","topic":"Bat Biology and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Nestedness; Frugivore; Ecology; Biology; Seed dispersal; Biological dispersal; Null model; Competition (biology); Modularity (biology); Dry season; Rainforest; Tropical and subtropical dry broadleaf forests; Trophic level; Habitat; Evolutionary biology","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":[0.0008002357,0.0005212891,0.000507006,0.001354467,0.0004295955,0.0008411117,0.00104182,0.0005003151,0.011339],"category_scores_gemma":[0.004199477,0.0002207065,0.000608652,0.001928682,0.000211349,0.0006979795,0.0009706537,0.0006456271,0.003358832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006406194,"about_ca_system_score_gemma":0.0004180849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01764168,"about_ca_topic_score_gemma":0.03475153,"domain_scores_codex":[0.9996612,0.00008284936,0.0000442481,0.0001190617,0.00003762482,0.00005507621],"domain_scores_gemma":[0.9989366,0.000451296,0.0002207706,0.0001193495,0.0001632157,0.0001087326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001495722,0.00026028,0.420528,0.003893651,0.0009765155,0.0004364899,0.001145064,0.01088779,0.002239658,0.005074889,0.5274147,0.02564721],"study_design_scores_gemma":[0.0006717003,0.0001019199,0.7216833,0.0007490714,0.00033054,0.0005023233,0.001038627,0.01155144,0.0008724284,0.00333037,0.2590673,0.000100936],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.06952714,0.0004360284,0.0002565218,0.0002065788,0.00002654745,0.0000175922,0.9277803,0.0001851093,0.001564193],"genre_scores_gemma":[0.06867655,0.0001927806,0.0007375107,0.00006772266,0.00001181351,0.00008898495,0.9293247,0.00004980962,0.0008501972],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01764168,"threshold_uncertainty_score":0.03793275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01583896757374906,"score_gpt":0.2248254795733029,"score_spread":0.2089865119995538,"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."}}