{"id":"W2957423647","doi":"10.1002/aqc.3157","title":"Macrophytes promote aquatic insect conservation in artificial ponds","year":2019,"lang":"en","type":"article","venue":"Aquatic Conservation Marine and Freshwater Ecosystems","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Global Risk Institute in Financial Services","keywords":"Macrophyte; Species richness; Biodiversity; Ecology; Wetland; Aquatic plant; Vegetation (pathology); Aquatic insect; Species diversity; Biology; Environmental science; Habitat","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001942763,0.0001382866,0.0001518754,0.0002675616,0.0004034858,0.0005233639,0.0001700481,0.0001362496,0.001765143],"category_scores_gemma":[0.0005112221,0.00008186505,0.0001489927,0.0002468485,0.0004201352,0.0003028536,0.0006447008,0.0001514996,0.0001140768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003877758,"about_ca_system_score_gemma":0.0003392976,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001797736,"about_ca_topic_score_gemma":0.01085077,"domain_scores_codex":[0.9998267,0.00004822325,0.00001109393,0.00002979525,0.00004025301,0.00004390764],"domain_scores_gemma":[0.9993586,0.00009351948,0.0002289337,0.00003060512,0.00007752652,0.0002107188],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001667486,0.000655874,0.5656472,0.000476876,0.0001609394,0.0006618286,0.0009980847,0.001749204,0.3759429,0.0003894109,0.0007550737,0.05089498],"study_design_scores_gemma":[0.00001034823,0.0004174513,0.9951617,0.00001037527,0.00001448393,0.00006835732,0.0003504957,0.0005637205,0.002508413,0.00007734406,0.0008134128,0.000003848377],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992965,0.00004670539,0.0001059108,0.000007455798,0.000001508822,0.000006909916,0.00003213368,0.000008086743,0.0004945956],"genre_scores_gemma":[0.9993197,0.00003294652,0.0003081313,0.00001295372,0.000002634873,0.000006558026,0.00004348256,0.000001930814,0.0002715867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001797736,"threshold_uncertainty_score":0.005904973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01427397158183834,"score_gpt":0.1914535712760126,"score_spread":0.1771795996941742,"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."}}