{"id":"W2790696652","doi":"10.1007/s11258-018-0819-1","title":"Investigating detection success: lessons from trials using decoy rare plants","year":2018,"lang":"en","type":"article","venue":"Plant Ecology","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Environment and Protected Areas; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Biodiversity Monitoring Institute; University of Alberta; Alberta Conservation Association","keywords":"Abundance (ecology); Decoy; Ecology; Biology; Biodiversity; Relative species abundance; Understory; Plant ecology; Rare species; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005952096,0.0001196817,0.0003026068,0.00004431344,0.0005319539,0.00001497393,0.0001393458,0.0001614364,0.001327289],"category_scores_gemma":[0.0006380707,0.000109719,0.00003755388,0.00008776493,0.0003443355,0.0001288419,0.0001498578,0.0001240789,0.0004900682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001185567,"about_ca_system_score_gemma":0.00001629184,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006994376,"about_ca_topic_score_gemma":0.05508777,"domain_scores_codex":[0.9987019,0.0003076381,0.0003324745,0.0003003825,0.0000814048,0.0002762354],"domain_scores_gemma":[0.9986238,0.0009527053,0.0002432945,0.000109498,0.000009340404,0.00006136833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003464401,0.0000410531,0.9666016,0.000003591352,0.00007842924,0.00001350536,0.0009382994,0.0006533421,0.02880953,0.0001033535,0.0005054309,0.002217193],"study_design_scores_gemma":[0.0006030272,0.0001329478,0.9297502,0.00001350928,0.00005964754,0.00004059416,0.0002482312,0.054571,0.007036043,0.006666755,0.0006494675,0.000228558],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962837,0.00002063084,0.0009590623,0.0002512822,0.0008407658,0.0001540235,0.0001094562,0.00004719441,0.001333941],"genre_scores_gemma":[0.9974958,0.00002043408,0.001756108,0.0004408731,0.0001638697,0.00001862996,0.0000433342,0.000008038303,0.00005292818],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05438834,"threshold_uncertainty_score":0.9995856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0676542179036519,"score_gpt":0.315881428266968,"score_spread":0.2482272103633161,"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."}}