{"id":"W2738149591","doi":"10.3732/ajb.1700061","title":"Harnessing plant spectra to integrate the biodiversity sciences across biological and spatial scales","year":2017,"lang":"en","type":"article","venue":"American Journal of Botany","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":133,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Aeronautics and Space Administration; National Science Foundation","keywords":"Biology; Biodiversity; Ecology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005499875,0.00009502889,0.0001725305,0.00001120094,0.001082287,0.0002811486,0.0005442991,0.00002089622,0.00002852025],"category_scores_gemma":[0.0001510807,0.00004425535,0.00005021481,0.00009454315,0.003069504,0.0001674724,0.0002641499,0.0001763144,0.00003196483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005404489,"about_ca_system_score_gemma":0.000007870805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000964874,"about_ca_topic_score_gemma":0.0005711546,"domain_scores_codex":[0.9991558,0.00007050423,0.0001460786,0.0001595685,0.0002519374,0.0002161682],"domain_scores_gemma":[0.9992812,0.00006281443,0.0003848179,0.0001398907,0.00001314682,0.0001181379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009238259,0.00003522119,0.6518381,5.684859e-7,0.0000197155,0.0001065055,0.001921371,0.00009331267,0.05686573,0.000004791998,0.001515431,0.2875068],"study_design_scores_gemma":[0.00008140512,0.0003551022,0.9943056,0.00002219611,0.00000612384,0.0003289874,0.00197521,0.00009291225,0.001320232,0.00006195376,0.001361139,0.00008912082],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942589,0.00002330756,0.000510515,0.00462166,0.0001577808,0.00004171077,0.000007120153,0.000003555866,0.0003754883],"genre_scores_gemma":[0.9960772,0.00004705856,0.003514366,0.0002630876,0.00008559661,3.576672e-8,7.109381e-8,0.000001498216,0.00001111429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3424675,"threshold_uncertainty_score":0.9996436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01932750566871465,"score_gpt":0.2591112342247751,"score_spread":0.2397837285560604,"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."}}