{"id":"W4391998772","doi":"10.1038/s41597-024-02980-3","title":"Plant trait and vegetation data along a 1314 m elevation gradient with fire history in Puna grasslands, Perú","year":2024,"lang":"en","type":"article","venue":"Scientific Data","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Université de Montréal; University of British Columbia","funders":"Senter for Internasjonalisering av Utdanning; Universitetet i Bergen","keywords":"Ecosystem; Vegetation (pathology); Grassland; Biodiversity; Biomass (ecology); Ecology; Trait; Specific leaf area; Growing season; Environmental science; Plant functional type; Climate change; Geography; Threatened species; Biology; Agronomy; Botany","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":[0.0004851412,0.0003076378,0.0003296963,0.002368333,0.0005548457,0.0004954658,0.0004233961,0.0003231132,0.002084404],"category_scores_gemma":[0.00143598,0.0002355669,0.0003556919,0.004310922,0.0003355949,0.0003822633,0.00108202,0.0002933983,0.0005907865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003722454,"about_ca_system_score_gemma":0.0003877017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03716501,"about_ca_topic_score_gemma":0.05100602,"domain_scores_codex":[0.9996294,0.00009383073,0.00003437989,0.0001248731,0.00005954214,0.00005787463],"domain_scores_gemma":[0.9989477,0.0002044296,0.0003493313,0.0001652811,0.0002027685,0.0001305615],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001004423,0.00006680138,0.9847105,0.0001411376,0.0001417053,0.0002389563,0.001066741,0.0004391883,0.002445911,0.0000780892,0.002100459,0.008470057],"study_design_scores_gemma":[0.000008836325,0.00001556051,0.9974038,0.00001139863,0.0000180877,0.00009799346,0.0003970096,0.0002149018,0.00009117771,0.00002015428,0.001715199,0.000005839396],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9787578,0.0001687494,0.0002877173,0.0000572034,0.00000203533,0.00002924521,0.0200124,0.00004601128,0.0006387894],"genre_scores_gemma":[0.9318052,0.0002207435,0.001763039,0.00006177573,0.00001041124,0.0002860341,0.0650919,0.00002336559,0.0007374082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03716501,"threshold_uncertainty_score":0.07389736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03511588098095743,"score_gpt":0.2405348986465477,"score_spread":0.2054190176655902,"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."}}