{"id":"W4297826356","doi":"10.5194/essd-14-4077-2022","title":"Global datasets of leaf photosynthetic capacity for ecological and earth system research","year":2022,"lang":"en","type":"article","venue":"Earth system science data","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; University of Toronto","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Photosynthesis; Satellite; Photosynthetic capacity; Atmospheric sciences; Environmental science; Mathematics; Botany; Physics; Biology","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":[],"consensus_categories":[],"category_scores_codex":[0.005450668,0.00009764641,0.0001827739,0.00006816375,0.0009704807,0.00008655478,0.001611129,0.00003335123,0.00008532819],"category_scores_gemma":[0.0001075073,0.00008197925,0.0000197097,0.0008454933,0.000887666,0.000414073,0.002860288,0.000128899,0.00003326656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002384223,"about_ca_system_score_gemma":0.00008360401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007884455,"about_ca_topic_score_gemma":0.0003389928,"domain_scores_codex":[0.9972779,0.0002441072,0.0002796725,0.0006985093,0.001055919,0.0004439596],"domain_scores_gemma":[0.9985356,0.000118961,0.0001032549,0.001075732,0.0000187153,0.0001477568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00105225,0.002484982,0.3934015,0.004080816,0.0002320601,0.0005718577,0.003514445,0.1751839,0.1425304,0.1964065,0.03230232,0.04823906],"study_design_scores_gemma":[0.000446679,0.0003133637,0.02402685,0.00006035018,0.00002098885,0.0004873425,0.001315925,0.9409809,0.0003057351,0.00006078837,0.0317203,0.0002608266],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9689042,0.00002033275,0.0004789638,0.00003308627,0.0001986915,0.0006607744,0.02751915,0.00003338736,0.002151432],"genre_scores_gemma":[0.9977148,0.00000172064,0.00166577,0.00000828607,0.00001093753,0.00004162573,0.0005036026,0.000003769936,0.00004950012],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.765797,"threshold_uncertainty_score":0.7464252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06897073284752128,"score_gpt":0.2981095917566041,"score_spread":0.2291388589090828,"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."}}