{"id":"W2975272826","doi":"10.5539/mas.v13n10p112","title":"Mapping and Analysis Factors of Affecting Productivity Tropical Rain Forests in East Kalimantan","year":2019,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Forest Ecology and Conservation","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Rainforest; Geography; Forestry; Geospatial analysis; Spatial analysis; Physical geography; Environmental science; Ecology; Cartography; Remote sensing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004137161,0.0000697811,0.0001635567,0.00005998708,0.0001185638,0.00002250497,0.0001610421,0.00004298443,0.00002178841],"category_scores_gemma":[0.00004227231,0.00003049247,0.00002775609,0.00128268,0.0002192516,0.0001330208,0.00007726916,0.00007578093,0.000001923409],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002170681,"about_ca_system_score_gemma":0.00001095987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009170989,"about_ca_topic_score_gemma":0.003047451,"domain_scores_codex":[0.9991463,0.00002391039,0.0001281766,0.0003429702,0.0001589465,0.0001997266],"domain_scores_gemma":[0.9997256,0.00008829237,0.00007271805,0.00005502532,0.00002167189,0.0000366956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007061428,0.00001797709,0.6597044,0.000002905399,0.00000314846,1.17946e-7,0.0003251418,0.0000456166,0.3368541,0.0003557269,1.588021e-7,0.002683583],"study_design_scores_gemma":[0.00005955558,0.00003154179,0.9799775,0.000003531422,0.000005157583,4.222971e-7,0.000349454,0.01555219,0.002565978,0.001385655,0.000003043621,0.00006599369],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990855,0.000006739944,0.0002257092,0.0001374436,0.00002311511,0.0001895175,0.000002143771,0.00001343876,0.0003163974],"genre_scores_gemma":[0.9998785,4.764273e-7,0.0000685664,0.00001748771,0.000008919074,0.000005102943,0.000003543165,2.924828e-7,0.00001715678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3342882,"threshold_uncertainty_score":0.1700549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669363481241465,"score_gpt":0.2087214673532187,"score_spread":0.1920278325408041,"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."}}