{"id":"W6969271831","doi":"10.5281/zenodo.8325258","title":"Labelled dataset to classify direct deforestation drivers in Cameroon","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"International Institute for Sustainable Development","funders":"UK Research and Innovation","keywords":"Deforestation (computer science); Test data; Forest cover; Logging","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004881991,0.0002715811,0.0003027601,0.0006135051,0.0003221037,0.0003798543,0.0009273494,0.0001386623,0.002104454],"category_scores_gemma":[0.001157003,0.0003006216,0.00004254732,0.001058807,0.00006934015,0.0001505416,0.0008521457,0.0006425532,0.02773824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004783729,"about_ca_system_score_gemma":0.000004269748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009102195,"about_ca_topic_score_gemma":0.00000246345,"domain_scores_codex":[0.9980947,0.0002341763,0.0004072898,0.0004666885,0.0004335845,0.0003634965],"domain_scores_gemma":[0.9989089,0.0001617732,0.00006755724,0.0005370432,0.00014642,0.0001782531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000125914,0.00003895618,4.628851e-8,0.0004324311,0.00003753802,0.0000362723,0.0001268901,0.02229557,0.00005701009,0.00009202726,0.958033,0.01883761],"study_design_scores_gemma":[0.0001683833,0.00008532788,0.000007319917,0.0001776441,0.0000271805,0.00002164003,0.00006167316,0.006141443,0.0000246,0.0008522706,0.9921371,0.0002954371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004331985,0.00007429112,0.01704655,0.0001097586,0.0003444089,0.000541549,0.9783611,0.0007260633,0.002752917],"genre_scores_gemma":[0.0001542054,0.0001813047,0.01016976,0.00008608784,0.0001182111,2.883695e-7,0.9879837,0.001264867,0.00004158672],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03410403,"threshold_uncertainty_score":0.9999446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03766769149225715,"score_gpt":0.3000655886640171,"score_spread":0.26239789717176,"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."}}