{"id":"W2626828989","doi":"10.1016/j.grj.2017.06.001","title":"Soil legacy data rescue via GlobalSoilMap and other international and national initiatives","year":2017,"lang":"en","type":"article","venue":"GeoResJ","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"European Commission; Bill and Melinda Gates Foundation","keywords":"Database; Computer science; Data science","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":[0.01139112,0.001251002,0.000691388,0.01078803,0.0008241919,0.003915105,0.002577053,0.001094754,0.02139204],"category_scores_gemma":[0.02227068,0.0005462814,0.0009557265,0.0167597,0.0007378398,0.005964342,0.006765164,0.001700897,0.01565658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118794,"about_ca_system_score_gemma":0.004780272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01507193,"about_ca_topic_score_gemma":0.01205047,"domain_scores_codex":[0.9942381,0.001195812,0.0006027406,0.0008957995,0.002653412,0.0004141351],"domain_scores_gemma":[0.9811307,0.00238634,0.001563332,0.007367141,0.006695929,0.0008565685],"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":[0.0002225531,0.000152628,0.01873194,0.001707672,0.0002286045,0.0003817123,0.001558374,0.003961375,0.002712785,0.02656439,0.5253838,0.4183942],"study_design_scores_gemma":[0.00002987408,0.00002440973,0.005957953,0.0003171627,0.00003339509,0.0001092653,0.0005594284,0.001627262,0.001821781,0.004640762,0.9848332,0.00004551562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.0230209,0.003687288,0.2038448,0.006345125,0.001613915,0.001304942,0.5171319,0.05042631,0.1926249],"genre_scores_gemma":[0.04779218,0.002457193,0.2554947,0.001370677,0.0002513885,0.001503391,0.6561924,0.009724037,0.02521411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02139204,"threshold_uncertainty_score":0.07156354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03920970807795823,"score_gpt":0.3078302376910173,"score_spread":0.268620529613059,"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."}}