{"id":"W2744195930","doi":"10.5194/cp-14-559-2018","title":"Recent climate variations in Chile: constraints from borehole temperature profiles","year":2018,"lang":"en","type":"article","venue":"Climate of the past","topic":"Climate change and permafrost","field":"Earth and Planetary Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University; Université du Québec à Montréal","funders":"Canada Excellence Research Chairs, Government of Canada","keywords":"Climatology; Borehole; Proxy (statistics); Climate model; Period (music); Geology; Climate change; Environmental science; Temperature record; Physical geography; Geography; Oceanography","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002522374,0.0001447659,0.0001964659,0.00005758963,0.0002326078,0.0000415123,0.0003239922,0.00009649283,0.01154489],"category_scores_gemma":[0.00003852638,0.00009713978,0.00005964488,0.0003244328,0.0003373284,0.0001175444,0.00005654567,0.000160782,0.00033526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006619783,"about_ca_system_score_gemma":0.00003042236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007242496,"about_ca_topic_score_gemma":0.01264296,"domain_scores_codex":[0.9988074,0.00009132898,0.0003074472,0.0002363946,0.0001768629,0.0003805989],"domain_scores_gemma":[0.9992923,0.0001000179,0.0001468141,0.0003299192,0.00006419771,0.00006671957],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004035888,0.00003579717,0.9923885,0.00002118293,0.000009542761,0.00000257802,0.0008268975,0.0000161806,0.002417499,0.0001007281,0.001219783,0.002920973],"study_design_scores_gemma":[0.0003254527,0.0000499667,0.9935454,0.0001207633,0.00001653545,0.000005548952,0.0004232521,0.0004914477,0.001073785,0.0002914008,0.003520449,0.000135965],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9636871,0.0003091819,5.587973e-7,0.001306868,0.0008696783,0.0002576164,0.01868862,0.00002279495,0.01485763],"genre_scores_gemma":[0.9958764,0.00113724,0.0001782032,0.0004003176,0.000422096,0.000002897353,0.001955006,0.000006429136,0.00002145127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0321893,"threshold_uncertainty_score":0.9893587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02386418762192606,"score_gpt":0.2407065525175545,"score_spread":0.2168423648956284,"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."}}