{"id":"W7097466531","doi":"","title":"JP2.4 VARIATIONS AND TRENDS IN CLIMATE INDICES FOR CANADA","year":2014,"lang":"en","type":"article","venue":"","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Climate change; Variety (cybernetics); Climate system; Climate extremes; Trend analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003272016,0.0002692542,0.0001973983,0.001779328,0.001240807,0.000949678,0.0005034382,0.0002489658,0.004116189],"category_scores_gemma":[0.0009925616,0.0001604967,0.0003758208,0.003582384,0.0002399288,0.0003093734,0.0003612379,0.0004284212,0.0004465288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01573702,"about_ca_system_score_gemma":0.01953312,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9974061,"about_ca_topic_score_gemma":0.9981021,"domain_scores_codex":[0.9997638,0.00001126232,0.00001224342,0.00003529006,0.00007713184,0.0001003026],"domain_scores_gemma":[0.998596,0.00005397537,0.0001072032,0.00003187862,0.0010004,0.0002104705],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002751736,0.00004204714,0.950951,0.0000703996,0.0001614225,0.0001109114,0.000625696,0.002325399,0.001668053,0.0009119252,0.01915956,0.02369841],"study_design_scores_gemma":[0.000007410815,0.000005941704,0.9911857,0.000008813798,0.00002415698,0.00002114901,0.0004223313,0.001332306,0.000198454,0.0000395298,0.006744569,0.000009519325],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9398838,0.0006673789,0.0003171478,0.0006888364,0.00003878758,0.00002160432,0.04604453,0.0001677597,0.01217008],"genre_scores_gemma":[0.977311,0.0002971605,0.0006463602,0.00009473829,0.00001000644,0.00001225228,0.01391985,0.000042983,0.007665596],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01573702,"threshold_uncertainty_score":0.1141806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223629476961394,"score_gpt":0.2246266583606433,"score_spread":0.2123903635910293,"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."}}