{"id":"W4386836035","doi":"10.1360/n072022-0348","title":"全球变暖背景下中国森林春季木质部物候提前的模拟证据","year":2023,"lang":"zh","type":"article","venue":"SCIENTIA SINICA Terrae","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Psychology","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":[0.002419674,0.0004779091,0.0005194285,0.000839766,0.0009806722,0.0007980632,0.001412238,0.0002785777,0.01203699],"category_scores_gemma":[0.000633837,0.0004346908,0.0003450755,0.003636944,0.0009210169,0.0005920149,0.0002775126,0.0004563287,0.067617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002334463,"about_ca_system_score_gemma":0.0004143014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007322432,"about_ca_topic_score_gemma":0.001992223,"domain_scores_codex":[0.9944352,0.0004299739,0.0007834968,0.001307501,0.001255926,0.001787926],"domain_scores_gemma":[0.9968951,0.0008877542,0.0002615608,0.001200531,0.00009466439,0.0006604434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004453885,0.0002580771,0.5572564,0.0003535839,0.0002731598,0.0008693141,0.002981112,0.00188409,0.001772309,0.001079097,0.272189,0.1606385],"study_design_scores_gemma":[0.0005628645,0.0002819283,0.7813147,0.0001773191,0.00007843847,0.00004243661,0.0004649795,0.00708813,0.0001115604,0.0009454621,0.2083189,0.0006132918],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8658171,0.001907253,0.00001519387,0.006095945,0.01025546,0.000522199,0.001005679,0.00108405,0.1132971],"genre_scores_gemma":[0.9717869,0.0005934103,0.0003156716,0.0004102604,0.0004530309,0.000003715623,0.0003211827,0.00002985262,0.02608603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2240583,"threshold_uncertainty_score":0.9998105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04586535058717092,"score_gpt":0.2821382473035937,"score_spread":0.2362728967164227,"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."}}