{"id":"W7125884919","doi":"","title":"Common structure in panels of short ecological time-series.","year":2000,"lang":"en","type":"article","venue":"PubMed Central","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Regression; Sample (material); Statistical hypothesis testing; Regression analysis; Test (biology); Linear regression; Food chain","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003273838,0.0001219679,0.0002566781,0.00004466093,0.0000258593,0.00003448374,0.0005709848,0.0001189085,0.0003082725],"category_scores_gemma":[0.0000184497,0.00009938977,0.00005929962,0.0002440611,0.00005811278,0.0002523536,0.00006852276,0.000184148,0.000004794563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006054727,"about_ca_system_score_gemma":0.00004350291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001327221,"about_ca_topic_score_gemma":0.00002132833,"domain_scores_codex":[0.9983409,0.0001401836,0.0002497209,0.0002732302,0.0001634703,0.0008324888],"domain_scores_gemma":[0.9993961,0.00003852536,0.00002897102,0.0003247125,0.0000108351,0.0002008311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00003027483,0.0001243743,0.01209607,0.00001062704,0.00001185981,0.00004943201,0.0004828753,0.0001629791,0.0006115975,0.01902204,0.0002986038,0.9670992],"study_design_scores_gemma":[0.0002879797,0.00005490809,0.9571137,0.000007375315,0.000005713291,0.00003563859,0.000002412979,0.004518316,0.004836876,0.02945396,0.003473702,0.0002094289],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8757117,0.0001088033,0.1137549,0.000604019,0.0003463175,0.0004102549,0.00001706831,0.00008213993,0.008964811],"genre_scores_gemma":[0.9126335,0.00002877536,0.08659234,0.0002062782,0.00007870153,0.00001596806,0.000003917733,0.000005874602,0.000434618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9668899,"threshold_uncertainty_score":0.4052997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01380277490859967,"score_gpt":0.2304740131242806,"score_spread":0.2166712382156809,"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."}}