{"id":"W1995014902","doi":"10.1890/09-0199.1","title":"Community surveys through space and time: testing the space–time interaction in the absence of replication","year":2010,"lang":"en","type":"article","venue":"Ecology","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":91,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Replication (statistics); Representation (politics); Sampling (signal processing); Interaction; Analysis of variance; Space time; Space (punctuation); Computer science; Statistical hypothesis testing; Statistics; Community structure; Spacetime; Term (time); Econometrics; Ecology; Mathematics; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002248083,0.00004823201,0.0000759243,0.000009897334,0.0002751094,0.000005384681,0.0001696353,0.0000539903,0.0001519176],"category_scores_gemma":[0.0009975809,0.00003137141,0.000009152307,0.0001316742,0.0004350138,0.00009062632,0.0001316648,0.000352799,0.0001079016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001893831,"about_ca_system_score_gemma":0.000004575419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007384735,"about_ca_topic_score_gemma":0.01364741,"domain_scores_codex":[0.9989479,0.0007022982,0.0001129368,0.0001053685,0.00004011835,0.00009137118],"domain_scores_gemma":[0.9976393,0.00196116,0.0001089657,0.0002731424,0.00001091465,0.000006529433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000003594816,0.0000660987,0.9788978,0.000002153265,0.000004651791,4.344022e-7,0.00334544,0.0002154015,0.01512027,0.001010071,0.0006830106,0.000651131],"study_design_scores_gemma":[0.00006603965,0.00005407689,0.9895124,0.000001190894,0.000002946544,0.00001215914,0.0003282067,0.006206563,0.00009451996,0.003477107,0.0002133253,0.00003145872],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820218,0.000004540653,0.00005510661,0.003570358,0.00008534654,0.0001442197,0.000001046017,0.000007659623,0.01410991],"genre_scores_gemma":[0.9989715,0.00000592975,0.0005650568,0.0001945255,0.000008219835,0.00001809905,0.000002565101,0.000002354284,0.0002317408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0169497,"threshold_uncertainty_score":0.7615575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02440081912656438,"score_gpt":0.2786523445870808,"score_spread":0.2542515254605164,"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."}}