{"id":"W2134920145","doi":"10.1016/j.ecolmodel.2008.04.001","title":"Modelling directional spatial processes in ecological data","year":2008,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":355,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gradient analysis; Ecology; Eigenfunction; Eigenvalues and eigenvectors; Spatial analysis; Spatial distribution; Forcing (mathematics); Flexibility (engineering); Process (computing); Environmental science; Computer science; Geology; Mathematics; Remote sensing; Statistics; Biology; Physics; Atmospheric sciences; Ordination","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004951826,0.0006564095,0.0009865327,0.001222337,0.0005483195,0.002318738,0.001835332,0.001829763,0.00190106],"category_scores_gemma":[0.02256047,0.001184917,0.001597975,0.002677992,0.001289657,0.003999972,0.001741837,0.002256548,0.0003527874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001656575,"about_ca_system_score_gemma":0.001374716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01958406,"about_ca_topic_score_gemma":0.02327558,"domain_scores_codex":[0.9985515,0.0007287629,0.0001273129,0.0002910961,0.0001841005,0.0001170012],"domain_scores_gemma":[0.9863901,0.01135757,0.0007012565,0.0008679117,0.0004018148,0.0002813546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003898039,0.00001999168,0.003087708,0.00006474561,0.00004033653,0.000050635,0.0001259907,0.9520196,0.0003216834,0.03613133,0.0003715028,0.007727572],"study_design_scores_gemma":[0.000005728658,0.000004416559,0.0001565652,0.000005438577,0.00000872377,0.00001250776,0.00001146766,0.9833677,0.0001215131,0.01588159,0.0004202944,0.00000406046],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07867586,0.0005007156,0.917717,0.0007345607,0.00007218481,0.00005203776,0.0007224428,0.0005351905,0.0009899203],"genre_scores_gemma":[0.8053973,0.001168519,0.1879372,0.0001112906,0.00007103187,0.0001918735,0.001393568,0.000212416,0.003516658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01958406,"threshold_uncertainty_score":0.03894013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09858268580793146,"score_gpt":0.2489609665006761,"score_spread":0.1503782806927447,"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."}}