{"id":"W2134097784","doi":"10.1007/s10980-007-9168-5","title":"Using the landscape morphometric context to resolve spatial patterns of submerged macrophyte communities in a fluvial lake","year":2007,"lang":"en","type":"article","venue":"Landscape Ecology","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"GDG Environnement; Université de Montréal","funders":"","keywords":"Macrophyte; Bay; Landscape ecology; Ecology; Context (archaeology); Species richness; Spatial variability; Geography; Transect; Fluvial; Aquatic plant; Environmental science; Physical geography; Geology; Habitat; Biology; Geomorphology; Structural basin","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007471414,0.0001364133,0.0002905767,0.00017567,0.0001254224,0.00001607873,0.0003900663,0.00009038563,0.004192226],"category_scores_gemma":[0.00002215475,0.00009301193,0.00005310778,0.0004595554,0.00002440309,0.00007234478,0.0002793933,0.0001593015,0.0001092278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003881519,"about_ca_system_score_gemma":0.00000954295,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01071261,"about_ca_topic_score_gemma":0.728758,"domain_scores_codex":[0.9987008,0.0001402217,0.0003769853,0.0001692223,0.0001726273,0.0004401333],"domain_scores_gemma":[0.9992477,0.0002349038,0.0001243133,0.0003043084,0.00001260041,0.00007621817],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001403176,0.00006644228,0.9954847,0.00001626317,0.00001387249,0.00002465835,0.001615576,0.001201852,0.000368792,0.000006444269,0.0001532066,0.0009078747],"study_design_scores_gemma":[0.0008709318,0.0001995309,0.9900187,0.00001922611,0.00001583149,0.00002062744,0.002218945,0.00341028,0.0005176956,0.00002043816,0.00253754,0.0001502818],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973781,0.00004609811,0.0003470123,0.0001088488,0.0004001116,0.0002570832,0.00003655496,0.00001386178,0.001412398],"genre_scores_gemma":[0.9992918,0.00002057636,0.0001099888,0.000397526,0.0001039941,0.00001267308,0.00002007449,0.00001317237,0.00003020635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7180455,"threshold_uncertainty_score":0.996718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865592998163292,"score_gpt":0.2410613622269399,"score_spread":0.222405432245307,"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."}}