{"id":"W3097072978","doi":"10.1101/2020.10.29.361303","title":"Disentangling metacommunity processes using multiple metrics in space and time","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Metacommunity; Ecology; Biological dispersal; Community structure; Abiotic component; Temporal scales; Community; Relative species abundance; Computer science; Abundance (ecology); Biology; Ecosystem","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003031843,0.00049962,0.0005425277,0.001413622,0.0003374791,0.0009594584,0.0005794899,0.0004719133,0.0006577329],"category_scores_gemma":[0.008107174,0.0002251742,0.001024712,0.0007158103,0.0008020988,0.001695412,0.0008524201,0.0006416454,0.00007313988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004644372,"about_ca_system_score_gemma":0.0004152097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004051554,"about_ca_topic_score_gemma":0.002763473,"domain_scores_codex":[0.9994169,0.0002619495,0.00004431511,0.0001266821,0.00008476101,0.00006542632],"domain_scores_gemma":[0.9931437,0.004298386,0.001167771,0.0006175993,0.0003618246,0.0004106708],"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":[0.0002032633,0.0001200762,0.1224359,0.00009376075,0.0003662259,0.00012901,0.0001937079,0.8471323,0.009342492,0.007211986,0.0002014241,0.01256985],"study_design_scores_gemma":[0.000007630388,0.0000810101,0.01938002,0.000005440221,0.00001861723,0.00003291981,0.00003848297,0.9751717,0.001283278,0.003872777,0.00009125713,0.00001683075],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9580774,0.00006539759,0.0414135,0.0000366786,0.000005616826,0.00001430043,0.0001169691,0.00007487331,0.0001951918],"genre_scores_gemma":[0.9939173,0.00001394915,0.005892292,0.000006310041,0.00000254065,0.0000127352,0.0001020928,0.00001035655,0.00004254891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004051554,"threshold_uncertainty_score":0.01603413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02187723052748638,"score_gpt":0.2300517851292924,"score_spread":0.2081745546018061,"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."}}