{"id":"W2905755634","doi":"10.1002/ecm.1350","title":"Trajectory analysis in community ecology","year":2018,"lang":"en","type":"article","venue":"Ecological Monographs","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":141,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Université de Montréal","funders":"Smithsonian Institution","keywords":"Trajectory; Perspective (graphical); Computer science; Variety (cybernetics); Variation (astronomy); Space (punctuation); Data science; Ecology; Domain (mathematical analysis); Community; Community structure; Data mining; Artificial intelligence; Mathematics; Habitat","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":[0.005102057,0.000656153,0.000875829,0.006064847,0.001139979,0.002299498,0.001416309,0.00113061,0.003630892],"category_scores_gemma":[0.02099844,0.0003426351,0.001257202,0.004402146,0.002891875,0.00358279,0.002278727,0.001580479,0.0004003413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003045017,"about_ca_system_score_gemma":0.001577138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01461904,"about_ca_topic_score_gemma":0.007542878,"domain_scores_codex":[0.9973839,0.001778294,0.00009495833,0.0003371243,0.0002878658,0.0001178496],"domain_scores_gemma":[0.9832857,0.01203448,0.001434987,0.001157624,0.001496635,0.000590594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004572291,0.00004963349,0.014633,0.0001870276,0.0001454388,0.0001306908,0.0007244736,0.2386741,0.0006512342,0.6836945,0.001855793,0.05920834],"study_design_scores_gemma":[0.000006780229,0.00001779342,0.001766889,0.00004002627,0.00001280692,0.00003526281,0.0002090465,0.6591337,0.0001371522,0.3349225,0.003702918,0.00001523089],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03195852,0.001088999,0.9625776,0.0007725187,0.00005719521,0.00008952105,0.0004136294,0.0002425642,0.002799289],"genre_scores_gemma":[0.5907048,0.001286613,0.4037853,0.0001135283,0.000129732,0.0003361671,0.0008193735,0.0001546182,0.002669925],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01461904,"threshold_uncertainty_score":0.02906787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526486304283983,"score_gpt":0.255590956932276,"score_spread":0.2403260938894361,"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."}}