{"id":"W7100027483","doi":"","title":"Collembola in successional coastal temperate forests on","year":2002,"lang":"en","type":"article","venue":"","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Species richness; Chronosequence; Abundance (ecology); Temperate rainforest; Biodiversity; Ecological succession; Fauna; Species diversity; Forest floor; Litter","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001752477,0.0001969028,0.0001428467,0.000597318,0.0009075683,0.0005461442,0.0002062432,0.0001300133,0.001388377],"category_scores_gemma":[0.000351168,0.0001225565,0.00008421531,0.0005218511,0.0002654355,0.0001952961,0.000496368,0.0001846259,0.000210111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001021615,"about_ca_system_score_gemma":0.0005982812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1456939,"about_ca_topic_score_gemma":0.4879178,"domain_scores_codex":[0.9998699,0.00001087497,0.000005970241,0.00002710094,0.00003022977,0.00005582138],"domain_scores_gemma":[0.9997175,0.0000278711,0.00006337294,0.00001139739,0.00008920293,0.00009068841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002371488,0.00009290705,0.9489648,0.00006793123,0.0000232595,0.0006935663,0.002304931,0.00006541904,0.02597878,0.00007402373,0.0002258567,0.02127124],"study_design_scores_gemma":[0.000001731172,0.00001608234,0.9991255,0.000004012036,0.000001992889,0.00004204275,0.0003600565,0.00001474196,0.00009943867,0.000003976576,0.0003294041,0.000001017501],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987865,0.0001635753,0.0000122426,0.000008299309,0.000001110972,0.000007078913,0.00007920008,0.000001785421,0.0009402767],"genre_scores_gemma":[0.9980197,0.0002889146,0.0001059028,0.00002172434,0.000003960429,0.000009443937,0.0004154441,0.000001001914,0.001133912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1456939,"threshold_uncertainty_score":0.2896917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05623740571813355,"score_gpt":0.2114754794406718,"score_spread":0.1552380737225383,"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."}}