{"id":"W2528492400","doi":"","title":"Can our Laws Save Species Like Eria meghasaniensis","year":2016,"lang":"en","type":"article","venue":"Indian Forester","topic":"Biological Control of Invasive Species","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Scope (computer science); Endangered species; Business; Extinction (optical mineralogy); Wildlife; Plan (archaeology); Biodiversity; Environmental planning; Population; Diversity (politics); Rehabilitation; Environmental protection; Environmental resource management; Geography; Ecology; Political science; Habitat; Law; Biology; Computer science; Environmental health; Medicine; Environmental science; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001239009,0.0002067183,0.0002414724,0.0000166884,0.0001544935,0.00009710179,0.0003810521,0.0001763568,0.001336173],"category_scores_gemma":[0.000118711,0.00005301476,0.0001672164,0.0001467259,0.0001352023,0.0001333599,0.0001188327,0.00009260091,0.000538257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005038905,"about_ca_system_score_gemma":0.000007949056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009051071,"about_ca_topic_score_gemma":0.006809627,"domain_scores_codex":[0.9986465,0.00007102988,0.0002286471,0.000359009,0.0002001078,0.000494697],"domain_scores_gemma":[0.9993621,0.0001669905,0.0001001591,0.0001042754,0.00008363694,0.0001828687],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001424801,0.0001005618,0.1616688,0.000006762394,0.00008208423,0.0001536685,0.0002559504,1.81855e-7,0.6520022,0.00671728,0.0360093,0.1428608],"study_design_scores_gemma":[0.0002543594,0.0003251423,0.7571472,0.00002819011,0.000007619363,0.00001568424,0.0003257878,1.44218e-7,0.005354972,0.002561566,0.2336957,0.0002836549],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9503907,0.00006580547,0.000001591586,0.04463256,0.0003045644,0.0001909343,0.0001929678,0.00009653113,0.004124328],"genre_scores_gemma":[0.9897684,0.00002850672,0.00004793218,0.002755658,0.0007401883,0.00001724372,0.00001754778,0.000001684247,0.006622836],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6466472,"threshold_uncertainty_score":0.9995767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0270896327532426,"score_gpt":0.1990552601408654,"score_spread":0.1719656273876228,"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."}}