{"id":"W1747086240","doi":"10.3968/j.ccc.1923670020070302.002","title":"Forest Eco-ervironment Protecyion ＆ Population Restriction","year":2010,"lang":"en","type":"article","venue":"Cross-cultural communication","topic":"Sustainability, Environment, and Optimization Algorithms","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Population; Ecology; Ethnology; Forestry; Sociology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.000431651,0.0001913586,0.0001232458,0.00003339199,0.0008063807,0.0002349403,0.0004740633,0.0001815516,0.001265424],"category_scores_gemma":[0.0001817008,0.0001697166,0.00007282588,0.0002355108,0.0004662597,0.001321346,0.0003547638,0.0003895042,0.0003522922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004584001,"about_ca_system_score_gemma":0.000005476043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008604685,"about_ca_topic_score_gemma":0.0005419236,"domain_scores_codex":[0.9985234,0.0001126972,0.000373169,0.000373272,0.000353823,0.0002636412],"domain_scores_gemma":[0.9985785,0.00004123226,0.0002318551,0.001006582,0.00003277748,0.0001090758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004519118,0.0003027167,0.911566,0.00001539033,0.00000931881,7.21232e-7,0.000565446,0.04686664,0.01358252,0.00150126,0.0006361266,0.02490866],"study_design_scores_gemma":[0.0003338012,0.00004482573,0.9586262,0.000004875484,0.00001145952,0.00000521966,0.0001682237,0.01283824,0.0008189504,0.002998519,0.0238998,0.000249957],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935002,0.00002131819,0.0005932213,0.000673742,0.0001778378,0.0007352636,0.000004780096,0.0001444366,0.004149257],"genre_scores_gemma":[0.9910966,0.0001544263,0.007033278,0.00009769746,0.00005746237,0.0001544728,0.0003988333,0.0000206913,0.0009865497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04706011,"threshold_uncertainty_score":0.9996476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021992507035609,"score_gpt":0.2832726781503822,"score_spread":0.2730527530800261,"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."}}