{"id":"W7020544332","doi":"","title":"Landen worden het eens in Montreal: een ‘Parijs-moment’ voor biodiversiteit","year":2022,"lang":"nl","type":"other","venue":"Socio-Environmental Systems Modeling","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Identification (biology); Term (time); Perspective (graphical)","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"category_scores_codex":[0.002104017,0.002529019,0.002981093,0.001537072,0.001215708,0.0004541589,0.002147479,0.001819312,0.06600236],"category_scores_gemma":[0.00001931038,0.003002034,0.001052951,0.0006736623,0.0004732214,0.0005724276,0.002752459,0.002759322,0.09767929],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01684443,"about_ca_system_score_gemma":0.000158422,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03800642,"about_ca_topic_score_gemma":0.0002314616,"domain_scores_codex":[0.9857993,0.001922114,0.002492975,0.003486207,0.003419553,0.002879909],"domain_scores_gemma":[0.9951556,0.0001297288,0.001758571,0.002126682,0.0000158684,0.0008136037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003856884,0.001530549,0.6366137,0.0006621641,0.002285699,0.0008078574,0.008004454,0.2592604,0.0006685804,0.00003284323,0.0894268,0.0003212465],"study_design_scores_gemma":[0.01403691,0.0005388978,0.003298319,0.002176776,0.002021156,0.0002294278,0.4152093,0.230693,0.000001455972,0.00009685574,0.323756,0.007941852],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6477122,0.04268597,0.000790071,0.0003440111,0.005509111,0.01397514,0.03271436,0.001179042,0.2550901],"genre_scores_gemma":[0.6676211,0.001689833,0.00008962657,0.00008952565,0.0009615442,0.0006029916,0.004803748,0.002023147,0.3221185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6333154,"threshold_uncertainty_score":0.9995413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01689972583530196,"score_gpt":0.2107670144862649,"score_spread":0.1938672886509629,"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."}}