{"id":"W3044515241","doi":"10.31025/2611-4135/2020.13972","title":"FREDERIC-BACK PARK, MONTREAL, CANADA: HOW 40 MILLION TONNES OF SOLID WASTE SUPPORT A PUBLIC PARK","year":2020,"lang":"en","type":"article","venue":"Detritus","topic":"Landfill Environmental Impact Studies","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Parks Canada","funders":"","keywords":"Population; Municipal solid waste; Leachate; Plan (archaeology); Environmental planning; Environmental protection; Engineering; Waste management; Geography; Civil engineering; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009164896,0.0002567331,0.0003852365,0.00002725269,0.0001313461,0.00002972156,0.0003334135,0.00007002502,0.001724887],"category_scores_gemma":[0.000143581,0.0002158854,0.00008659536,0.0003945371,0.0002243486,0.000279054,0.0004131075,0.0001220492,0.0002022982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003149422,"about_ca_system_score_gemma":0.00004802117,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1684965,"about_ca_topic_score_gemma":0.1909389,"domain_scores_codex":[0.9980887,0.00005030775,0.0002911383,0.0004127969,0.0006087151,0.0005483495],"domain_scores_gemma":[0.999068,0.00006267577,0.0001720944,0.0002965143,0.000007409198,0.0003933737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001347753,0.0003261708,0.3459282,0.00009636777,0.0002015642,0.0002014951,0.001904492,0.0007360527,0.04460363,0.000003733136,0.5967736,0.009089941],"study_design_scores_gemma":[0.003666565,0.0012823,0.5550276,0.00004191967,0.0001588571,0.00006535118,0.002977221,0.001656325,0.2005536,0.00008381257,0.2328373,0.001649144],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9698644,0.0004415199,0.00008488749,0.01184855,0.0002274219,0.0004489505,0.0002999117,0.00004646929,0.01673791],"genre_scores_gemma":[0.997522,0.0002512331,0.0001667807,0.001222174,0.00007247501,0.00001636908,0.00003153181,0.00002638358,0.0006910758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3639364,"threshold_uncertainty_score":0.9991876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176478861931018,"score_gpt":0.2031463416747863,"score_spread":0.1813815530554761,"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."}}