{"id":"W3205503685","doi":"10.13031/trans.14253","title":"The Development of a GIS-Based Framework to Locate Biomass and Municipal Solid Waste Collection Points for an Optimal Waste Conversion Facility","year":2021,"lang":"en","type":"article","venue":"Transactions of the ASABE","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Municipal solid waste; Biomass (ecology); Environmental science; Bioenergy; Raw material; Geographic information system; Agriculture; Waste management; Environmental engineering; Biofuel; Engineering; Geography; Remote sensing; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0001775859,0.00008922609,0.0001108076,0.00005200677,0.0002298116,0.00001719057,0.0001282945,0.00004985259,0.00001837191],"category_scores_gemma":[0.00001737316,0.00006838561,0.00005816849,0.0003054978,0.00005622041,0.0000504074,0.00001329938,0.00005184326,0.000001174554],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004795843,"about_ca_system_score_gemma":0.00003912017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009673218,"about_ca_topic_score_gemma":0.000324258,"domain_scores_codex":[0.9993696,0.00003214658,0.0002338136,0.0001154229,0.0001213807,0.0001275853],"domain_scores_gemma":[0.9995018,0.00005701103,0.00003555372,0.0002724009,0.0000864064,0.00004679535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008571638,0.0004380702,0.0002519892,0.001437459,0.0006257608,5.341244e-7,0.009492441,0.9026214,0.06246268,0.0003327642,0.0007758654,0.02070391],"study_design_scores_gemma":[0.0006167047,0.00009484306,0.0004413427,0.00007517531,0.0000579456,6.879537e-7,0.002786766,0.275883,0.7166963,0.00007065383,0.003152489,0.0001240215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4224817,0.00003671135,0.5766098,0.0002295594,0.0002253763,0.0003026687,0.000028028,0.00003741993,0.00004867585],"genre_scores_gemma":[0.986023,0.00001111804,0.0137299,0.00001955882,0.000004404517,0.00004135671,0.000008200578,0.00000913106,0.0001533115],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6542336,"threshold_uncertainty_score":0.2788684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0255178718911179,"score_gpt":0.2553976855127585,"score_spread":0.2298798136216406,"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."}}