{"id":"W2558333270","doi":"10.2139/ssrn.2873250","title":"Dynamic Staffing of Volunteer Gleaning Operations","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Food Waste Reduction and Sustainability","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Staffing; Volunteer; Computer science; Business; Management; Economics; Biology; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00312481,0.000249214,0.0001683276,0.0009616714,0.001734954,0.001602916,0.001142064,0.0005493893,0.01581896],"category_scores_gemma":[0.00903682,0.000213954,0.0001549435,0.0007519815,0.0003869289,0.00122396,0.002510273,0.0007004991,0.001491305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002620788,"about_ca_system_score_gemma":0.006426211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006519932,"about_ca_topic_score_gemma":0.01586514,"domain_scores_codex":[0.9980082,0.0005992979,0.00005835136,0.0002187607,0.0002383963,0.0008771091],"domain_scores_gemma":[0.991241,0.001511789,0.0007353295,0.0005614398,0.001011078,0.004939458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00310388,0.002624925,0.1298346,0.0003839202,0.00007735883,0.0009597416,0.01211725,0.04006125,0.009226748,0.01417048,0.05788971,0.7295501],"study_design_scores_gemma":[0.0006260486,0.006177821,0.3883392,0.0007015545,0.0001041426,0.0008413545,0.1036964,0.1491557,0.005167966,0.03683605,0.3080469,0.0003069401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9312093,0.0001845397,0.01248878,0.003438489,0.000259665,0.0005500391,0.000377932,0.0005072284,0.05098417],"genre_scores_gemma":[0.9875801,0.00005375799,0.004077474,0.0001173364,0.00004806993,0.0001413055,0.0001777171,0.00004190627,0.007762312],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01581896,"threshold_uncertainty_score":0.05291969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005879703919017308,"score_gpt":0.2144037790179109,"score_spread":0.2085240750988936,"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."}}