{"id":"W1830627288","doi":"10.1139/x2012-140","title":"A heuristic approach to automated forest road location","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest Biomass Utilization and Management","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations; Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Computer science; Set cover problem; Heuristic; Greedy randomized adaptive search procedure; Greedy algorithm; Graph; Set (abstract data type); Mathematical optimization; GRASP; Mathematics; Artificial intelligence; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.000782844,0.0007882332,0.0009497906,0.001276574,0.0006245006,0.0009523981,0.001652438,0.001067068,0.003278829],"category_scores_gemma":[0.00215514,0.000510552,0.0006839555,0.001317991,0.0006613072,0.0008622823,0.0006924592,0.000663007,0.0004066142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009344234,"about_ca_system_score_gemma":0.00246291,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007954052,"about_ca_topic_score_gemma":0.0109092,"domain_scores_codex":[0.9993788,0.0002568373,0.0000285414,0.0001068531,0.0001315032,0.0000973478],"domain_scores_gemma":[0.9991447,0.0005210093,0.0001165334,0.00008308927,0.00009462381,0.00004010447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006830598,0.000102124,0.0004827574,0.00009288001,0.00003211835,0.0001175966,0.00005719994,0.9199277,0.001506577,0.006770844,0.001519918,0.06932205],"study_design_scores_gemma":[0.00002226768,0.0000303829,0.00007311995,0.000006455956,0.000009110317,0.00002979479,0.00002362854,0.996774,0.0003987449,0.001876619,0.0007484932,0.00000728778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03367699,0.0002565117,0.9592441,0.0001863198,0.00004491763,0.000243481,0.0001627946,0.001091682,0.0050931],"genre_scores_gemma":[0.3393143,0.0001876396,0.658394,0.00008328747,0.00002760407,0.0002644911,0.0002439739,0.00008446249,0.001400245],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9920459,"threshold_uncertainty_score":0.01581556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04855201591770519,"score_gpt":0.2993479467602172,"score_spread":0.250795930842512,"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."}}