{"id":"W2994151768","doi":"","title":"A Geospatial Analysis of the Portland-Montreal Pipeline on Water Resources and Conserved Lands in Maine","year":2013,"lang":"en","type":"article","venue":"Digital Commons - Colby (Colby College)","topic":"Archaeology and Natural History","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Department of Transportation","keywords":"Geospatial analysis; Pipeline (software); Geography; Archaeology; Environmental resource management; Environmental planning; Environmental science; Cartography; Engineering","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":[0.0003766436,0.0001619974,0.0004211886,0.0002984687,0.0004382658,0.00002031829,0.0003583461,0.0001737275,0.0002159084],"category_scores_gemma":[0.0001520433,0.0001039154,0.0001539142,0.000807696,0.001059112,0.0002086341,0.0002069902,0.0002472296,0.00001338397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008775473,"about_ca_system_score_gemma":0.00006954056,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01460635,"about_ca_topic_score_gemma":0.2215709,"domain_scores_codex":[0.998428,0.000262466,0.0003676179,0.0002579204,0.0003168097,0.0003672062],"domain_scores_gemma":[0.9989295,0.0004559289,0.0001179714,0.0002747373,0.0001015891,0.0001202813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004419433,0.0003306838,0.9699185,0.0000129842,0.0002883864,0.00003597311,0.01563543,0.00006513819,0.00006099391,0.001649327,0.009084748,0.002475821],"study_design_scores_gemma":[0.001581993,0.0002221571,0.9273492,0.0000391482,0.0002033161,0.000002495599,0.001881864,0.001095844,0.0001054418,0.003306364,0.06387552,0.0003366988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9559248,0.0001898103,0.00000267163,0.002785773,0.00009495553,0.0005443652,0.0001924543,0.00003023231,0.04023492],"genre_scores_gemma":[0.992644,0.00002140491,0.000009890935,0.0002422665,0.00004210044,0.00004051768,0.00004160025,0.000008975335,0.006949279],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2069646,"threshold_uncertainty_score":0.9919555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009727107037403216,"score_gpt":0.2311601431623101,"score_spread":0.2214330361249069,"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."}}