{"id":"W7086945845","doi":"10.5281/zenodo.17058755","title":"Data and Code for \"Quantifying land-use metrics for solar photovoltaic projects in the western United States\"","year":2025,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Photovoltaic Systems and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Adobe; Code (set theory); Software; Photovoltaic system; Data file; Data format; Order (exchange)","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.003020522,0.0002442406,0.0002904614,0.0003446547,0.001375561,0.001041595,0.002338877,0.0001507676,0.0002483411],"category_scores_gemma":[0.004067837,0.0002010455,0.00004400501,0.001189886,0.0002006421,0.0003546541,0.003001364,0.0003552846,0.00005630039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002973858,"about_ca_system_score_gemma":0.00001196948,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0027039,"about_ca_topic_score_gemma":0.0004907909,"domain_scores_codex":[0.9973352,0.0005120286,0.0004103662,0.0008283454,0.0004208211,0.0004932197],"domain_scores_gemma":[0.9977331,0.0004327355,0.0001945472,0.001373923,0.00016665,0.00009908242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000948523,0.0001244151,0.000180533,0.0006113317,0.00002514283,0.00000801272,0.0004118837,0.00004003716,0.00004125641,0.000003476498,0.9969976,0.001461454],"study_design_scores_gemma":[0.0006846623,0.0001664723,0.0004208554,0.00006308944,0.0000438076,0.00001845082,0.000543953,0.004017916,0.00001335645,0.00003738894,0.9937717,0.000218367],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003391694,0.00005291714,0.00154318,0.0001915462,0.00007980043,0.003466988,0.9910687,0.00009358399,0.0001115995],"genre_scores_gemma":[0.001663218,0.0002613138,0.0001537336,0.0004121128,0.00004595765,0.000001861075,0.9968275,0.0002755685,0.0003586756],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.005758869,"threshold_uncertainty_score":0.9999954,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1010490661235359,"score_gpt":0.3088784719626917,"score_spread":0.2078294058391558,"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."}}