{"id":"W2029241378","doi":"10.1016/j.techsoc.2014.10.003","title":"Beyond appropriate technology: Social considerations for the sustainable use of Arsenic–Iron Removal Plants in rural Bangladesh","year":2014,"lang":"en","type":"article","venue":"Technology in Society","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Government of Canada; Canadian International Development Agency; University of Guelph","keywords":"Sanitation; Sustainability; Scarcity; Business; Natural resource economics; Arsenic; Developing country; Economic growth; Appropriate technology; Environmental planning; Engineering; Political science; Environmental engineering; Geography; Economics; Ecology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003533179,0.0002735928,0.000253423,0.00078336,0.005507169,0.004706572,0.0006805981,0.003240918,0.007675544],"category_scores_gemma":[0.00657318,0.0001298526,0.0001882419,0.001001613,0.008669996,0.002775073,0.003637262,0.001908326,0.0003667117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007007093,"about_ca_system_score_gemma":0.01372791,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01963512,"about_ca_topic_score_gemma":0.05219227,"domain_scores_codex":[0.9957436,0.002609591,0.0001265401,0.0001514889,0.0005412454,0.0008275272],"domain_scores_gemma":[0.9957189,0.002145058,0.0006639464,0.000137463,0.0008157379,0.0005188598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001494404,0.0002105705,0.03240233,0.0006634865,0.00007589639,0.004423807,0.03794556,0.003127879,0.007320795,0.8266589,0.01829771,0.06872358],"study_design_scores_gemma":[0.00003975276,0.0003025281,0.03922026,0.0008794452,0.00009918321,0.001491605,0.2109755,0.001612283,0.004336736,0.4120598,0.328874,0.0001089296],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3959956,0.003506568,0.004978805,0.367418,0.0001870766,0.0001045661,0.0001653281,0.00002023736,0.2276238],"genre_scores_gemma":[0.9922696,0.00121461,0.0003259349,0.002226252,0.00005040945,0.00002644532,0.000009901213,0.000005431774,0.003871429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9944928,"threshold_uncertainty_score":0.05084026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01153357629165456,"score_gpt":0.2350146178415655,"score_spread":0.2234810415499109,"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."}}