{"id":"W1989575007","doi":"10.1186/1746-4269-7-37","title":"Local Knowledge and Conservation of Seagrasses in the Tamil Nadu State of India","year":2011,"lang":"en","type":"article","venue":"Journal of Ethnobiology and Ethnomedicine","topic":"Marine and coastal plant biology","field":"Earth and Planetary Sciences","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Social Sciences and Humanities Research Council of Canada; University of Guelph; Shastri Indo-Canadian Institute","keywords":"Tamil; Biodiversity; Traditional knowledge; Geography; State (computer science); Agroforestry; Ecology; Biology; Indigenous; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0002946923,0.00011138,0.00009319177,0.001575233,0.001153183,0.001017304,0.0003641139,0.0001119568,0.001344636],"category_scores_gemma":[0.001150928,0.00009089197,0.0001064383,0.002249512,0.0008920578,0.0004992891,0.0008964681,0.0002067769,0.00008397313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008278492,"about_ca_system_score_gemma":0.001137591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0392327,"about_ca_topic_score_gemma":0.0904842,"domain_scores_codex":[0.9997547,0.00006835148,0.00002490701,0.00003710508,0.00005497211,0.00006000899],"domain_scores_gemma":[0.9988511,0.0004458513,0.0003500299,0.00007647901,0.0001251767,0.0001513726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003899641,0.00005719558,0.8761501,0.0002538669,0.00003928502,0.001595508,0.06412615,0.0002146693,0.001570742,0.00130522,0.0008875338,0.05376075],"study_design_scores_gemma":[0.000002089249,0.00004054723,0.9253798,0.0000804213,0.00002618236,0.0006034794,0.07035243,0.0001591212,0.0001454153,0.0002281303,0.002969917,0.00001260713],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973953,0.0001441554,0.00003356388,0.0001450768,0.00000154467,0.000004425173,0.00005766702,0.000002726714,0.002215549],"genre_scores_gemma":[0.9994825,0.0001573041,0.00007254812,0.00002276078,0.000001072814,0.000002466367,0.0000453763,5.590276e-7,0.0002152502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0392327,"threshold_uncertainty_score":0.07800871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02895027827515553,"score_gpt":0.2387253818959026,"score_spread":0.2097751036207471,"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."}}