Reply to commentary by R Duggleby (2019)
Bibliographic record
Abstract
Duggleby (2018) has made a numerical analysis of some aspects of the wide range of phenomena we reviewed in Steele et al. (2018) and asserted " .thatpanspermia as proposed by Steele et al. ( 2018) is extremely implausible."It seems to us that Duggleby has based his viewpoint on a quite narrow and specific model of Panspermia which he supposes to be active in the cosmos.Here we address both his conclusions and his numerical analysis.Our response therefore will be at two levels, his specific analysis and his general conclusions.In the specific section below we show that while Duggleby's numerical analysis appears in part correct it is, in the final analysis, quite irrelevant to Cosmic Panspermia.In the general response which follows we address his unsupported conclusion throughout his critique, namely that … " none of the examples mentioned by Steele et al. ( 2018) is decisive enough to allow no other explanation."
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.027 | 0.036 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".